importance of academic skills in higher education

The importance of study skills in HE for learners to enhance and develop their studies further

B y   Giedrius   Zilionis ,   Senior  Business  Lecturer   and  Alexander Kaiser ,   Health  Lecturer

Study skills are some of the most essential academic tools in Higher Education. All learners have different skills and sometimes these are not fully recognised or developed – simply because, ironically, study skills are not implemented.  By effectively using study skills, learners can discover hidden talents and how well these can be of benefit to them during their studies and beyond.

Benefits of academic skills

There are discussions as to whether or not academic skills should be prioritised in the teaching of undergraduate students, since employers argue that many students are not equipped with the job-related skills that are needed, even after 3 years of degree education (Menz, 2021).  However, according to Hermida (2009) most first-year students lack necessary basic academic skills such as reading, because academic reading differs greatly from the reading that is undertaken in Secondary Education.  Students need to learn academic language and familiarise themselves with the key contributors to their respective fields. Others such as Blades and Gibb (2012) argue that academic skills such as taking responsibility, undertaking research and communicating findings are important when it comes to employability.

Why do we need skills?

Skills are necessary for every aspect of human life. These skills allow us to do something right and well. Skills are learned and developed in academia and work practices. Simply, if a student develops skills well in a particular field they can become an expert in it. Students start learning some key skills at the beginning of their degree which will help them later in their professional life, career and opportunities. Students will have more confidence, motivation, engagement and achieve goals. Therefore, using a skill-based approach can help students grasp concepts faster and strengthen what they already know (Podareducation, 2021.)

Below are additional essential skills that will help students thrive instead of ‘survive’ at LSST.

Transferable skills

In general, transferrable skills are referred to as skills that can be used in a variety of situations. Transferrable skills include basic skills such as literacy and numeracy skills but also extend to what some authors call “employability skills”. These skills are those which provide students with the skills to enhance their chances of getting employed. This includes skills that are non-job-specific (Blades and Gibb, 2012). A large part of employability depends on language efficiency, digital competence as well as social skills and social awareness (Nägele, Stadler, 2017).

This is why at LSST, students are encouraged to begin their development of these skills from the start of their programme where respective modules allow students to develop their academic skills while focusing on a range of challenges that help develop employability skills. For example, students need to familiarise themselves with IT systems, work in multi-cultural groups and come to know about how to learn efficiently. Particularly, group work allows students to explore their leadership skills, time-management skills and sometimes conflict management is needed. Further, students are supported by the academic team to do all these things in a stimulating and safe environment. They are constantly instructed to attempt tasks that lie just outside their abilities before they are assisted to hone their skills.

Digital skills

This digital and technology-driven world requires students to learn digital skills. Degrees are one of the starting points where learners can start or improve their digital skills intensely. Students must use some digital skills during their studies, such as information/data literacy (browsing, searching, and evaluating data); communication and collaboration (interaction via ICT, emails, chats, blogs); digital content creation (programming and copyrights licensing); and problem-solving (technical problems identifying and solving). See CEDEFOP (2021).

Developing and maintaining digital skills is vital in today’s teaching and learning process. Students can enhance their digital skills through learning – online and activities in class. It is essential to learn digital skills from L3 at LSST digital skills usage will lead learners throughout their studies and personal lives.

As educators, we have to support students to recognise the importance of digital skills in the classroom to assister their learning and their employability - and encourage them to build the confidence to transfer their skills to multiple contexts.  Digital skills enable educators and learners to move forward in their professional careers. The importance of skills is necessary for every aspect of human being life. The skills allow us to do something right and well.

Students that start learning and practising key study skills at the beginning of their degree will have more confidence, motivation, engagement and achieve more goals. Therefore, using a skill-based approach can help students grasp concepts faster and strengthen what they already know (Podareducation, 2021.) Learning and improving current skills makes students better communicators too.

Computer skills

Unlike digital skills, computer user skills are those basic skills that are needed to use computers generally.  Computer skills are needed at LSST to assess course material, search for information and access online libraries. Basic computer skills are also needed to write assignments and can be beneficial to stay in touch with lecturers and other students, for example for sharing ideas and formulating opinions. Efficient use of email is essential in today’s world. Some students, may not have all of the required skills yet. Further, research shows that non-traditional students often tend to put in more effort to compensate for this initial lack of skills (Henson, 2013).

All modern businesses are reliant on the efficient computer skills of their employees. Computers are not only used by businesses around the world to complete tasks but are also essential in a fast-moving world as they can be used to plan and organise a variety of tasks more efficiently in a world in which job tasks become more and more versatile. At LSST students have access to IT equipment and can make use of academic support services which may help with the development of IT skills.

Literacy skills

Literacy is the ability to read, write, speak, and listen in a way that lets us communicate effectively and make sense of the world. According to Unesco (2020), 14% of adults still lack basic literacy skills globally.

In England, 1 in 7 adults, roughly 5.1 million, lack basic literacy skills. England is the only developed country where the literacy and numeracy levels of 16-24 years old are worse than those at 55-65 years old.  43% of adults 16-years and older read at or below the basic level . Their skills are limited to understanding short, simple texts and one-step math problems. (Seedsofliteracy.org, 2015).

Many adults want to improve their literacy skills to get higher-paying jobs. Acquiring stronger literacy skills can open up new careers and often lead to work promotions. Sometimes motivation comes from children who are learning to read themselves.

Improving literacy skills is vital. At LSST, we have several modules such as Preparing for Success, Knowledge and Creativity; Self-development and Responsibility, and Inquiry Based Learning, where students learn the literacy skills to enhance their academic performance further and progress to the next level. Students learn, read, write, present, communicate, and reflect skills during their studies. Regardless of the skills students are needed, lacking  literacy skills  holds a person back at every stage of their life.

Self-development skills

To best support students, it is imperative to understand their motivation to study in Higher Education. More students than ever are beginning to study after a prolonged period of employment (Rozvadska, Novotny, 2019). As opposed to traditional students, non-traditional students more often state financial concerns as motivating factors for studying. They also often are more concerned about academic issues than their traditional counterparts. Further, social issues, such as lack of confidence appear to be more prevalent with non-traditional students (Taylor, House, 2010). In practice, it is important to support students at LSST in a variety of ways. They should be confident that they receive necessary financial support before commencing their studies but it is also important to teach skills that increase self-confidence, such as time-management skills and organisational skills. It has been shown that positive teaching is effective in student empowerment (e.g. Joseph, Murphy, Holford, 2020). As a result, LSST adopts a facility of teachers as facilitators rather than directional teachers, where possible. Students are supported in class but also have access to resources that are designed to support students with social issues as well as financial issues. For example, students are assigned a personal academic tutor, can receive guidance on mental health and can be supported by a dedicated academic support team.

In conclusion, study skills are a fundamental part of academic, professional and personal development. Furthermore, learners can develop these skills at LSST in conjunction with their experience. Additionally, enthusiasm to study and learn skills enhances student confidence and self-assurance. We must all work together to further improve student study skills and learning strategies by making our teaching and learning even more effective and successful.

How to reference this article

Zilionis, G. and Kaiser, A. G.  (2022). The importance of study skills in HE for learners to enhance and develop their studies further in academia . Available at:  https://www.lsst.ac/blogs/ [Note: Please add accessed date here].

Blades, R., Fauth, B., Gibb, J. (2012). ‘ Measuring employability skills. A rapid review to inform development of tools for project evaluation’ . National Children’s Bureau. London.

CEDEFOP. (2021).  Digital skills: Challenges and opportunities . [online] Available at: https://www.cedefop.europa.eu/en/data-insights/digital-skills-challenges-and-opportunities . [Accessed 7 Feb. 2022].

Henson, A.R. (2013). ‘The impact of Computer Efficacy on the Success of the Nontraditional Community College Student’. Dissertations , 301.

Hermida, J. (2009). ‘ The Importance of Teaching Academic Reading Skills in First-Year University Courses . Available at: https://ssrn.com/abstract=1419247 [Accessed 7 Feb. 2022].

Menz, M. (2020). ‘Integrating Academic Skills and Employability’. Journal of Research in Higher Education . 4(2), 5-17 doi: 10.24193/JRHE.2020.2.1

Joseph, S., Murphy, D., Holford, J. (2020). ‘Positive education: A new look at Freedom to Learn. Oxford Review of Education , 46(5). 549-562

Nägele, C., Stadler, B.E. (2017). ‘Competence and the Need for Transferable Skills’ in Competence- based Vocational and Professional Education, Springer International Publishing, Switzerland

Rozvadská, K., Novotný, P. (2019). The Structure of non-traditional students’ motives for entering higher education. Open Journal per la formazione in rete . 19(2). 133-148

Seedsofliteracy.org, (2015). The Importance of Adult Literacy | Seeds of Literacy . [online] Available at: https://www.seedsofliteracy.org/the-importance-of-adult-literacy/ [Accessed 7 Feb. 2022].

Podareducation.org. (2021).  Importance of Skill Development Curriculum in School | Podar Blogs . [online] Available at: https://www.podareducation.org/blog-importance-of-skill-development-curriculum-in-school [Accessed 1 Feb. 2022].

Taylor, J., House, B. (2010). ‘An Exploration of Identity, Motivations and Concerns of Non-Traditional Students at Different Stages of Higher Education’ Psychology Teaching Review . 16(1). 46-57

Unesco.org. (2020). 14 per cent of adults worldwide still lack basic literacy skills, UNESCO report finds | UIL . [online] Available at: https://uil.unesco.org/literacy/14-cent-adults-worldwide-still-lack-basic-literacy-skills-unesco-report-finds . [Accessed 7 Feb. 2022].

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First-year university students’ academic success: the importance of academic adjustment

• Open access
• Published: 04 November 2017
• Volume 33 , pages 749–767, ( 2018 )

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• Els C. M. van Rooij 1 ,
• Ellen P. W. A. Jansen 1 &
• Wim J. C. M. van de Grift 1  

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A Correction to this article was published on 08 January 2018

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Considering the pivotal role of academic adjustment for student success, it is important to gain insight into how several motivational and behavioural factors affect academic adjustment and the extent to which academic adjustment influences student success. This empirical study investigated how intrinsic motivation, academic self-efficacy, self-regulated study behaviour and satisfaction with the chosen degree programme influenced academic adjustment in university and how these variables and adjustment affected three important indicators of student success: grade point average (GPA), attained number of credits (ECTS) and intention to persist. The sample consisted of 243 first-year university students in the Netherlands. Structural equation modelling showed that academic adjustment was influenced by intrinsic motivation, self-regulated study behaviour and degree programme satisfaction, which together explained 72% of the variance in adjustment. Motivational and behavioural variables did not influence GPA and credits directly but through academic adjustment. Furthermore, only satisfaction with the degree programme predicted intention to persist. These results point to the importance of academic adjustment in predicting university GPA and credits and the pivotal role of satisfaction with the degree programme in predicting intention to persist. Universities could integrate the development of self-regulated study skills—the biggest contributor to academic adjustment—in the first-year programme. Moreover, looking at the importance of students’ satisfaction with the programme, communication and collaboration between secondary schools and universities should be enhanced in order to help students to choose a university degree programme that matches their abilities, interests and values.

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Introduction

Drop-out rates in the first year of university are high worldwide. In the Netherlands, where this study was conducted, 33% of first-year university students do not continue to the second year of the programme they initially started (Inspectie van het Onderwijs 2016 ). A smooth transition from secondary school to university increases the chances of student success, in terms of achievement and persistence (Lowe and Cook 2003 ; Rienties et al. 2012 ). Therefore, it is important for university educators to understand how to improve this transition for students. An effective measure of how well a student has transitioned to university is the level of academic adjustment to this new environment. In this study, we draw on traditional theories of student success [e.g. Tinto ( 1993 ) and Astin ( 1999 )] and earlier research on academic adjustment (Baker and Siryk 1989 ) and conceptualise academic adjustment as the ability to have successful interactions with the new academic environment and to cope with its academic demands. In other words, it revolves around the fit between the student and the university environment (Ramsay et al. 2007 ). To make the concept of academic adjustment more explicit, we follow Baker and Siryk’s ( 1984 ) categorisation of four aspects of academic adjustment, which are motivation to learn and having clear academic goals, applying oneself to academic work, exerting effort to meet academic demands and being satisfied with the academic environment. Previous research consistently showed that academic adjustment influences academic achievement (Bailey and Phillips 2016 ; Rienties et al. 2012 ).

This study has two goals. First, we aim to determine which motivational and behavioural variables measured in the first year of university affect students’ academic adjustment and success, i.e. grade point average (GPA), number of attained study credits [European Credit Transfer and Accumulation System (ECTS)] and intention to persist after 3 months of study. An important question here is which variables influence student success, either directly or indirectly through adjustment. Second, we investigate the magnitude of the influence of academic adjustment on the three outcome variables. Most research only uses one outcome measure, even though the specific outcome measure chosen may affect the results. Robbins et al. ( 2004 ) showed, for example, that the impact of predictive factors differs for achievement and persistence. Moreover, these outcome measures in themselves differ. A student’s GPA reflects how well a student performs, whereas the number of credits merely shows whether a student is passing courses. Persistence is yet another distinct measure of success, in that students with a high GPA and many credits may drop out, whereas students with low GPAs or few credits may choose to persist. The differences in measures of success makes it important to include all of them and investigate whether academic adjustment affects them differently.

The motivational and behavioural input variables on which we focus appear in prior literature as important correlates of student success and academic adjustment in university and will be discussed below.

Theoretical framework

Academic adjustment influencing student success.

Research on student success in higher education has a rich history. The traditional theories of Tinto ( 1993 ) and Astin ( 1999 ) focus on the interaction between the student and the institution, where Tinto’s theory of student attrition includes academic, social and institutional integration and goal commitment and Astin’s student development theory revolves around student involvement, which he defines as the energy that a student devotes to the academic experience (Astin 1999 ). The common ground lies therein that a student enters higher education with certain personal characteristics, e.g. personality, motivation, study skills, which change and may even be challenged in interaction with the new educational environment. Successful interaction with this new environment, such as having positive interactions with lecturers and fellow students and being able to handle the increased complexity and quantity of the learning content, then determines whether or not a student is satisfied with the first-year experience and whether he or she obtains good grades, passes his or her courses and persists to the second year (Astin 1999 ; Pascarella and Terenzini 2005 ; Sevinç and Gizir 2014 ). Successful interaction between a first-year student and the academic characteristics and demands of the university environment can be summarised by the construct of academic adjustment. Prior literature consistently showed the pivotal role of academic adjustment in predicting achievement (Aspelmeier et al. 2012 ; Rienties et al. 2012 ; Wintre et al. 2011 ) and persistence (Kennedy et al. 2000 ; Kuh et al. 2006 ) in higher education. Some studies even reported that the effects of background variables on achievement were indirect, with adjustment as a mediator (Kamphorst et al. 2012 ; Petersen et al. 2009 ). Moreover, academic adjustment explained variance in achievement beyond secondary school GPA (McKenzie and Schweitzer 2001 ). Lowe and Cook ( 2003 ) found that 20 to 30% of university students experienced considerable difficulty adjusting to higher education, leading a significant number to drop out or underperform. These factors make academic adjustment an important concept when investigating student success.

Correlates of student success and academic adjustment

Because of the aforementioned importance of academic adjustment as a correlate of first-year success, it is useful to know which variables influence adjustment. Robbins et al. ( 2004 ) emphasised the importance of combining motivational factors and study skills when explaining academic achievement, and Kennedy et al. ( 2000 ) warned against using too narrow a range of variables. We followed this line of thought to explain adjustment and included different motivational and behavioural factors in our model to obtain a more integrative view of adjustment and achievement.

Motivational correlates of success and adjustment

Intrinsic motivation.

Meta-analyses on academic achievement showed a consistent relationship between motivation and achievement (Richardson et al. 2012 ; Robbins et al. 2004 ). Other studies investigated the link between motivational factors and adjustment. For example, Lynch ( 2006 ) and Petersen et al. ( 2009 ) reported a positive link between intrinsic motivation and adjustment. Baker and Siryk ( 1984 ) showed that achievement motivation was correlated with academic adjustment. Moreover, Baker ( 2004 ) showed that lack of motivation is related to poorer adjustment to university. Following these findings and the expectation that students who are intrinsically motivated to study a certain topic will find it easier to adjust to an educational environment where they get the opportunity to study this topic, we expected intrinsic motivation to have a direct and an indirect effect on achievement through adjustment.

Academic self-efficacy

According to Robbins et al.’s ( 2004 ) meta-analysis, academic self-efficacy is the strongest non-cognitive correlate of GPA. Self-efficacy is a person’s perception of the ability to perform adequately in a given situation (Bandura 1997 ). Academic self-efficacy in the university context thus refers to a student’s confidence that he or she can perform adequately in the university environment. Besides being an important correlate of achievement, academic self-efficacy relates to effort and perseverance in learning, self-regulation, less stress in demanding situations and better adjustment to new learning situations (Chemers et al. 2001 ). McKenzie and Schweitzer ( 2001 ) found that the prediction of GPA improved by 12% when academic integration and self-efficacy were added to a model with university entry score as a predictor. De Clercq et al. ( 2013 ), who used an inclusive approach that took into account several predictors, also reported that self-efficacy was one of the most powerful predictors of GPA at the end of the first year in university. When investigating persistence as an outcome measure, Kennedy et al. ( 2000 ) found no differences in self-efficacy between students who continued their studies after 1 year and those who did not. Still, there is some evidence that self-efficacy could affect persistence, because Willcoxson et al. ( 2011 ) found that the opposite of academic self-efficacy, lack of academic confidence, caused students to give up their studies. Examining the relationship between academic self-efficacy and adjustment, several studies showed that self-efficacy, or the comparable concept of academic self-confidence, positively affected adjustment (Chemers et al. 2001 ; Martin et al. 1999 ). This finding can be explained by Bandura’s ( 1997 ) self-efficacy theory, which states that people high in efficacy show more persistence in the face of challenges. The transition from secondary education to university is such a challenge. Moreover, Aspelmeier et al. ( 2012 ), who found that self-esteem and internal locus of control had a positive effect on first-year students’ academic adjustment, suggested that academic self-efficacy is an important factor to consider in future research on adjustment. We thus hypothesised that academic self-efficacy influences achievement both directly and via adjustment.

• Degree programme satisfaction

Although models explaining university success included degree programme satisfaction less often than motivation and self-efficacy, it may be crucial for predicting persistence (Suhre et al. 2007 ; Yorke and Longden 2007 ), especially in the Netherlands and many other European countries such as Germany and Belgium, where students entering university immediately start in a specific major. Not being satisfied with the programme is one of the most important determinants of dropping out (De Buck 2009 ; Wartenbergh and Van den Broek 2008 ). Moreover, satisfaction relates to achievement; Suhre et al. ( 2007 ) showed that students who were more satisfied obtained more credits. We know of no research that investigates the relationship between degree programme satisfaction and academic adjustment, but we expect that students who are satisfied can better cope with academic demands. In the first few weeks of the programme, where students immediately start with several courses specific to the degree programme they chose, students already get a good view of what the programme entails and they can judge the extent to which the programme meets their expectations and the extent to which they are satisfied with the programme. Adjustment to the whole first-year experience, which includes among other things adjusting to a new way of learning, to more independency, and to a faster learning pace, however, is a process that takes longer. The rationale here is that when students are satisfied with the programme they chose, the process of adjusting academically may be easier. On the contrary, students who are having doubts regarding whether this specific degree programme matches their interests may be preoccupied with the dilemma of whether or not to proceed with this programme, which may also have a negative effect on their process of adjusting to university. Their doubts about the programme may even transfer into doubts about belonging in university altogether. Thus, we expected degree programme satisfaction to be related to academic adjustment, achievement and persistence.

Behavioural correlate of success and adjustment

Self-regulated study behaviour.

Motivation is an important but insufficient condition to perform well in university. As Robbins et al. ( 2004 ) concluded, it is important to include study skills, along with psychosocial variables, in models predicting achievement. Self-regulation is a specifically important skill in the university environment, where students must regulate their own study behaviour. Moreover, students who live independently may have many personal and social demands that compete with academic demands. At this point, behaviour regulation becomes crucial. According to Pintrich ( 2004 ), behaviour regulation is part of self-regulation, referring to individual attempts to control one’s own behaviour. Important behaviour regulation activities in the academic environment—or self-regulated study behaviour—are effort regulation, time management and environment management. Effort regulation refers to the ability to control the allocation and intensity of effort, with the goal of doing well in a course; time management involves activities such as making schedules for studying and allocating time for different activities; and environment management pertains to finding the optimal physical conditions for a learning environment, such as avoiding distractors (e.g. social media [Jacobsen and Forste 2011 ]) or people (Pintrich 2004 ). Effort, time and environment regulation are among the study skills often connected to achievement (Burlison et al. 2009 ; Lynch 2006 ). A meta-analysis of the Motivated Strategies for Learning Questionnaire (MSLQ) even showed that of all learning strategies included in the MSLQ, effort regulation and time and study environment management had the highest observed validities for predicting GPA (Credé and Phillips 2011 ). In addition, Wintre et al. ( 2011 ) reported that first-year students who maintained their secondary school GPA in the first year of higher education had better time management skills than those whose GPA would drop and Hurtado et al. ( 2007 ) found that students’ time management skills was a significant predictor of academic adjustment. In contrast with university lecturers’ expectations, first-year students often do not possess the self-regulatory skills that the university environment demands, because they are accustomed to the structured and supervised situation in secondary education (Cook and Leckey 1999 ). This lack of regulatory skill could cause adjustment problems in university; Abott-Chapman et al. ( 1992 ) showed that students with insufficient study skills were at risk of academic adjustment problems. We therefore expected self-regulated study behaviour to influence adjustment and achievement.

Previous achievement as a predictor of success and adjustment

Much research indicated that past achievement is a predictor of university achievement (Bowles et al. 2014 ; McKenzie and Schweitzer 2001 ; Richardson et al. 2012 ; Robbins et al. 2004 ; Suhre et al. 2007 ). However, it is equivocal whether past achievement (i.e. secondary school GPA) also influences academic adjustment at university. It seems reasonable to expect that students with higher scores in secondary education will be better equipped to cope with academic demands and thus adjust to university more easily (Baker and Siryk 1989 ; Kaczmarek et al. 1990 ). However, Wouters et al. ( 2011 ) found no relationship between achievement in secondary education and academic adjustment in higher education, so we questioned whether to expect a pathway from secondary school GPA to adjustment in university.

The conceptual model

Figure 1 presents a schematic representation of the conceptual model of motivational and behavioural factors influencing academic adjustment and the three measures of student success. We expected intrinsic motivation, academic self-efficacy, self-regulated study behaviour and satisfaction with degree programme choice to relate to academic adjustment, as well as to the measures of student success, GPA, credits and intention to persist.

Conceptual model of motivational and behavioural factors impacting academic adjustment and student success outcomes

Educational context

There are two characteristics of the Dutch secondary and higher education system that are relevant in this study. First, in the Netherlands, as in many other European countries, the secondary school system is differentiated: from grade 7 onwards, students attend a level of secondary education that matches their capabilities. Pre-university education is the highest of the three existing levels and graduating from pre-university grants access to a degree programme at a research university. For some programmes, additional requirements are at play, such as specific subject uptake in pre-university education, but in general, the application process is not as intense as in for example the USA. Second, also quite common in Europe, students entering university choose the degree programme they major in before they start.

The total sample was a convenience sample that consisted of 243 first-year university students from different research-intensive universities in the Netherlands, who completed the questionnaire approximately 3 months after the start of their programme. Many different degree programmes were represented in the sample, but a large majority of the students were pursuing a social sciences degree (77%), e.g. Spatial Sciences, Sociology and Law, and a smaller number of students were in the humanities (4%) and natural sciences (19%). Women were overrepresented in this study (60%, as opposed to 53% in the population of first-year university students in the Netherlands; Sociaal en Cultureel Planbureau [SCP] 2014 ). Most students started university after graduating from pre-university education (82%); 14% came from higher vocational education, and the other 4% had switched from another programme at university. Students’ average age was 19.13 years (SD 1.57), ranging from 17 to 28 years, hence the sample can be seen as a sample of traditional students. This makes the sample representative, as in the Netherlands 80% of all pre-university students directly continue to university education (Centraal Bureau voor de Statistiek [CBS] 2016 ). Furthermore, 24% of students can be classified as first-generation university students, students of whom neither of their parents had attended higher education. Among all first-year university students in the Netherlands, the percentage of first-generation students is 33% (Van den Broek et al. 2014 ).

Student success outcomes

Students indicated the average grade they obtained for the courses they had taken in the first quarter of the study year. In the Dutch education system, grades range from 1 to 10, and a 5.5 or higher is required to pass. The students’ grades in this sample ranged from 4 to 9, with an average grade of 6.90 (SD = 0.98).

In addition to their GPA, students reported the number of credits they had obtained in the first quarter of the year.

Intention to persist

We measured students’ intention to persist with one question: ‘Do you intend to finish this degree programme (i.e. the 3-year university bachelor’s program)?’

• Academic adjustment

We measured students’ academic adjustment with the academic adjustment subscale of the Student Adaptation to College Questionnaire (SACQ) by Baker and Siryk ( 1984 ). This subscale consists of 24 questions that involve coping with the academic demands of the university experience. In line with Baker and Siryk’s internal consistency measures for the scale, which range from α = .82 to .87, and with more recent studies who used the academic adjustment subscale of the SACQ [e.g. Jones et al. ( 2015 ) and Rodríguez-González et al. ( 2012 )], the alpha of this scale in our study was good: .85.

Motivational factors

We used a measure of intrinsic motivation specifically focused on the university environment, i.e. a desire to gain academic knowledge in one’s field of interest and to conduct research because one finds it inherently interesting or enjoyable (based on Ryan and Deci 2000 ). The 13 items were based on the Scientific Attitude Inventory II (SAI II; Moore and Foy 1997 ).

To measure academic self-efficacy for the university environment, we used 16 of the 33 items of the College Academic Self-Efficacy Scale (CASES; Owen and Froman 1988 ). Previous research has shown that these items were sufficient to obtain a reliable measure of academic self-efficacy (Van Rooij et al. 2017 ). The 16 items were typical behaviours that students need to demonstrate at university, such as being able to understand difficult passages in textbooks and attending class consistently even in a dull course.

We measured the extent to which the university students were satisfied with the degree programme they had chosen by averaging the score on two items: ‘I am satisfied with the programme I chose’ and ‘Looking back, I wish I had chosen a different degree programme’ (reverse coded).

Behavioural factor: self-regulated study behaviour

The self-regulated study behaviour scale consisted of the effort regulation and the time and study environment management subscales of Part B of the Motivated Strategies for Learning Questionnaire (MSLQ) (Pintrich et al. 1993 ). The effort regulation scale had four items, and the time and study environment management subscale consisted of eight items. Credé and Phillips’s ( 2011 ) meta-analyses of the MSLQ showed that the scales of time and study environment management and effort regulation were so strongly correlated that they may assess the same construct. Correspondingly, the internal consistency of the complete self-regulated study behaviour scale was good (α = .87). Table 1 summarises measurement characteristics.

Previous achievement

We determined academic achievement in secondary school with an item that asked for average secondary school diploma grade. Scores ranged from 6 (satisfactory) to 9 (very good), with an average grade of 7.07 (SD = .72).

The Ethics Committee of the university had given approval of the study. All participants received an e-mail invitation to participate in the study. Seventy-one percent of participants received this e-mail, composed by the researchers, via a coordinator of their programme who was interested in having the first-year students of his or her programme participate in the study and the other 29% received the invitation directly from the researchers. This latter group participated in a previous study a year earlier, when they were still in secondary school, and had given consent to be contacted again for a follow-up study. The e-mail invitation explained the research purpose and asked the student to complete an online questionnaire; participation was voluntary. Incentives were allotted among participants who had completed the questionnaire. The response rate was 52%.

Due to 11 students having missing values on multiple variables, we based our structural equation model tests on 232 first-year university students. We used Mplus, Version 7, to perform the analyses. First, we inspected the descriptive statistics and correlational matrix to conclude whether certain variables were significantly and substantially related to each other. Second, using these results, we decided which variables to include in the first model, based on the conceptual model with both direct and indirect links from the motivational and behavioural factors to the student success outcomes. Third, we tested this first model and evaluated its goodness of fit based on agreed-upon criteria (e.g. Kline 2005 ). Fourth, if the model fit was insufficient, we adapted the model, according to the reported modification indices and theoretical considerations, after which we tested the new model.

Descriptive results

Table 2 presents the descriptive statistics of all factors used in the model. The mean scores on all factors, as well as on secondary school and university GPA, were relatively high and the variances, especially those of academic adjustment and academic self-efficacy, were quite low. There were no significant differences in factor and outcome means between first-generation students and continuing generation students. We also did not find any significant differences between students who came from pre-university, from higher vocational education and from another university degree programme.

Table 3 shows the correlations between all factors used in the model. The motivational and behavioural variables had higher correlations with academic adjustment than with the three measures of student success, with the exception of degree programme satisfaction, which correlated equally strongly with intention to persist and academic adjustment.

Path analysis

As can be deduced from Fig. 1 , our conceptual model consisted of many links, between each of the motivational and behavioural variables and academic adjustment and each of the student success outcomes. However, because correlations lower than .25 would likely have resulted in insignificant links in the model, we excluded the hypothesised pathways between intrinsic motivation and GPA, ECT and intention to persist, and those between academic self-efficacy and ECT and intention to persist. We then tested this model in Mplus. Goodness-of-fit statistics showed that this model had good fit ( Χ 2 (11) = 14.91, p  = .07, Χ 2 /df = 1.36, RMSEA = .04 [confidence interval = .00–.08], CFI = .99, TLI = .98, SRMR = .06). However, many of the pathways were insignificant: secondary school GPA and academic self-efficacy were not significantly related to academic adjustment; self-regulated study behaviour and satisfaction with the choice of degree programme were not significantly related to GPA; secondary school GPA, self-regulated study behaviour and satisfaction with the programme were not significantly related to credits; and academic adjustment was not significantly related to intention to persist.

These results implied that many links from the motivational and behavioural variables affected university success outcomes not directly but through adjustment. Therefore, we tested a second model in which we removed all insignificant pathways from the first model. We present this model in Fig. 2 . This model achieved good fit: Χ 2 (19) = 20.55, p  = .36, Χ 2 /df = 1.08, RMSEA = .02 [CI = .00–.06], CFI = .99, TLI = .99, SRMR = .06. All hypothesised links were significant, except the link from academic self-efficacy to university GPA (β = .13 (SE = .06), p  = .06). Moreover, university GPA and intention to persist were not significantly related to each other (β = .12 (SE = .07), p  = .12) and neither were self-regulated study behaviour and intrinsic motivation (β = .14 (SE = .08), p  = .10). The model showed that the motivational and behavioural variables affected two university success outcomes, GPA and credits, through academic adjustment. Self-regulated study behaviour (β = .61), intrinsic motivation (β = .14) and satisfaction with the choice of degree programme (β = .36) had impacts on academic adjustment. Academic self-efficacy was not significantly related to university GPA, but did correlate highly with self-regulated study behaviour (β = .63), thereby indirectly influencing adjustment and subsequent achievement. In total, 72% of the variance in academic adjustment was explained by the aforementioned variables. Academic adjustment influenced both GPA (β = .38) and the number of attained credits (β = .50) in university. Secondary school GPA only had impact on university GPA (β = .28). Respectively, 29 and 25% of the variance in GPA and credits were explained. The intention to persist was largely influenced by students’ satisfaction with the degree programme they had chosen (β = .60).

Fitted model of motivational and behavioural factors impacting academic adjustment and student success outcomes. Note: dotted lines represent insignificant pathways

Conclusions and discussion of the main findings

We investigated which motivational and behavioural variables measured in the beginning of the first year of university affected students’ academic adjustment and success (GPA, credits and intention to persist) and the influence of academic adjustment in predicting these three outcomes. Students who were more intrinsically motivated to gain academic knowledge and to do research, who could effectively regulate their study behaviour and who were more satisfied with their chosen degree programme had better academic adjustment (i.e. had more successful interactions with the academic experience and were better able to cope with the academic demands of the university environment). Furthermore, students with better academic adjustment and who had a higher GPA in secondary education had a higher university GPA. In addition, better academic adjustment led to more credits in the first half of the first semester of university. However, whether these students actually intended to persist was a different question: it depended less on the level of academic adjustment and secondary school GPA than on their satisfaction with their chosen degree programme. Our results thus confirmed the importance of academic adjustment as a measure of how successfully the student transitioned from secondary school to higher education in predicting study results in the first year of university. In addition, academic adjustment was substantially more important in predicting the number of attained credits and university GPA than secondary school GPA. Thus, it is again confirmed that first-year students’ experiences, more specifically how they interact with the learning environment, have more impact on their success than their previous results (Kuh et al. 2006 ). Motivational and behavioural factors did not influence GPA and credits directly but only through academic adjustment. Thus, effectively regulating study behaviour (e.g. maintaining study schedules, turning off social media when studying), being intrinsically motivated to gain academic knowledge and being satisfied with chosen degree programme did not necessarily mean students would achieve high grades and obtain all credits. It did, however, increase their chances of being well-adjusted (i.e. able to cope with the academic demands of the new learning environment). Subsequently, this academic adjustment led to a better GPA and more credits. Studies that tested the effects of these motivational and behavioural factors as having only direct effects on achievement may underemphasise the pivotal role of adjustment.

Another important finding was that self-regulated study behaviour exerted the largest influence on academic adjustment of all measured variables. This means that in order to experience a smooth transition, it is very important that students are capable of regulating their study behaviour and less important that they are intrinsically motivated and satisfied with the degree programme. The high degree of self-regulation that university demands is one of the largest differences with secondary school; therefore, students who are good self-regulators will adjust more easily. Another possible explanation is that behavioural factors are more important in explaining adjustment than motivational ones. In this regard, Astin’s claim about student involvement can be applied to academic adjustment as well: “It is not so much what the individual thinks or feels, but what the individual does, how he or she behaves” (Astin 1999 , p. 519). Furthermore, the differences in magnitude of influence on adjustment could be attributable to smaller differences between students in intrinsic motivation than in self-regulated study behaviour.

A surprising result was that academic self-efficacy, widely accepted as a very important correlate of student success (e.g. Robbins et al. 2004 ), did not affect any of the student success outcomes of our study, nor did it affect academic adjustment. Its only role in the model was as an important correlate of self-regulated study behaviour, consistent with previous research indicating high correlations between self-regulation and self-efficacy (Bouffard-Bouchard et al. 1991 ; Fenollar et al. 2007 ). Again, a possible explanation is that behavioural factors are more important in influencing adjustment than motivational factors such as self-efficacy and that the differences between students in self-efficacy were rather small. Two other explanations are provided by De Clercq et al. ( 2017 ), who found a relationship between self-efficacy and achievement that was less strong than expected in their person-centred study on first-year achievement. As they explained, global self-efficacy, such as the general measure of academic self-efficacy that we used in this study, is not as good a predictor as domain-specific self-efficacy, e.g. self-efficacy in a specific subject or a specific skill, and self-efficacy beliefs are not good predictors of achievement in new learning contexts, such as the first year at university (De Clercq et al. 2017 ). However, we did find that students who were more confident in their academic skills tended to regulate their effort and manage their study time and environment more effectively than students lower in self-efficacy. Because self-regulated study behaviour is very important in university—where instructors provide little control or structure and more autonomy and responsibility is demanded of students (Pintrich 2004 )—self-efficacy is still an important factor in the transition from secondary to university education due to its influence on behaviour regulation.

Contrary to our expectation, only one variable influenced students’ intention to persist, namely, the level of satisfaction with their chosen degree programme. Although this satisfaction also influenced academic adjustment, academic adjustment did not have any influence on intention to persist. Thus, whether a student planned to continue his or her studies after the first year was not related to how well the student could cope with the demands of the academic environment in general, but rather how well he or she fitted within the specific study programme. The outcome variable, intention to persist, thus measured a different entity than the outcome variables GPA and credits, which did not directly relate to a specific degree programme. If we had measured intention to persist as a students’ intention to stay in university altogether or drop out completely, academic adjustment may have played a role.

Implications

The results indicated the crucial role of academic adjustment in predicting achievement in university. Self-regulated study behaviour, satisfaction with degree programme choice and, to a lesser extent, intrinsic motivation influenced students’ academic adjustment. All these factors can be influenced, both before and after the transition. For example, secondary education could emphasise the development of self-regulated study behaviour. Jansen and Suhre ( 2010 ) showed that study skills preparation in secondary school, regarding time management and learning skills, positively influenced university students’ study behaviour. We also found a connection between academic self-efficacy and self-regulated study behaviour (e.g. Bouffard-Bouchard et al. 1991 ). Schunk and Ermter ( 2000 ) stated that when either of these aspects is low or lacking, the other aspect cannot fully develop, because they influence each other reciprocally. Therefore, they recommended addressing self-efficacy and self-regulatory competence together: interventions that teach self-regulation skills should contain components that increase students’ confidence in their academic skills (Schunk and Ermter 2000 ).

University staff should temper their expectations of first-year students’ self-regulation skills. Previous studies showed that many first-year lecturers believe students already possess these skills (Cook and Leckey 1999 ), and therefore, they do not emphasise (further) development of these skills, even though they are crucial to student success. Paying attention to study skill development, however, may produce positive effects. Interventions focused on the development of academic skills led to gains in academic achievement (Evans and Burck 1992 ). Promoting good study behaviour alone may not be sufficient, in that intrinsic motivation also influenced adjustment. Moreover, many researchers emphasised the importance of combining study skills factors and motivational factors to boost students’ achievement (Eccles and Wigfield 2002 ; Pintrich et al. 1993 ; Robbins et al. 2004 ). Of Zepke and Leach’s ( 2010 ) ten proposed actions to enhance higher education students’ engagement, the first two focus on increasing motivation: enhancing students’ self-belief and enabling students to work autonomously, enjoy learning relationships with others and feel they are able to reach their own goals. These actions could be a meaningful starting point to increase motivation.

Whereas self-regulation skills and motivation can be positively influenced when the student already is in university, this is to a lesser extent the case with students’ satisfaction with their chosen programme. There is not much that can be done when the student has simply chosen a programme that is not what he or she expected it to be and thus does not match his or her abilities, interests and values. Switching programmes then is a good solution. Because of this large influence we found of satisfaction with the programme on persistence [which is in line with a study by Jansen and Suhre ( 2010 )], it is worthwhile to help prospective students make a good programme choice. Both secondary schools and universities play important roles in this regard. Secondary schools could provide students with the opportunity to get to know the programmes in which they are interested—for example, by having them write a comparative essay of three study programmes, which would encourage them to go in depth to investigate the study programmes and the extent to which they fit the students’ individual strengths, interests, values and learner characteristics. Universities could provide information for prospective students in such a way that their expectations of a programme will be realistic. Information should be transparent about crucial characteristics of the study, such as the curriculum, the degree of difficulty, the level of guidance and availability of staff, the available facilities of the university and so on. Last, since both universities and secondary schools are important parties in the transition, it would be beneficial if they would communicate and collaborate more.

Limitations and directions for future research

A first limitation of the current study was that we only accounted for academic adjustment, not for other types of adjustment. Although it is the most consistent correlate of achievement compared with other types (Rienties et al. 2012 ), measuring social, personal-emotional and institutional adjustment in addition could be valuable. Second, there were some limitations regarding the sample: it was a convenience sample that consisted of students from several universities and degree programmes without taking these differences into account. Although interesting for future research, investigating differences between fields or programmes was not the intention of this study and the sample was not sufficiently large to do so. Looking at the relatively high GPAs, and the relatively small variance of measures as self-efficacy and academic adjustment that we found, it seems likely that the sample was biased towards the better performing students. We know from research on response bias that it is a familiar problem that higher-achieving students are more inclined to complete surveys than their lower-achieving peers (Sax et al. 2003 ). Therefore, it is important to validate these results with a larger and more diverse sample. In this regard, especially the absence of a link between self-efficacy and academic adjustment would be worthwhile to re-investigate. If the variance between both factors would be increased the model may behave differently. Third, we measured all variables at one point in time, which makes it impossible to detect causal relationships and to map processes. Many of the proposed linkages in the conceptual model could arguably be turned around, e.g. academic adjustment could influence self-efficacy. To determine causal relationships, it would be worthwhile to conduct longitudinal research that starts measuring motivational and behavioural variables in secondary school and investigates how they relate to adjustment and student success outcomes later in university. Relatedly, research should investigate whether secondary school teachers are giving adequate attention to preparing students for university. If so, how, and are their practices in line with what students need to be well prepared? In this study, for example, self-regulated study behaviour is very important for first-year university students. Are secondary schools preparing their students to manage their time, environment, and effort efficiently? Moreover, study choice is crucial; students who are dissatisfied with their chosen programme are at a high risk to quit. Researchers could provide a clear image of what teachers and advisors in secondary school currently are doing to help their students make suitable choices and how they could improve those choice processes.

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08 january 2018.

The article “First-year university students’ academic success: the importance of academic adjustment,” written by Els C. M. van Rooij, Ellen P. W. A. Jansen, and Wim J. C. M. van de Grift, was originally published electronically on the publisher’s internet portal (currently SpringerLink) on 4 November 2017 without open access.

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Els C. M. van Rooij (corresponding author). Department of Teacher Education, University of Groningen, Grote Kruisstraat 2/1, 9712 TS Groningen, The Netherlands. Telephone: +31 50 363 31 99. E-mail address: [email protected].

Current themes of research

University preparation in secondary education; the transition from secondary education to university; first-year university students’ achievement.

Relevant publication

Van Rooij, E., Jansen, E. & Van de Grift, W. (2017). Secondary school students’ engagement profiles and their relationship with academic adjustment and achievement in university. Learning and Individual Differences, 54, 9–19.

Ellen P. W. A. Jansen . Department of Teacher Education, University of Groningen, Grote Kruisstraat 2/1, 9712 TS Groningen, The Netherlands. Telephone: +31 50 363 3644. E-mail address: [email protected].

The transition from secondary education to university; assessment and self-selection for teacher education; learning communities in higher education; international students and the international classroom; excellence in higher education.

Relevant publications

Jansen, E. P. W. A., Andre, S., & Suhre, C. J. M. (2013). Readiness and expectations questionnaire: a cross-cultural measurement instrument for first-year university students . Educational Assessment Evaluation and Accountability , 25 (2), 115–130.

Jansen, E. P. W. A., & Suhre, C. J. M. (2010). The effect of secondary school study skills preparation on first-year university achievement . Educational Studies , 36 (5), 569–580.

Jansen, E. P. W. A., Suhre, C. J. M., & André, S. (2016). Transition to an international degree programme:

Preparedness, first-year experiences and study success of students from different nationalities. In E. Kyndt, V. Donche, K. Trigwell, & S. Lindblom-Ylänne (Eds.), Higher Education Transitions: Theory and Research (New perspectives on learning and instruction). Routledge.

Jansen, E. P. W. A., & Van der Meer, J. (2012). Ready for university? A cross national study on students’ perceived preparedness for university . Australian Educational Researcher , 39 (1), 1–16.

Wim J. C. M. van de Grift . Department of Teacher Education, University of Groningen, Grote Kruisstraat 2/1, 9712 TS Groningen, The Netherlands. Telephone: +31 50 363 8518. E-mail address: [email protected].

Evidence-based education; teacher development; school didactics.

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Van de Grift, W., Helms-Lorenz, M., & Maulana, R. (2014). Teaching skills of student teachers: Calibration of an evaluation instrument and its value in predicting student academic engagement . Studies in Educational Evaluation , 43 , 150–159.

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van Rooij, E.C.M., Jansen, E.P.W.A. & van de Grift, W.J.C.M. First-year university students’ academic success: the importance of academic adjustment. Eur J Psychol Educ 33 , 749–767 (2018). https://doi.org/10.1007/s10212-017-0347-8

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Received : 15 February 2017

Revised : 04 July 2017

Accepted : 04 August 2017

Published : 04 November 2017

Issue Date : October 2018

DOI : https://doi.org/10.1007/s10212-017-0347-8

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SYSTEMATIC REVIEW article

Systematic review of learning generic skills in higher education—enhancing and impeding factors.

• 1 Centre for University Teaching and Learning (HYPE), Faculty of Educational Sciences, University of Helsinki, Helsinki, Finland
• 2 Department of Teacher Education, University of Turku, Turku, Finland

The research field on generic skills in higher education has expanded rapidly. In addition, the importance of generic skills has been highlighted both in educational policy discourses and in practice of higher education. The present study reviews theoretical, methodological, and empirical viewpoints on learning generic skills and synthesizes the empirical evidence about the factors that enhance and impede student learning of generic skills. Altogether 116 articles were included in the analysis. The systematic analysis revealed remarkable variation in concepts, research methods, and operationalization of generic skills. These findings suggest that research in this field is still incoherent. According to the results, contextual factors that enhance or impede higher education students' learning of generic skills were investigated more often than individual factors. Furthermore, the articles included in this review emphasized learning of work-oriented professional skills over higher-order thinking skills. To ensure the development of research on generic skills, it is important to focus on more coherent theorization and operationalization of the various generic skills. More longitudinal studies with methods that genuinely capture actual skills and their development are also needed to advance the field. The results can be used for future discussions on theorization, empirical research, and practical development of student learning of generic skills.

Introduction

Generic skills, such as critical thinking, collaboration, communication, argumentation, and problem-solving skills, usually refer to cognitive skills and higher order thinking skills, as well as twenty-first century competence and future citizens' literacy. Learning generic skills is widely singled out as the key aim of higher education in addition to domain-specific knowledge and skills (e.g., Arum and Roksa, 2011 ; Hyytinen et al., 2019 ; Shavelson et al., 2019 ). The importance of generic skills has been also highlighted in the transition phase to work and later in working life ( Tuononen et al., 2019 ). Similarly, generic skills are considered essential for citizens of the twenty-first century in various policy papers and reports ( Strijbos et al., 2015 ; OECD, 2019 ). As part of a discussion on educational policy, several lists of the key generic skills of higher education have been compiled ( European Parliament Council, 2008 ; OECD, 2019 ). For example, the European Parliament Council (2008) has determined the key generic skills that should be included in higher education degrees. Consequently, generic skills are found as learning objectives in almost all higher education curricula today. Naturally, the aim is to organize teaching so as to enhance student learning in the best possible way. Therefore, it is not surprising that higher education students' generic skills have also attracted remarkable interest from researchers, and become an expanding field of research.

Unfortunately, this broad interest in generic skills and proliferation of studies involves some disadvantages. The interests, intentions, and perspectives of various stakeholders have influenced the research on generic skills and especially the development of research instruments ( Strijbos et al., 2015 ; Muukkonen et al., 2019 ; Toom et al., 2021 ). Thus, the research field is at risk of fragmentation. Recent evidence suggests that there is conceptual incoherence in the research field of generic skills as well as a lack of clear theoretical frameworks and robust instruments (e.g., Barrie, 2006 ; Braun et al., 2012 ; El Soufi and See, 2019 ). Another disadvantage is related to research designs and methods. It seems that previous research has relied mainly on indirect methods and materials, such as self-reports of learning, in the investigations of generic skills, and only a limited number of studies have applied performance-based methods and focused on learning generic skills in authentic situations ( Braun et al., 2012 ; Zlatkin-Troitschanskaia et al., 2015 ). In addition to the scattered research on student learning of generic skills, systematic research on the characteristics of the learning environment or other factors contributing to student learning of generic skills is scarce. This may be related to the laborious research designs that the studies would require, or the lack of robust and valid research instruments to measure generic skills and characteristics of the learning environment. In order to obtain a more coherent picture of the status of generic skills research, there is a need for the systematic analysis of the methods and concepts utilized in the studies.

Through a systematic review, this study aims to contribute to existing theoretical, methodological, and empirical viewpoints on learning of generic skills. This study reviews and synthesizes the empirical evidence about higher education students' generic skills and the factors that enhance and impede their learning of generic skills. Moreover, this study explores methods that are used in the empirical studies and elaborates on concepts related to learning generic skills. The research questions are as follows:

1) From the perspective of student learning in higher education, which generic skills are explored in empirical research, and how are they explored?

2) How do higher education students learn generic skills during their studies?

3) Which factors have been identified to enhance or impede student learning of generic skills?

Materials and Methods

A combined literature search in the electronic databases of EBSCOHost, Scopus, and Eric was carried out to identify peer-reviewed journal articles in English. The three main keywords utilized in the search were “student learning,” “generic skills,” and “higher education,” but the searching of databases included the combination of words and phrases such as learning or “student learning” and “generic skills” and “higher education” or “university.” The search included all disciplines. We searched online and empirical research articles from 2014 to 2019, resulting in over 907 articles. After that, the first and second authors went through the titles and abstracts, and selected those studies that specifically addressed higher education student learning of generic skills. Therefore, the articles focusing solely on teachers' or employers' perspectives on learning generic skills were excluded. In addition, educational policy articles related to generic skills, quality assurance, curriculum analysis, theoretical, and review articles were excluded. Finally, 393 articles were selected for the first phase of review. During this phase, the first and second author read the articles and ensured that the articles met the inclusion criteria. The following inclusion criteria were used: (1) the study was retrieved from a peer-reviewed journal, (2) it was written in English, (3) the study was conducted in the context of higher education, and (4) the study reported empirical evidence on students' learning of generic skills. In addition, duplicates were removed in this phase. After that, a total of 273 articles were included in the analysis. In the second phase of review, the first and sixth author went through the articles and re-checked that they met the criteria. Especially the fourth criterion was at the focus in this phase of article selection. After these thorough reading rounds, 116 articles were finally included in the analysis. In the Figure 1 , flow selection process is presented.

Figure 1 . Flow diagram of selection process.

Qualitative content analysis was adopted for the analysis of the articles ( Elo and Kyngäs, 2007 ). First, all articles were read through to gain familiarity with the data and to identify the concepts that were utilized in the studies focusing on the higher education students' learning of generic skills. Each article was analyzed separately and systematically. We found extensive conceptual variation. The articles were categorized based on the concepts utilized in the articles. We identified two types of articles based on the focus of the articles (see Table 1 ). The first type of article focused on sets of generic skills while the others concentrated on specific generic skills. In total, analysis revealed six different specific generic skills. Below, we consider these two types of articles in greater detail.

Table 1 . Phases of analysis.

In the second phase of analysis, the first author further analyzed which generic skills were measured in the first type of article, namely those that focused on sets of generic skills. The measured skills were categorized into 17 main categories based on the analysis. These categories (see Table 2 ) were subsequently reviewed and refined through discussion between all authors. In the third phase, the articles of both types were further analyzed in terms of the research methods used in the studies. In addition, during this phase, learning of generic skills as well as enhancing and impeding factors in learning generic skills were identified from the results sections of the articles. Descriptions of the qualities analyzed were written for each article and collected in Excel worksheets. The fourth and final phase consisted of final interpretations discussed by all the authors. All authors participated in all the phases of analysis, except the second phase which was conducted by the first author.

Table 2 . Sets of generic skills: the main categories and subcategories of measured generic skills.

Measured Skills and Methods in the Reviewed Articles

Our first aim was to explore, from the perspective of student learning in higher education, which generic skills are explored in empirical research, and how they are explored. The final sample included studies that had various objectives, and that were conducted using a wide variety of research methods. There was great variation in the number of the participants in the studies reviewed, from six students to 74,687 students. As mentioned above, there was remarkable variation in the generic skills investigated in the articles (see Table 1 ). There were two types of articles, namely, those focusing on a set of generic skills and those focusing on a specific generic skill at a time. Most of the articles (60%, n = 70) focused broadly on sets of generic skills. These studies described their focus as generic skills, or a similar concept, such as employability skills, transferable skills, soft skills, graduate attributes, generic competencies, learning outcomes, academic competencies, core competencies, and non-technical skills. In addition, the rest of the studies framed their research with generic skills but focused on more specific generic skills ( n = 46), namely critical thinking skills, communication skills, collaboration skills, creativity and problem-solving skills, self-regulation skills, or ethical skills. Due to the difference in the approach the studies adopted, in the following section we report separately the studies that focused on sets of skills and the studies that focused on a specific generic skill . Hence, section Sets of Generic Skills reveals the variation identified in studies focusing on a set of generic skills and, respectively, section Specific Generic Skills concentrates on articles that focus on specific generic skills by describing the identified skills and the methods used to investigate these skills.

Sets of Generic Skills

In the articles that focused broadly on sets of generic skills, the definitions of generic skills and the methods that were used to measure those skills were varied. Based on the information available about the surveys used, we analyzed which skills were measured as a part of the sets of generic skills (see Table 2 ). The number of skills measured varied from three to 89. These skills were categorized into 17 main categories. The skills most often measured were professional skills (f = 93), including professionalism, leadership, project skills, and entrepreneurial skills. Next, analytical skills (f = 66), applying knowledge (f = 59), communication skills (f = 59), and collaboration skills (f = 51). After these, time-management (f = 29), study skills (f = 29), self-knowledge (f = 25), and ICT skills (f = 23) were included in the instruments. Ethics ( n = 18), globalization (f = 17), research skills (f = 15), adaptability (f = 10), foreign language skills (f = 10), and personal attributes (f = 10) were also measured in numerous studies. Additionally, career skills (f = 5) and giving and receiving feedback (f = 2) were measured in a few studies. However, it is important to note that not all articles reported the survey instrument used at all, or the instrument was not reported accurately. In Table 2 , categories and subcategories of the measured generic skills are presented in greater detail.

Most of the these studies that measured sets of generic skills utilized surveys (e.g., Jackson, 2014a , 2015 ; Pita et al., 2015 ; Prokofieva et al., 2015 ; Abayadeera and Watty, 2016 ; Joseph et al., 2016 ; Monteiro et al., 2016 ; He et al., 2017 ; Burch et al., 2018 ; Akhmetshin et al., 2019 ; López et al., 2019 ). Control and experimental groups were also used in study designs ( Guo, 2019 ; Tomasson Goodwill et al., 2019 ). In addition, five articles used qualitative methods ( Viviers, 2016 ; Kridiotis and Swart, 2017 ; Sonnenschein et al., 2017 ; Nastiti et al., 2018 ; Lee et al., 2019 ), and mixed methods ( Bellew and Gabaudan, 2017 ; Dinning, 2017 ; Sarkar et al., 2017 ; Ssegawa and Kasule, 2017 ; Tran, 2017 ; Tomasson Goodwill et al., 2019 ), and one was a mixed-method study using performance-based assessment and interviews ( Feldon et al., 2016 ). In these articles various generic skills were measured using scales including several items or one-item measures ( Yin et al., 2014 , 2016 ; Abayadeera and Watty, 2016 ; Jackson, 2016a ; Liu et al., 2017 ; Yin and Ke, 2017 ; Guo, 2018 ; Tuononen et al., 2019 ).

Specific Generic Skills

The articles that focused on specific generic skills explored critical thinking (10), communication skills (10), collaboration skills (9), creativity and problem-solving skills (8), and self-regulation skills (6). Furthermore, there were a few articles that studied ethical skills (3). These studies utilized various research methods that are presented in greater detail in the following.

Critical Thinking

Studies measuring critical thinking used a variety of methods. In some studies, performance-based assessments were used. These included multiple-choice tests and a few open-ended tasks. Some of the performance assessments used standardized tests ( Al-Thani et al., 2016 ; Ding et al., 2016 ; Nedelova and Šukolova, 2017 ; Stone et al., 2017 ), and in some studies, researchers had created their own performance tasks or used regular examination tasks or course assignments ( Sotiriadou and Hill, 2015 ; Calma, 2017 ; Utriainen et al., 2017 ; Lespiau and Tricot, 2018 ). Many of the studies investigated used self-report surveys to investigate experiences and opinions ( Kim, 2015 ; Sotiriadou and Hill, 2015 ; Danczak et al., 2017 ; Ibrahim and Jaaffar, 2017a ). One study used an interview as a method ( Kim, 2015 ). In two studies, mixed methods were used, combining two of the above-mentioned methods ( Kim, 2015 ; Sotiriadou and Hill, 2015 ). In investigating the development of critical thinking, various designs were used. A cross-sectional design was used to compare junior and senior students ( Al-Thani et al., 2016 ), and students in different groups or study fields ( Ding et al., 2016 ; Lespiau and Tricot, 2018 ). In a few studies, a longitudinal design was used, comparing pre-course and post-course measurements ( Kim, 2015 ; Sotiriadou and Hill, 2015 ; Stone et al., 2017 ).

Communication Skills

Many of the studies that focused on students' communication skills also used self-report surveys ( Jackson, 2014b , 2016b ; Tun Lee-Foo et al., 2015 ; Mercer-Mapstone and Matthews, 2017 ; Ibrahim and Jaaffar, 2017a ). Typically the studies on students' communications skills utilized multi-method designs, for example combining a survey with written reports ( Drury and Muirb, 2014 ), and writing assignments ( Rayner et al., 2016 ), or multiple-choice tests with long answer questions ( Hryciw and Dantas, 2016 ) and performance assessments ( Van Ginkel et al., 2015 ). In addition, some studies utilized even more complex designs, for example, including dialogue circles, videoing, and team performance measures ( Pöysä-Tarhonen et al., 2016 ), or student surveys, teacher interviews, and student performance in communication tasks ( Mercer-Mapstone and Kuchel, 2016 ).

Creativity and Problem-Solving

Most of the studies that explored creativity and problem-solving used self-report surveys ( Wood and Bilsborow, 2014 ; Techanamurthy et al., 2018 ; Keinänen and Kairisto-Mertanen, 2019 ; Mareque et al., 2019 ). However, there were exceptions as well, especially regarding problem-solving skills. For example, an online game-based assessment tool ( Seow et al., 2019 ), problem-solving tests ( Klegeris et al., 2017 ) and evaluation rubrics were used. Furthermore, many studies explored the influence of some specific factor on the development of the skills, such as innovation pedagogy ( Keinänen and Kairisto-Mertanen, 2019 ), experiential learning pedagogy ( Seow et al., 2019 ), participating in leisure activities ( Mareque et al., 2019 ), or engaging students in complex learning activities (in this case, design-based research) ( Wood and Bilsborow, 2014 ). Mostly the studies focused on exploring students' own perceptions of the level of their skills during studies or upon graduation ( Tahir et al., 2017 ; Techanamurthy et al., 2018 ) or after a specific pedagogical intervention ( Keinänen and Kairisto-Mertanen, 2019 ; Mareque et al., 2019 ). Seow et al. (2019) used a quasi-experimental design with a control-group and pre-post test design to explore differences in performance after a specific intervention between the groups. Klegeris et al. (2017) used a cross-sectional design to compare the problem-solving abilities of first- and upper-year students.

Collaboration Skills

Studies measuring collaboration skills utilized surveys ( Bravo et al., 2016 ; Ibrahim and Jaaffar, 2017b ; Sridharan et al., 2018 ; Christensen et al., 2019 ). Some studies used pre- and post- design to explore students' collaboration skills ( Christensen et al., 2019 ). In addition, evaluation rubrics were used to assess teamwork competencies, including identity, communication, implementation, and regulation ( Cela-Ranilla et al., 2014b ). Collaboration skills were also explored qualitatively through students' reflection about teamwork.

Self-Regulation Skills

Self-regulation skills were often explored using self-assessments, such as surveys and learning diaries ( Ibrahim and Jaaffar, 2017b ; Tseng et al., 2019 ). In addition, evaluation rubrics were used to evaluate self-management skills including planning, organization, development, and assessment ( Cela-Ranilla et al., 2014b ).

Ethical Skills

Studies investigating ethical skills utilized surveys and students' written reflections as research methods ( Howells et al., 2016 ; Steur et al., 2016 ; Taplin et al., 2018 ).

Higher Education Students' Learning of Generic Skills During Their Studies

Our second aim was to explore whether students learn generic skills in higher education. First, we present the results of the studies that focused on sets of generic skills and then the studies that focused on specific generic skills.

Most of the articles that investigated sets of generic skills explored students' perceptions of learning of generic skills. The results showed that the students had learnt the generic skills under investigation well ( Bonesso et al., 2015 ; Joseph et al., 2016 ; Pirog, 2016 ; Yin et al., 2016 ; Guo et al., 2017 ; Larraz et al., 2017 ; Sarkar et al., 2017 ; Tahir et al., 2017 ; Rozlin et al., 2018 ; López et al., 2019 ; Skaniakos et al., 2019 ). A study of Spanish university students showed that students reported to have learnt best the basic general knowledge in the field of study, learning, information management, problem solving, teamwork, concern for quality and motivation to achieve objectives ( López et al., 2019 ). Martínez-Clares and González-Morga (2018 ) found that students evaluated that they had developed the most in teamwork as well as in ethical and social commitment. Dinning (2017) showed that 60% or more of the students reported improvements in creativity, problem-solving, persuading and influencing, team work, project management, verbal communication, developing new ideas and making things happen, time management, and flexibility. Similarly, Ssegawa and Kasule (2017) found that students reported having learnt skills well, especially adapting to new environments and willingness to learn new ideas. Another study found that students had learned the ability to articulate employability skills ( Tomasson Goodwill et al., 2019 ). Sarkar et al. (2017) found that students' awareness of employability and underpinning skills increased. Students perceived themselves as capable of working independently ( Pop and Khampirat, 2019 ).

Some of the studies that focused broadly on sets of generic skills found that students had not learned generic skills very well (e.g., Perdigones et al., 2014 ; Monteiro et al., 2016 ) or learned only a few of them ( Abayadeera and Watty, 2016 ). Some articles listed generic skills which students experienced that they had learnt the least. These skills included time management, oral communication, negotiation, coping with stress, creating viable solutions, and meeting deadlines, ability to use computers, and teamwork ( Perdigones et al., 2014 ; Jackson, 2016a ; Ssegawa and Kasule, 2017 ). In addition, the generic skills that students perceived having had least learning in included entrepreneurial cooperation, leadership skills, IT skills, and cooperation with people from different cultures ( Pirog, 2016 ), speaking and writing in a foreign language ( Conchado et al., 2015 ; Pirog, 2016 ; Martínez-Clares and González-Morga, 2018 ), as well as conflict management ( Bonesso et al., 2015 ). Chan and Fong (2018) found that students generally rated their current competency level lower than the perceived importance of the generic skills to their future career.

Some articles also found differences in generic skills between the students. For example, students' perceptions of generic skills were the highest for students who were satisfied with the guidance and who had progressed well in their studies ( Skaniakos et al., 2019 ). Disciplinary differences were also found, showing that students from the Faculty of Education had the highest scores, while the lowest means were from students in the Faculty of Mathematics and Science and in the Faculty of Social Sciences ( Skaniakos et al., 2019 ). In addition, it was revealed that students with different motivations as well as students from different university types, disciplines, and university years engaged differently with developing generic skills ( Tran, 2017 ). Students in the flipped group reported higher scores for generic skills than students in traditional lecture courses ( Guo, 2019 ). Kirstein et al. (2019) found that students from poorer quality schools perceived that the education program developed their generic skills more than students from better quality schools. Furthermore, they found that male and African students had lower perceptions of the development of generic skills than female and white students. However, no statistically significant differences were found between students with different home languages ( Kirstein et al., 2019 ).

The findings relating to learning and development of critical thinking skills were contradictory, depending on the study design, methods and sample size. For example, Al-Thani et al. (2016) found that senior students performed better in a thinking test than junior students. However, Ding et al. (2016) did not find differences across different study years, across fields, or across university tiers. Kim (2015) reported in her case study that both graduate and doctoral students tended to show low critical thinking under minimal and enhanced scaffolds. Sotiriadou and Hill (2015) found that students reported some improvement in their critical thinking. However, at the same time, the most versatile levels of critical thinking were challenging to develop ( Sotiriadou and Hill, 2015 ). Danczak et al. (2017) found some development of critical thinking during a course, but it seems that their findings could be explained by the time that the students used in completing their test. In sum, based on the studies covered here, it seems that the development of critical thinking is uncertain or limited ( Kim, 2015 ; Ding et al., 2016 ; Danczak et al., 2017 ).

Studies on communication skills focused on both oral and written communication. Students were found to manage oral communication skills better than their counterparts in working life ( Tun Lee-Foo et al., 2015 ). It was also found that third-year students perceived significantly higher levels of improvement of oral communication skills than students in the first or second year of studies ( Mercer-Mapstone and Matthews, 2017 ).

Several articles reported improvement in students' scientific writing skills during their studies ( Drury and Muirb, 2014 ; Hryciw and Dantas, 2016 ; Pöysä-Tarhonen et al., 2016 ; Rayner et al., 2016 ). Physiology students were found to improve their performance especially in writing laboratory reports, comparing information from different sources, proposing further experiments, constructing logical arguments, interpreting results, as well as writing hypotheses, introductions, discussions, and conclusions ( Drury and Muirb, 2014 ).

The studies that focused on collaboration skills emphasized the importance of collaboration ( Chydenius and Gaisch, 2016 ; Salleh et al., 2016 , 2017 ) and teamwork skills ( García et al., 2016 ). Many studies found that the students in higher education developed a good level of performance with regard to teamwork skills ( Cela-Ranilla et al., 2014b ; Tynjälä et al., 2016 ; Sridharan et al., 2018 ; Christensen et al., 2019 ). Bravo et al. (2016) found that students perceived improvement in their understanding of how teams work.

Creativity and Problem-Solving Skills

The studies that focused on exploring students' learning and level of the skills showed contradictory results. Some studies showed that the students had learnt problem-solving and creativity skills well during their degrees ( Klegeris et al., 2017 ; Tahir et al., 2017 ; López et al., 2019 ), whereas in some studies this was true only to a certain extent ( Calma, 2017 ; Techanamurthy et al., 2018 ). Some studies explored whether the learning of these skills could be enhanced with various pedagogical approaches. Most of the studies indicated that the learning of problem-solving and creativity skills can be positively enhanced ( Wood and Bilsborow, 2014 ; Mareque et al., 2019 ; Seow et al., 2019 ). An exception to this was a study where only some of the students felt that their skills had improved, whereas others did not ( Keinänen and Kairisto-Mertanen, 2019 ).

Studies focusing on self-regulation, self-management, and self-monitoring showed that students were learning these skills. First-year students reported learning time management, learning skills, and self-monitoring skills ( Mah and Ifenthaler, 2018 ). It was also found that senior students report higher performance in self-management skills compared to freshmen ( Cela-Ranilla et al., 2014a ; Tseng et al., 2019 ). The students developed a good level of performance with regard to self-management ( Cela-Ranilla et al., 2014a ).

There were some studies that investigated student learning of ethical skills during higher education, and a variety of concepts were utilized. Students in teacher education studies were found to develop in terms of their social responsibility skills ( Howells et al., 2016 ) as well as scholarship and moral citizenship ( Steur et al., 2016 ).

Factors Enhancing or Impeding Student Learning of Generic Skills

The third aim of this review study was to identify factors that enhance or impede student learning of generic skills. First, the enhancing and impeding factors of the studies focusing on sets of generic skills are presented, followed by the results of the studies focusing on specific generic skills.

Both enhancing and impeding factors were identified in the studies that focused broadly on sets of generic skills. Most of the studies highlighted that good and well-organized teaching ( Boahin and Hofman, 2014 ; Guo et al., 2017 ) and various active learning methods, such as project-based learning ( Dinning, 2017 ; Lee et al., 2019 ), problem-based learning ( Bautista, 2016 ; Joseph et al., 2016 ; Martínez-Clares and González-Morga, 2018 ; Adriaensen et al., 2019 ; Deep et al., 2019 ), cooperative learning ( El Tantawi et al., 2014 ; Canelas et al., 2017 ; Kridiotis and Swart, 2017 ; Larraz et al., 2017 ; Martínez-Clares and González-Morga, 2018 ), flipped classroom ( Ng, 2016 ; Canelas et al., 2017 ; Guo, 2019 ), and workshops ( Krassadaki et al., 2014 ; Sarkar et al., 2017 ) enhanced the learning of generic skills. It was found that students' generic skills developed in disciplinary courses that intentionally integrated the learning of generic skills ( Windsor et al., 2014 ; Rocha, 2015 ). Additionally, satisfaction with the guidance ( Skaniakos et al., 2019 ), group work ( Prokofieva et al., 2015 ), peer interaction ( Guo, 2018 ), interaction with tutor, and defining the teamwork rules ( Carvalho, 2016 ) were positively related to generic skills learning. Positive course experiences, including appropriate workload, good teaching, clear goals and standards, and emphasis on independence were related to positive evaluations of generic skills development ( Liu et al., 2017 ). In addition, constructively aligned and continuous assessment was found to be positively related to the learning of generic skills ( Murdoch-Eaton et al., 2016 ; Ruge and McCormack, 2017 ). Peer assessment, feedback, general study guidance, and portfolio ( Adriaensen et al., 2019 ) or other reflection tasks ( Tomasson Goodwill et al., 2019 ) also enhanced the learning of generic skills.

Some studies found that games ( Fitó-Bertran et al., 2015 ; Hermnandez-Lara et al., 2018 ), role playi ng (El Tantawi et al., 2014) , business simulations ( Kelton and Kingsmill, 2016 ; Levant et al., 2016 ; Buil et al., 2018 ), and online tools or competitions ( Viviers, 2016 ; Abdulwahed and Hasna, 2017 ) enhanced the learning of generic skills. Some studies showed that different kinds of work-integrated learning environments enhanced the learning of generic skills (e.g., Jackson, 2015 ). For example, work-integrated learning curricula ( Jackson, 2015 ; Smith and Worsfold, 2015 ; Rambe, 2018 ), work experience and internships ( Levant et al., 2016 ; Bellew and Gabaudan, 2017 ; Sonnenschein et al., 2017 ), service learni ng (Kao et al., 2014) , and workplace simulations ( Bautista-Mesa et al., 2018 ) were perceived to enhance student learning of generic skills. The importance of a mentor during work-integrated learning was highlighted in a few studies ( Jackson, 2015 ; Bellew and Gabaudan, 2017 ). Furthermore, social media use for employment purposes was positively related to generic skills and internship served as a mediating mechanism through which social media use affects generic skills ( He et al., 2017 ).

Students' own personal activities also contributed to the learning of generic skills ( Ssegawa and Kasule, 2017 ). Student engagement ( Guo, 2018 ), deep approach to learning, interest, and flow experiences ( Buil et al., 2018 ) were mentioned as promoting factors. A few studies also found that higher initial skills levels was a promoting factor for learning more new skills during the academic year compared to those whose initial skills levels were lower ( Feldon et al., 2016 ) and for students' entrepreneurial intentions ( Bonesso et al., 2018 ).

Some of the studies that we reviewed identified factors that impede or challenge student learning of generic skills. Most of the impeding factors were associated with the learning environment. More precisely, teacher-focused instruction ( Guo, 2018 ), students' passive role in teachi ng (Guo, 2018) , lack of teacher-student interaction ( Guo et al., 2017 ), and overly rapid pace of teaching impeded the learning of generic skills ( Viviers, 2016 ). Poor working life and practice experiences as well as mismatches between employers' and students' expectations were also found to be challenging factors for generic skills development. Tran (2017) found five inhibiting factors: students' working part-time, a lack of information about extra-curricular activities, students' beliefs about participating bringing no benefits, competition with curriculum-based activities, and unprofessional organization of these activities. Additionally, it was shown that students' surface approach to learni ng (Guo et al., 2017) , surface motives and poor study strategies ( Yin et al., 2016 ) were related to their poor learning of generic skills.

Asking students about their experiences on factors that enhance their learning of critical thinking, one study found that inquiry-based learning methods were helpful ( Danczak et al., 2017 ). It has also been suggested that instruction that takes critical thinking into account could be a powerful tool for enhancing students' level of critical thinki ng (Al-Thani et al., 2016) . For example, scaffolding and sequential assignments have been found to improve students' critical thinking skills in some studies ( Sotiriadou and Hill, 2015 ) but not always ( Kim, 2015 ). Research on performance-based assessment has shown that students' primary knowledge enhances performance and motivation in reasoni ng (Lespiau and Tricot, 2018) .

In several studies, various e-learning resources were found to enhance students' written communication skills. A specific e-learning environment that provides resources for learning discipline-specific content and writing was found to improve both students' written communication skills and content understandi ng (Drury and Muirb, 2014) . A scaffolded learning approach including both online writing tasks and active-learning lectures, small-group discussions, and collaborative workshops improved students' scientific literacy skills ( Hryciw and Dantas, 2016 ). Additionally, role models in terms of communication skills, feedback on performance ( Van Ginkel et al., 2015 ), mentoring, and peer collaboration were found to be influential factors for student learning ( Jackson, 2014b , 2016b) . Also, explicit teaching of science communication skills embedded in courses was found to be influential ( Mercer-Mapstone and Kuchel, 2016 ).

Studies focusing on collaboration skills indicated that factors related to teaching and learning environments were found to enhance the learning of generic skills. Team-based learning in accounting courses enhanced student perceptions of their ability to work effectively in diverse teams, as well as other teamwork abilities such as cultural diversity, leadership and planning, and implementation ( Christensen et al., 2019 ). Students were found to learn collaboratively when working on their study task in a culturally mixed small group ( Daly et al., 2015 ). Bravo et al. (2016) showed that teamwork processes have significant effects on improvements in teamwork skills, and thus teachers should use assignments that require managing these teamwork processes rather than focusing solely on the success of the assignment. Students perceived six factors that contribute to positive student teamwork experiences: shared team goals; cultural diversity; adaptable work skills; challenging task context; collaborative research; cross-functional teams ( Volkov and Volkov, 2015 ). Sridharan et al. (2018) found that peer assessment improved collaboration skills. Digital games provide an excellent online learning environment for students to work in and improve their teamwork skills ( Cela-Ranilla et al., 2014b ). Online learning environments utilizing problem-based learning, and providing versatile support and encouragement for continuous assessment, were reported to enhance students' teamwork skills ( García et al., 2016 ). Work-integrated learning helped undergraduates to develop their interpersonal skills ( Ibrahim and Jaaffar, 2017a ).

Most of the studies explored the effect of implementing different pedagogical approaches or interventions to enhance students' learning of problem-solving, innovation, and creativity skills. For example, a design-based research approach was found to improve students' creativity skills ( Wood and Bilsborow, 2014 ). Innovation pedagogy enhanced students' learning of different innovation competences, and introducing an experiential learning pedagogy was found to improve students' problem-solving skills ( Seow et al., 2019 ). Various arts-related leisure activities were found to be positively related to creativity ( Mareque et al., 2019 ). Incorporating generic skills (including creativity and problem-solving) within curricula and academic courses was found to be correlated with students' satisfaction in learning those skills ( Tahir et al., 2017 ). Some studies also indicate that students' problem-solving skills evolve along with university experience, further suggesting that some instructional methods might be especially beneficial in enhancing the learning of those skills (such as problem-based learning, case studies, team-based learning) as opposed to traditional lecture-style courses ( Klegeris et al., 2017 ).

Several enhancing factors of self-regulation skills were indicated by the studies. The use of teaching and learning materials improved the attitude of learners to the development of self- and social competencies ( Edeling and Pilz, 2016 ). In addition, work-related factors such as work-integrated programs ( Ibrahim and Jaaffar, 2017b ) and the training company enhance students' learning of self-management skills ( Edeling and Pilz, 2016 ). Furthermore, it was also found that a 3D simulation learning environment and digital games ( Cela-Ranilla et al., 2014a , b ) enhanced student learning of self-management skills.

It was found that reflective writing tasks as well as other learning and assessment experiences provided during the course enhanced student teachers' learning of social responsibility skills ( Howells et al., 2016 ). Taplin et al. (2018) found that use of role-play enhanced student learning of ethical skills.

Our systematic review study contributes to the research on generic skills by structuring the current research in the field, elaborating the concepts and theories related to learning generic skills, and clarifying the methods utilized in the empirical studies. The study revealed the remarkable variation in concepts and their definitions, research methods, and the way generic skills were measured. The conceptual variation manifested itself in many different ways. Most of the reviewed studies investigated sets of generic skills and used the term generic skills or other similar concept, such as employability skills, transferable skills, soft skills, graduate attributes, or generic competencies. These results reflect those of Lizzio et al. (2002) and Barrie (2006) , who also found that generic skills are known by several other terms. The number of generic skills explored ranged from one or two skills to several dozen. The present study thus clearly shows that “generic skills” is used as an umbrella term, which can include various wide-ranging skills. Some of the articles framed their research with generic skills but focused more specifically on individual specific generic skills. The studies exploring specific skills had their focus on one of six generic skills. These skills were critical thinking, communication skills, collaboration skills, creativity and problem-solving skills, self-regulation skills, and ethical skills. Similar skills have been found in a previous review study that explored generic competences and found that the most frequently appearing generic competences were a set of conceptual skills, people skills, and personal skills ( Strijbos et al., 2015 ).

It was somewhat surprising that the studies that focused on sets of generic skills most often measured professional skills such as professionalism and leadership skills. These skills are not higher-order thinking skills, which are outlined as the key skills and aims of higher education ( Strijbos et al., 2015 ; OECD, 2019 ). The high amount of professional skills in the articles studied may be due to the emphasis on working life. Consequently, in many studies the learning of generic skills was justified by the need for these skills in working life. After the professional skills, analytical skills, applying knowledge, communication, and collaboration were most often operationalized as generic skills in the surveys. These skills can be considered higher-order thinking skills and important for professionals in various fields. There is surprisingly little research on generic skills and their relation to learning processes, although these skills are needed in quality learning and studying ( Badcock et al., 2010 ; Arum and Roksa, 2011 ; Tuononen and Parpala, 2021 ). In addition, these skills are important for lifelong learning.

A more accurate analysis of the articles focusing on sets of generic skills showed inconsistency in the instruments used. Almost every study introduced its own survey instrument to measure generic skills. In these studies, the operationalization of the measured skills was often incoherent, and they failed to give an explicit definition of generic skills. The present review study confirmed the previous findings, which have demonstrated several problems in surveys in the research field of generic skills. For example, abstract or vague expressions and double-barreled items in the questionnaires have been found ( Braun et al., 2012 ).

Most of the studies in this review used self-report methods with a cross-sectional study design. The studies with a longitudinal design focused mostly on a short period of time, e.g., one course or one semester. While the methods chosen may reflect a lack of long-term research resources, more thought should be put into methods to capture actual skills and their development. Self-report measures only capture students' perceptions and experiences, while performance-based assessments would enable a deeper understanding of students' competency ( Zlatkin-Troitschanskaia et al., 2015 ). Furthermore, while cross-sectional studies do not inform us about the development of generic skills, even longitudinal designs that focus on short periods of time can provide inaccurate information about actual development of skills. The learning of generic skills takes time ( Arum and Roksa, 2011 ; Hyytinen et al., 2019 ; Muukkonen et al., 2019 ), and such designs may not be able to capture the development, or the development that they capture may not be lasting. Additionally, only a few studies used performance-based assessments to explore generic skills. This was somewhat surprising, since investigating skills with performance-based assessment would be ontologically and methodologically reasonable ( McClelland, 1973 ; Ercikan and Oliveri, 2016 ; Hyytinen et al., 2021 ). Additionally, more performance-based assessments of generic skills with larger data sets are needed ( Al-Thani et al., 2016 ). One another methodological aspect relates to the level of analysis. Most of the articles utilize group-level analysis, which may not reveal individual variation in perceptions of learning generic skills.

Conceptual and methodological shortcomings make it difficult to compare studies, and build a cumulative understanding about the status of generic skills in higher education. Additionally, each of the studies focuses on different sets of skills, which complicates the matter. The studies that focus on specific individual skills such as critical thinking, problem-solving or collaboration skills are often more advanced in their theoretical and conceptual framework, as well as methods, compared with studies that focus on a varied set of skills. This is probably due to the conceptual clarity in the field of the respective skill, e.g., critical thinking. In order to contribute to higher education research, studies of generic skills need to strive for increased clarity and coherence.

Our aim was also to explore how higher education students have learned generic skills during their studies. A coherent picture of the learned generic skills is relatively challenging to capture because the articles have focused on different sets of generic skills with various surveys. Although students in many studies perceived that they had learned generic skills well, some studies indicated that their learning of generic skills was limited. Additionally, some studies indicated that there were differences between the students in learning generic skills, for example, regarding their discipline. Furthermore, it is also important to remember that most of the studies reviewed mainly explored students' own experiences in learning generic skills, not their actual level of generic skills (cf. Braun et al., 2012 ; Zlatkin-Troitschanskaia et al., 2015 ). However, it is noteworthy that there was also contradictory evidence about students' generic skills learning based on the studies that used performance-based assessment and whether these skills develop during studies.

The present review study also identified enhancing and impeding factors that were found to be associated with learning generic skills in the studies. The results indicated that most of these factors were contextual, relating to the teaching and learning environment, rather than focusing on individual factors. Active learning methods that emphasize students' activity and role in the learning process were most often found to be enhancing factors. In addition, the role of different digital learning environments such as games and online tools in the learning of generic skills was investigated, and they were usually perceived as useful. Work-based learning and work-related projects were also perceived as useful. It was interesting that previous knowledge and initial skill level were related to the learning of new generic skills. This finding supports evidence from previous studies (e.g., Richardson et al., 2012 ). In addition, students' own personal activities, such as student engagement, deep approach to learning, and interest were individual factors that were found to enhance the learning of generic skills (cf. Arum and Roksa, 2011 ). The impeding factors were also mainly associated with the learning environment. For example, teacher-focused instruction, lack of interaction, and poor working life and practice experiences were found to be negatively related to the learning of generic skills.

Limitations

Some limitations of this review study have been identified. First, these articles were searched for using the term generic skills, not specific skills. Therefore, the sample of critical thinking studies, and certain other skills, does not represent all research in the field. Second, we only included articles for 5 years in the analysis, and thus the sample does not comprehensively describe the research of generic skills and how generic skills research has developed during the 2010s. The number of studies published was so large that we were not able to include more years in this review study. Third, the enhancing and impeding factors found in the studies were based mainly on self-reports. Thus, how much they actually enhance or impede the learning of generic skills has not been explored in these studies.

Conclusions

The present study shows that there is a lot of research activity in this area, indicating the importance and relevance of generic skills research. To ensure the development of research on generic skills, it is essential to enhance the dialogue between theoretical, methodological, and empirical perspectives to extend previous work in the field. The results of the present study demonstrate that the challenges in exploring generic skills are both methodological and theoretical in nature (cf. Barrie, 2006 ; Braun et al., 2012 ; El Soufi and See, 2019 ). The problem is that the results do not accumulate because so many different theoretical frameworks, concepts, definitions, and instruments are used. Therefore, we suggest that existing valid instruments should be utilized when new studies are constructed. In this way, the definition of concepts will become clearer and valid instruments will evolve. Generic skills can be explored using self-reports if valid instruments are used. In addition, self-reports can be used to develop students' reflection skills and help students to recognize and evaluate their generic skills ( Kyndt et al., 2014 ). However, this review study showed that intervention and longitudinal studies are needed but such study designs are demanding and require greater resources. In the future, it would be interesting to explore how the learning of generic skills progresses during studies and how a high level of certain skills can promote the learning of other skills. This review study advances new research on higher education student learning of generic skills and also contributes to the practical development of teaching and learning in higher education by indicating the enhancing and impeding factors.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Author Contributions

TT, HH, and AT contributed to conception and design of the study. TT and HH conducted literature search. TT, HH, AT, and KK wrote other sections of the manuscript. All authors analyzed and wrote the results. All authors contributed to manuscript revision, read, and approved the submitted version.

This work was supported by the Finnish Ministry of Education and Culture (Grant Number: OKM/280/523/2017). University of Helsinki, Finland has covered the article processing fee.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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Keywords: generic skills, learning, higher education, systematic (literature) review, enhancing and impeding factors

Citation: Tuononen T, Hyytinen H, Kleemola K, Hailikari T, Männikkö I and Toom A (2022) Systematic Review of Learning Generic Skills in Higher Education—Enhancing and Impeding Factors. Front. Educ. 7:885917. doi: 10.3389/feduc.2022.885917

Received: 28 February 2022; Accepted: 03 May 2022; Published: 26 May 2022.

Reviewed by:

Copyright © 2022 Tuononen, Hyytinen, Kleemola, Hailikari, Männikkö and Toom. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Tarja Tuononen, tarja.tuononen@helsinki.fi

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Why do Study Skills Matter?

Posted on: February 10, 2020

Every student is familiar with the term ‘study skills.’ But not everyone really knows or understands what they are or why they matter. After all, if your grades are pretty good why you should worry about improving your study skills?

What are study skills?

Study skills are a range of approaches to learning that improve your ability to study, and to retain and recall information. Spending time on improving your study skills, no matter how good your grades are, has to be time well spent.

Some people are naturally good at time management but may struggle with critical thinking. Another student may be great at taking notes but isn’t great at putting a concept into their own words. To be able to really do your best in your studies and easily demonstrate your learning, you need to spend time developing your study skills.

Many universities will offer classes in improving study skills and it is always worth signing up for them. But there’s many things you can do yourself to push your studies forward that bit further.

Some key study skills

Time management.

Too many people think students have an easy life. After all, it’s all drinking, hangovers and having fun with your friends. Students only bother studying around exam time, right?

We all know that isn’t true. Yes, university is a lot of fun, but it is also a lot of hard work. Juggling your classes, coursework, and reading assignments alongside your part time job can be exhausting. When you’re busy studying your time management skills becomes essential. At the start of each term or semester, as soon as you get your timetable and course information, write down every due date then work backwards, deciding when you will need to begin each piece of coursework. Give yourself more time than you really need but stick to the planned dates to make sure you are prepared for any unexpected blocks in the road.

It’s also a good idea to block out a set time every day to study and, no matter what comes along, do your best to stick to it. Form good habits early in your university life and you will find it much easier, and with discipline you’ll find yourself achieving more.

Learning tools

We all learn differently. Some thrive in lectures, absorbing everything that is said. Others take copious notes in order to remember. For some, diagrams and charts are an important part of taking information on board. There are many tools out there to aid learning. Some will work for you and some won’t. Talk to your friends and find out what they do to make sure they remember important information and ideas. They may use tools that you have never encountered, tools that you may find really useful. Just make sure you share with them in return!

There are many useful ways of learning; flash-cards, mnemonics, mind-maps… there are so many tools that everyone can find something that works for them. If you find you’re struggling to grasp a concept, speak to your lecturer who will definitely have suggestions for how you can get a form hold of that idea. Don’t forget that they were students once too.

Note-taking

Taking good notes is an art form and there are many ways to make your notes work for you. It’s rarely helpful to write down everything, word-for-word, that you hear in a lecture. Instead, write down key thoughts or ideas that the speaker is discussing. Write down thoughts and questions that you have around the subject. Once the lecture is over try coding each separate concept in a different colour, with supporting points in the same colour as you’ve used for the concept. That way you’ll build up a bank of easy-to-reference notes throughout your course making things easier to find and easier to reference when you need them.

Revise your notes as soon as possible after you’re written them. Make sure that everything you’ve taken down makes sense, that you understand all the concepts and haven’t got any unfinished thoughts to confuse things. If any questions come out of your notes speak to your lecturer.

Critical thinking

What is critical thinking? Put simply it is using your reasoning abilities to challenge the ideas and concepts that you are learning about. It is a skill essential for many subjects of study and one that will prove useful in class discussions and in essay writing. It is likely that this a skill your lecturers will help you to develop, and for some courses there are focussed classes on it as well as many books available. Improving your critical thinking skills is essential to you being able to dig deeper and develop your understanding of your chosen subject of study and it will be of huge use in your day-to-day life too.

Ask questions

Is asking questions really a skill? Yes, it is. Apart from demonstrating to your teacher that you are an active participant in class it also enables you to find out more about areas that may be confusing you. It’s a way to (kindly) challenge what another class member has suggested and to help yourself gain a deeper understanding.

As has already been touched on, asking your lecturer questions when you’re stuck or need a clearer explanation will help you further in the course. It can be intimidating admitting that you don’t understand something, but every teacher was a student once and one of the reasons they are in this job is to help you do the best you can.

Study groups

Joining, or starting, a study group can be invaluable. It offers you the chance to support others on your course and to learn from them. The interaction will build your teamwork skills as well as friendships. You may find that other members of your study group have insights into your subject that haven’t occurred to you. And at the stressful times around coursework deadlines and exam periods you can test each other and help each other too.

In all of the pressure of university life, looking after yourself is a bit of a skill too. Don’t forget to set aside time to relax, to see friends, to exercise, or simply to sleep. With a deadline looming it can be tempting to spend every minute working on that essay or preparing for that exam. But evidence shows you will do worse if you haven’t been taking care of yourself.

Even if finding a spare half-hour seems impossible, it’s important to find it. Cook yourself a nice dinner, watch an episode of your favourite TV programme, find some way to relax. It may feel indulgent, but you’ll be glad you did later on.

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Developing your Academic Skills

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by Elef Moschou

Last semester I joined the ELSP (English Language Support Project) as a volunteer. As a participant I speak to various new students, and we discussed about the university life and Aberdeen. This programme is an excellent opportunity to develop my speaking skills. During university you might often be called to present your work, structured and cohesive speaking will be very helpful. Being a good presenter will also enable you to have a more structured way of thinking when planning essays or during tests. Moreover, joining us, the content creators, and/or the university newspaper, The Gaudie, will also assist you in developing your writing and speaking skills. As creative writing allows you to further develop your thinking process it can be useful even if you are in a degree programme that does not require essay writing.

The university’s Student Learning Service also offers creative writing resources, workshops, and individual sessions. In my opinion, especially when your programme does not require a particular skill, it gives you an extra reason to try and develop it on your own. Having a well-rounded skillset will enhance your employability and it will be beneficial in other aspects of your life. The Student Learning Service furthermore provides more academic assistance. Including academic writing, you can find math support and assistance in studying. What I personally appreciate a lot is that you can choose whether you want to be alone or in a group. Needless to say that professional help is always better when you do not know where to start from.

Enhancing your academic skills can be achieved through multiple ways. Finding the right way for you and your needs can ensure higher success. Don’t fear trying out new things and asking for help. When trying out something, whether it is a society, going for walks or even something as simple as cleaning, make the most out of it and be active in experiencing life. Go take a look on the resources available and tell me all about it in the comments, good luck.

Information on developing your academic skills can be found on our Study Support page, click here for more information.

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The Importance of Students’ Motivation for Their Academic Achievement – Replicating and Extending Previous Findings

Ricarda steinmayr.

1 Department of Psychology, TU Dortmund University, Dortmund, Germany

Anne F. Weidinger

Malte schwinger.

2 Department of Psychology, Philipps-Universität Marburg, Marburg, Germany

Birgit Spinath

3 Department of Psychology, Heidelberg University, Heidelberg, Germany

Associated Data

The datasets generated for this study are available on request to the corresponding author.

Achievement motivation is not a single construct but rather subsumes a variety of different constructs like ability self-concepts, task values, goals, and achievement motives. The few existing studies that investigated diverse motivational constructs as predictors of school students’ academic achievement above and beyond students’ cognitive abilities and prior achievement showed that most motivational constructs predicted academic achievement beyond intelligence and that students’ ability self-concepts and task values are more powerful in predicting their achievement than goals and achievement motives. The aim of the present study was to investigate whether the reported previous findings can be replicated when ability self-concepts, task values, goals, and achievement motives are all assessed at the same level of specificity as the achievement criteria (e.g., hope for success in math and math grades). The sample comprised 345 11th and 12th grade students ( M = 17.48 years old, SD = 1.06) from the highest academic track (Gymnasium) in Germany. Students self-reported their ability self-concepts, task values, goal orientations, and achievement motives in math, German, and school in general. Additionally, we assessed their intelligence and their current and prior Grade point average and grades in math and German. Relative weight analyses revealed that domain-specific ability self-concept, motives, task values and learning goals but not performance goals explained a significant amount of variance in grades above all other predictors of which ability self-concept was the strongest predictor. Results are discussed with respect to their implications for investigating motivational constructs with different theoretical foundation.

Introduction

Achievement motivation energizes and directs behavior toward achievement and therefore is known to be an important determinant of academic success (e.g., Robbins et al., 2004 ; Hattie, 2009 ; Plante et al., 2013 ; Wigfield et al., 2016 ). Achievement motivation is not a single construct but rather subsumes a variety of different constructs like motivational beliefs, task values, goals, and achievement motives (see Murphy and Alexander, 2000 ; Wigfield and Cambria, 2010 ; Wigfield et al., 2016 ). Nevertheless, there is still a limited number of studies, that investigated (1) diverse motivational constructs in relation to students’ academic achievement in one sample and (2) additionally considered students’ cognitive abilities and their prior achievement ( Steinmayr and Spinath, 2009 ; Kriegbaum et al., 2015 ). Because students’ cognitive abilities and their prior achievement are among the best single predictors of academic success (e.g., Kuncel et al., 2004 ; Hailikari et al., 2007 ), it is necessary to include them in the analyses when evaluating the importance of motivational factors for students’ achievement. Steinmayr and Spinath (2009) did so and revealed that students’ domain-specific ability self-concepts followed by domain-specific task values were the best predictors of students’ math and German grades compared to students’ goals and achievement motives. However, a flaw of their study is that they did not assess all motivational constructs at the same level of specificity as the achievement criteria. For example, achievement motives were measured on a domain-general level (e.g., “Difficult problems appeal to me”), whereas students’ achievement as well as motivational beliefs and task values were assessed domain-specifically (e.g., math grades, math self-concept, math task values). The importance of students’ achievement motives for math and German grades might have been underestimated because the specificity levels of predictor and criterion variables did not match (e.g., Ajzen and Fishbein, 1977 ; Baranik et al., 2010 ). The aim of the present study was to investigate whether the seminal findings by Steinmayr and Spinath (2009) will hold when motivational beliefs, task values, goals, and achievement motives are all assessed at the same level of specificity as the achievement criteria. This is an important question with respect to motivation theory and future research in this field. Moreover, based on the findings it might be possible to better judge which kind of motivation should especially be fostered in school to improve achievement. This is important information for interventions aiming at enhancing students’ motivation in school.

Theoretical Relations Between Achievement Motivation and Academic Achievement

We take a social-cognitive approach to motivation (see also Pintrich et al., 1993 ; Elliot and Church, 1997 ; Wigfield and Cambria, 2010 ). This approach emphasizes the important role of students’ beliefs and their interpretations of actual events, as well as the role of the achievement context for motivational dynamics (see Weiner, 1992 ; Pintrich et al., 1993 ; Wigfield and Cambria, 2010 ). Social cognitive models of achievement motivation (e.g., expectancy-value theory by Eccles and Wigfield, 2002 ; hierarchical model of achievement motivation by Elliot and Church, 1997 ) comprise a variety of motivation constructs that can be organized in two broad categories (see Pintrich et al., 1993 , p. 176): students’ “beliefs about their capability to perform a task,” also called expectancy components (e.g., ability self-concepts, self-efficacy), and their “motivational beliefs about their reasons for choosing to do a task,” also called value components (e.g., task values, goals). The literature on motivation constructs from these categories is extensive (see Wigfield and Cambria, 2010 ). In this article, we focus on selected constructs, namely students’ ability self-concepts (from the category “expectancy components of motivation”), and their task values and goal orientations (from the category “value components of motivation”).

According to the social cognitive perspective, students’ motivation is relatively situation or context specific (see Pintrich et al., 1993 ). To gain a comprehensive picture of the relation between students’ motivation and their academic achievement, we additionally take into account a traditional personality model of motivation, the theory of the achievement motive ( McClelland et al., 1953 ), according to which students’ motivation is conceptualized as a relatively stable trait. Thus, we consider the achievement motives hope for success and fear of failure besides students’ ability self-concepts, their task values, and goal orientations in this article. In the following, we describe the motivation constructs in more detail.

Students’ ability self-concepts are defined as cognitive representations of their ability level ( Marsh, 1990 ; Wigfield et al., 2016 ). Ability self-concepts have been shown to be domain-specific from the early school years on (e.g., Wigfield et al., 1997 ). Consequently, they are frequently assessed with regard to a certain domain (e.g., with regard to school in general vs. with regard to math).

In the present article, task values are defined in the sense of the expectancy-value model by Eccles et al. (1983) and Eccles and Wigfield (2002) . According to the expectancy-value model there are three task values that should be positively associated with achievement, namely intrinsic values, utility value, and personal importance ( Eccles and Wigfield, 1995 ). Because task values are domain-specific from the early school years on (e.g., Eccles et al., 1993 ; Eccles and Wigfield, 1995 ), they are also assessed with reference to specific subjects (e.g., “How much do you like math?”) or on a more general level with regard to school in general (e.g., “How much do you like going to school?”).

Students’ goal orientations are broader cognitive orientations that students have toward their learning and they reflect the reasons for doing a task (see Dweck and Leggett, 1988 ). Therefore, they fall in the broad category of “value components of motivation.” Initially, researchers distinguished between learning and performance goals when describing goal orientations ( Nicholls, 1984 ; Dweck and Leggett, 1988 ). Learning goals (“task involvement” or “mastery goals”) describe people’s willingness to improve their skills, learn new things, and develop their competence, whereas performance goals (“ego involvement”) focus on demonstrating one’s higher competence and hiding one’s incompetence relative to others (e.g., Elliot and McGregor, 2001 ). Performance goals were later further subdivided into performance-approach (striving to demonstrate competence) and performance-avoidance goals (striving to avoid looking incompetent, e.g., Elliot and Church, 1997 ; Middleton and Midgley, 1997 ). Some researchers have included work avoidance as another component of achievement goals (e.g., Nicholls, 1984 ; Harackiewicz et al., 1997 ). Work avoidance refers to the goal of investing as little effort as possible ( Kumar and Jagacinski, 2011 ). Goal orientations can be assessed in reference to specific subjects (e.g., math) or on a more general level (e.g., in reference to school in general).

McClelland et al. (1953) distinguish the achievement motives hope for success (i.e., positive emotions and the belief that one can succeed) and fear of failure (i.e., negative emotions and the fear that the achievement situation is out of one’s depth). According to McClelland’s definition, need for achievement is measured by describing affective experiences or associations such as fear or joy in achievement situations. Achievement motives are conceptualized as being relatively stable over time. Consequently, need for achievement is theorized to be domain-general and, thus, usually assessed without referring to a certain domain or situation (e.g., Steinmayr and Spinath, 2009 ). However, Sparfeldt and Rost (2011) demonstrated that operationalizing achievement motives subject-specifically is psychometrically useful and results in better criterion validities compared with a domain-general operationalization.

Empirical Evidence on the Relative Importance of Achievement Motivation Constructs for Academic Achievement

A myriad of single studies (e.g., Linnenbrink-Garcia et al., 2018 ; Muenks et al., 2018 ; Steinmayr et al., 2018 ) and several meta-analyses (e.g., Robbins et al., 2004 ; Möller et al., 2009 ; Hulleman et al., 2010 ; Huang, 2011 ) support the hypothesis of social cognitive motivation models that students’ motivational beliefs are significantly related to their academic achievement. However, to judge the relative importance of motivation constructs for academic achievement, studies need (1) to investigate diverse motivational constructs in one sample and (2) to consider students’ cognitive abilities and their prior achievement, too, because the latter are among the best single predictors of academic success (e.g., Kuncel et al., 2004 ; Hailikari et al., 2007 ). For effective educational policy and school reform, it is crucial to obtain robust empirical evidence for whether various motivational constructs can explain variance in school performance over and above intelligence and prior achievement. Without including the latter constructs, we might overestimate the importance of motivation for achievement. Providing evidence that students’ achievement motivation is incrementally valid in predicting their academic achievement beyond their intelligence or prior achievement would emphasize the necessity of designing appropriate interventions for improving students’ school-related motivation.

There are several studies that included expectancy and value components of motivation as predictors of students’ academic achievement (grades or test scores) and additionally considered students’ prior achievement ( Marsh et al., 2005 ; Steinmayr et al., 2018 , Study 1) or their intelligence ( Spinath et al., 2006 ; Lotz et al., 2018 ; Schneider et al., 2018 ; Steinmayr et al., 2018 , Study 2, Weber et al., 2013 ). However, only few studies considered intelligence and prior achievement together with more than two motivational constructs as predictors of school students’ achievement ( Steinmayr and Spinath, 2009 ; Kriegbaum et al., 2015 ). Kriegbaum et al. (2015) examined two expectancy components (i.e., ability self-concept and self-efficacy) and eight value components (i.e., interest, enjoyment, usefulness, learning goals, performance-approach, performance-avoidance goals, and work avoidance) in the domain of math. Steinmayr and Spinath (2009) investigated the role of an expectancy component (i.e., ability self-concept), five value components (i.e., task values, learning goals, performance-approach, performance-avoidance goals, and work avoidance), and students’ achievement motives (i.e., hope for success, fear of failure, and need for achievement) for students’ grades in math and German and their GPA. Both studies used relative weights analyses to compare the predictive power of all variables simultaneously while taking into account multicollinearity of the predictors ( Johnson and LeBreton, 2004 ; Tonidandel and LeBreton, 2011 ). Findings showed that – after controlling for differences in students‘ intelligence and their prior achievement – expectancy components (ability self-concept, self-efficacy) were the best motivational predictors of achievement followed by task values (i.e., intrinsic/enjoyment, attainment, and utility), need for achievement and learning goals ( Steinmayr and Spinath, 2009 ; Kriegbaum et al., 2015 ). However, Steinmayr and Spinath (2009) who investigated the relations in three different domains did not assess all motivational constructs on the same level of specificity as the achievement criteria. More precisely, students’ achievement as well as motivational beliefs and task values were assessed domain-specifically (e.g., math grades, math self-concept, math task values), whereas students’ goals were only measured for school in general (e.g., “In school it is important for me to learn as much as possible”) and students’ achievement motives were only measured on a domain-general level (e.g., “Difficult problems appeal to me”). Thus, the importance of goals and achievement motives for math and German grades might have been underestimated because the specificity levels of predictor and criterion variables did not match (e.g., Ajzen and Fishbein, 1977 ; Baranik et al., 2010 ). Assessing students’ goals and their achievement motives with reference to a specific subject might result in higher associations with domain-specific achievement criteria (see Sparfeldt and Rost, 2011 ).

Taken together, although previous work underlines the important roles of expectancy and value components of motivation for school students’ academic achievement, hitherto, we know little about the relative importance of expectancy components, task values, goals, and achievement motives in different domains when all of them are assessed at the same level of specificity as the achievement criteria (e.g., achievement motives in math → math grades; ability self-concept for school → GPA).

The Present Research

The goal of the present study was to examine the relative importance of several of the most important achievement motivation constructs in predicting school students’ achievement. We substantially extend previous work in this field by considering (1) diverse motivational constructs, (2) students’ intelligence and their prior achievement as achievement predictors in one sample, and (3) by assessing all predictors on the same level of specificity as the achievement criteria. Moreover, we investigated the relations in three different domains: school in general, math, and German. Because there is no study that assessed students’ goal orientations and achievement motives besides their ability self-concept and task values on the same level of specificity as the achievement criteria, we could not derive any specific hypotheses on the relative importance of these constructs, but instead investigated the following research question (RQ):

RQ. What is the relative importance of students’ domain-specific ability self-concepts, task values, goal orientations, and achievement motives for their grades in the respective domain when including all of them, students’ intelligence and prior achievement simultaneously in the analytic models?

Materials and Methods

Participants and procedure.

A sample of 345 students was recruited from two German schools attending the highest academic track (Gymnasium). Only 11th graders participated at one school, whereas 11th and 12th graders participated at the other. Students of the different grades and schools did not differ significantly on any of the assessed measures. Students represented the typical population of this type of school in Germany; that is, the majority was Caucasian and came from medium to high socioeconomic status homes. At the time of testing, students were on average 17.48 years old ( SD = 1.06). As is typical for this kind of school, the sample comprised more girls ( n = 200) than boys ( n = 145). We verify that the study is in accordance with established ethical guidelines. Approval by an ethics committee was not required as per the institution’s guidelines and applicable regulations in the federal state where the study was conducted. Participation was voluntarily and no deception took place. Before testing, we received written informed consent forms from the students and from the parents of the students who were under the age of 18 on the day of the testing. If students did not want to participate, they could spend the testing time in their teacher’s room with an extra assignment. All students agreed to participate. Testing took place during regular classes in schools in 2013. Tests were administered by trained research assistants and lasted about 2.5 h. Students filled in the achievement motivation questionnaires first, and the intelligence test was administered afterward. Before the intelligence test, there was a short break.

Ability Self-Concept

Students’ ability self-concepts were assessed with four items per domain ( Schöne et al., 2002 ). Students indicated on a 5-point scale ranging from 1 (totally disagree) to 5 (totally agree) how good they thought they were at different activities in school in general, math, and German (“I am good at school in general/math/German,” “It is easy to for me to learn in school in general/math/German,” “In school in general/math/German, I know a lot,” and “Most assignments in school/math/German are easy for me”). Internal consistency (Cronbach’s α) of the ability self-concept scale was high in school in general, in math, and in German (0.82 ≤ α ≤ 0.95; see Table 1 ).

Means ( M ), Standard Deviations ( SD ), and Reliabilities (α) for all measures.

Task Values

Students’ task values were assessed with an established German scale (SESSW; Subjective scholastic value scale; Steinmayr and Spinath, 2010 ). The measure is an adaptation of items used by Eccles and Wigfield (1995) in different studies. It assesses intrinsic values, utility, and personal importance with three items each. Students indicated on a 5-point scale ranging from 1 (totally disagree) to 5 (totally agree) how much they valued school in general, math, and German (Intrinsic values: “I like school/math/German,” “I enjoy doing things in school/math/German,” and “I find school in general/math/German interesting”; Utility: “How useful is what you learn in school/math/German in general?,” “School/math/German will be useful in my future,” “The things I learn in school/math/German will be of use in my future life”; Personal importance: “Being good at school/math/German is important to me,” “To be good at school/math/German means a lot to me,” “Attainment in school/math/German is important to me”). Internal consistency of the values scale was high in all domains (0.90 ≤ α ≤ 0.93; see Table 1 ).

Goal Orientations

Students’ goal orientations were assessed with an established German self-report measure (SELLMO; Scales for measuring learning and achievement motivation; Spinath et al., 2002 ). In accordance with Sparfeldt et al. (2007) , we assessed goal orientations with regard to different domains: school in general, math, and German. In each domain, we used the SELLMO to assess students’ learning goals, performance-avoidance goals, and work avoidance with eight items each and their performance-approach goals with seven items. Students’ answered the items on a 5-point scale ranging from 1 (totally disagree) to 5 (totally agree). All items except for the work avoidance items are printed in Spinath and Steinmayr (2012) , p. 1148). A sample item to assess work avoidance is: “In school/math/German, it is important to me to do as little work as possible.” Internal consistency of the learning goals scale was high in all domains (0.83 ≤ α ≤ 0.88). The same was true for performance-approach goals (0.85 ≤ α ≤ 0.88), performance-avoidance goals (α = 0.89), and work avoidance (0.91 ≤ α ≤ 0.92; see Table 1 ).

Achievement Motives

Achievement motives were assessed with the Achievement Motives Scale (AMS; Gjesme and Nygard, 1970 ; Göttert and Kuhl, 1980 ). In the present study, we used a short form measuring “hope for success” and “fear of failure” with the seven items per subscale that showed the highest factor loadings. Both subscales were assessed in three domains: school in general, math, and German. Students’ answered all items on a 4-point scale ranging from 1 (does not apply at all) to 4 (fully applies). An example hope for success item is “In school/math/German, difficult problems appeal to me,” and an example fear of failure item is “In school/math/German, matters that are slightly difficult disconcert me.” Internal consistencies of hope for success and fear of failure scales were high in all domains (hope for success: 0.88 ≤ α ≤ 0.92; fear of failure: 0.90 ≤ α ≤ 0.91; see Table 1 ).

Intelligence

Intelligence was measured with the basic module of the Intelligence Structure Test 2000 R, a well-established German multifactor intelligence measure (I-S-T 2000 R; Amthauer et al., 2001 ). The basic module of the test offers assessments of domain-specific intelligence for verbal, numeric, and figural abilities as well as an overall intelligence score (a composite of the three facets). The overall intelligence score is thought to measure reasoning as a higher order factor of intelligence and can be interpreted as a measure of general intelligence, g . Its construct validity has been demonstrated in several studies ( Amthauer et al., 2001 ; Steinmayr and Amelang, 2006 ). In the present study, we used the scores that were closest to the domains we investigated: overall intelligence, numerical intelligence, and verbal intelligence (see also Steinmayr and Spinath, 2009 ). Raw values could range from 0 to 60 for verbal and numerical intelligence, and from 0 to 180 for overall intelligence. Internal consistencies of all intelligence scales were high (0.71 ≤ α ≤ 0.90; see Table 1 ).

Academic Achievement

For all students, the school delivered the report cards that the students received 3 months before testing (t0) and 4 months after testing (t2), at the end of the term in which testing took place. We assessed students’ grades in German and math as well as their overall grade point average (GPA) as criteria for school performance. GPA was computed as the mean of all available grades, not including grades in the nonacademic domains Sports and Music/Art as they did not correlate with the other grades. Grades ranged from 1 to 6, and were recoded so that higher numbers represented better performance.

Statistical Analyses

We conducted relative weight analyses to predict students’ academic achievement separately in math, German, and school in general. The relative weight analysis is a statistical procedure that enables to determine the relative importance of each predictor in a multiple regression analysis (“relative weight”) and to take adequately into account the multicollinearity of the different motivational constructs (for details, see Johnson and LeBreton, 2004 ; Tonidandel and LeBreton, 2011 ). Basically, it uses a variable transformation approach to create a new set of predictors that are orthogonal to one another (i.e., uncorrelated). Then, the criterion is regressed on these new orthogonal predictors, and the resulting standardized regression coefficients can be used because they no longer suffer from the deleterious effects of multicollinearity. These standardized regression weights are then transformed back into the metric of the original predictors. The rescaled relative weight of a predictor can easily be transformed into the percentage of variance that is uniquely explained by this predictor when dividing the relative weight of the specific predictor by the total variance explained by all predictors in the regression model ( R 2 ). We performed the relative weight analyses in three steps. In Model 1, we included the different achievement motivation variables assessed in the respective domain in the analyses. In Model 2, we entered intelligence into the analyses in addition to the achievement motivation variables. In Model 3, we included prior school performance indicated by grades measured before testing in addition to all of the motivation variables and intelligence. For all three steps, we tested for whether all relative weight factors differed significantly from each other (see Johnson, 2004 ) to determine which motivational construct was most important in predicting academic achievement (RQ).

Descriptive Statistics and Intercorrelations

Table 1 shows means, standard deviations, and reliabilities. Tables 2 –4 show the correlations between all scales in school in general, in math, and in German. Of particular relevance here, are the correlations between the motivational constructs and students’ school grades. In all three domains (i.e., school in general/math/German), out of all motivational predictor variables, students’ ability self-concepts showed the strongest associations with subsequent grades ( r = 0.53/0.61/0.46; see Tables 2 –4 ). Except for students’ performance-avoidance goals (−0.04 ≤ r ≤ 0.07, p > 0.05), the other motivational constructs were also significantly related to school grades. Most of the respective correlations were evenly dispersed around a moderate effect size of | r | = 0.30.

Intercorrelations between all variables in school in general.

Intercorrelations between all variables in German.

Intercorrelations between all variables in math.

Relative Weight Analyses

Table 5 presents the results of the relative weight analyses. In Model 1 (only motivational variables) and Model 2 (motivation and intelligence), respectively, the overall explained variance was highest for math grades ( R 2 = 0.42 and R 2 = 0.42, respectively) followed by GPA ( R 2 = 0.30 and R 2 = 0.34, respectively) and grades in German ( R 2 = 0.26 and R 2 = 0.28, respectively). When prior school grades were additionally considered (Model 3) the largest amount of variance was explained in students’ GPA ( R 2 = 0.73), followed by grades in German ( R 2 = 0.59) and math ( R 2 = 0.57). In the following, we will describe the results of Model 3 for each domain in more detail.

Relative weights and percentages of explained criterion variance (%) for all motivational constructs (Model 1) plus intelligence (Model 2) plus prior school achievement (Model 3).

Beginning with the prediction of students’ GPA: In Model 3, students’ prior GPA explained more variance in subsequent GPA than all other predictor variables (68%). Students’ ability self-concept explained significantly less variance than prior GPA but still more than all other predictors that we considered (14%). The relative weights of students’ intelligence (5%), task values (2%), hope for success (4%), and fear of failure (3%) did not differ significantly from each other but were still significantly different from zero ( p < 0.05). The relative weights of students’ goal orientations were not significant in Model 3.

Turning to math grades: The findings of the relative weight analyses for the prediction of math grades differed slightly from the prediction of GPA. In Model 3, the relative weights of numerical intelligence (2%) and performance-approach goals (2%) in math were no longer different from zero ( p > 0.05); in Model 2 they were. Prior math grades explained the largest share of the unique variance in subsequent math grades (45%), followed by math self-concept (19%). The relative weights of students’ math task values (9%), learning goals (5%), work avoidance (7%), and hope for success (6%) did not differ significantly from each other. Students’ fear of failure in math explained the smallest amount of unique variance in their math grades (4%) but the relative weight of students’ fear of failure did not differ significantly from that of students’ hope for success, work avoidance, and learning goals. The relative weights of students’ performance-avoidance goals were not significant in Model 3.

Turning to German grades: In Model 3, students’ prior grade in German was the strongest predictor (64%), followed by German self-concept (10%). Students’ fear of failure in German (6%), their verbal intelligence (4%), task values (4%), learning goals (4%), and hope for success (4%) explained less variance in German grades and did not differ significantly from each other but were significantly different from zero ( p < 0.05). The relative weights of students’ performance goals and work avoidance were not significant in Model 3.

In the present studies, we aimed to investigate the relative importance of several achievement motivation constructs in predicting students’ academic achievement. We sought to overcome the limitations of previous research in this field by (1) considering several theoretically and empirically distinct motivational constructs, (2) students’ intelligence, and their prior achievement, and (3) by assessing all predictors at the same level of specificity as the achievement criteria. We applied sophisticated statistical procedures to investigate the relations in three different domains, namely school in general, math, and German.

Relative Importance of Achievement Motivation Constructs for Academic Achievement

Out of the motivational predictor variables, students’ ability self-concepts explained the largest amount of variance in their academic achievement across all sets of analyses and across all investigated domains. Even when intelligence and prior grades were controlled for, students’ ability self-concepts accounted for at least 10% of the variance in the criterion. The relative superiority of ability self-perceptions is in line with the available literature on this topic (e.g., Steinmayr and Spinath, 2009 ; Kriegbaum et al., 2015 ; Steinmayr et al., 2018 ) and with numerous studies that have investigated the relations between students’ self-concept and their achievement (e.g., Möller et al., 2009 ; Huang, 2011 ). Ability self-concepts showed even higher relative weights than the corresponding intelligence scores. Whereas some previous studies have suggested that self-concepts and intelligence are at least equally important when predicting students’ grades (e.g., Steinmayr and Spinath, 2009 ; Weber et al., 2013 ; Schneider et al., 2018 ), our findings indicate that it might be even more important to believe in own school-related abilities than to possess outstanding cognitive capacities to achieve good grades (see also Lotz et al., 2018 ). Such a conclusion was supported by the fact that we examined the relative importance of all predictor variables across three domains and at the same levels of specificity, thus maximizing criterion-related validity (see Baranik et al., 2010 ). This procedure represents a particular strength of our study and sets it apart from previous studies in the field (e.g., Steinmayr and Spinath, 2009 ). Alternatively, our findings could be attributed to the sample we investigated at least to some degree. The students examined in the present study were selected for the academic track in Germany, and this makes them rather homogeneous in their cognitive abilities. It is therefore plausible to assume that the restricted variance in intelligence scores decreased the respective criterion validities.

When all variables were assessed at the same level of specificity, the achievement motives hope for success and fear of failure were the second and third best motivational predictors of academic achievement and more important than in the study by Steinmayr and Spinath (2009) . This result underlines the original conceptualization of achievement motives as broad personal tendencies that energize approach or avoidance behavior across different contexts and situations ( Elliot, 2006 ). However, the explanatory power of achievement motives was higher in the more specific domains of math and German, thereby also supporting the suggestion made by Sparfeldt and Rost (2011) to conceptualize achievement motives more domain-specifically. Conceptually, achievement motives and ability self-concepts are closely related. Individuals who believe in their ability to succeed often show greater hope for success than fear of failure and vice versa ( Brunstein and Heckhausen, 2008 ). It is thus not surprising that the two constructs showed similar stability in their relative effects on academic achievement across the three investigated domains. Concerning the specific mechanisms through which students’ achievement motives and ability self-concepts affect their achievement, it seems that they elicit positive or negative valences in students, and these valences in turn serve as simple but meaningful triggers of (un)successful school-related behavior. The large and consistent effects for students’ ability self-concept and their hope for success in our study support recommendations from positive psychology that individuals think positively about the future and regularly provide affirmation to themselves by reminding themselves of their positive attributes ( Seligman and Csikszentmihalyi, 2000 ). Future studies could investigate mediation processes. Theoretically, it would make sense that achievement motives defined as broad personal tendencies affect academic achievement via expectancy beliefs like ability self-concepts (e.g., expectancy-value theory by Eccles and Wigfield, 2002 ; see also, Atkinson, 1957 ).

Although task values and learning goals did not contribute much toward explaining the variance in GPA, these two constructs became even more important for explaining variance in math and German grades. As Elliot (2006) pointed out in his hierarchical model of approach-avoidance motivation, achievement motives serve as basic motivational principles that energize behavior. However, they do not guide the precise direction of the energized behavior. Instead, goals and task values are commonly recruited to strategically guide this basic motivation toward concrete aims that address the underlying desire or concern. Our results are consistent with Elliot’s (2006) suggestions. Whereas basic achievement motives are equally important at abstract and specific achievement levels, task values and learning goals release their full explanatory power with increasing context-specificity as they affect students’ concrete actions in a given school subject. At this level of abstraction, task values and learning goals compete with more extrinsic forms of motivation, such as performance goals. Contrary to several studies in achievement-goal research, we did not demonstrate the importance of either performance-approach or performance-avoidance goals for academic achievement.

Whereas students’ ability self-concept showed a high relative importance above and beyond intelligence, with few exceptions, each of the remaining motivation constructs explained less than 5% of the variance in students’ academic achievement in the full model including intelligence measures. One might argue that the high relative importance of students’ ability self-concept is not surprising because students’ ability self-concepts more strongly depend on prior grades than the other motivation constructs. Prior grades represent performance feedback and enable achievement comparisons that are seen as the main determinants of students’ ability self-concepts (see Skaalvik and Skaalvik, 2002 ). However, we included students’ prior grades in the analyses and students’ ability self-concepts still were the most powerful predictors of academic achievement out of the achievement motivation constructs that were considered. It is thus reasonable to conclude that the high relative importance of students’ subjective beliefs about their abilities is not only due to the overlap of this believes with prior achievement.

Limitations and Suggestions for Further Research

Our study confirms and extends the extant work on the power of students’ ability self-concept net of other important motivation variables even when important methodological aspects are considered. Strength of the study is the simultaneous investigation of different achievement motivation constructs in different academic domains. Nevertheless, we restricted the range of motivation constructs to ability self-concepts, task values, goal orientations, and achievement motives. It might be interesting to replicate the findings with other motivation constructs such as academic self-efficacy ( Pajares, 2003 ), individual interest ( Renninger and Hidi, 2011 ), or autonomous versus controlled forms of motivation ( Ryan and Deci, 2000 ). However, these constructs are conceptually and/or empirically very closely related to the motivation constructs we considered (e.g., Eccles and Wigfield, 1995 ; Marsh et al., 2018 ). Thus, it might well be the case that we would find very similar results for self-efficacy instead of ability self-concept as one example.

A second limitation is that we only focused on linear relations between motivation and achievement using a variable-centered approach. Studies that considered different motivation constructs and used person-centered approaches revealed that motivation factors interact with each other and that there are different profiles of motivation that are differently related to students’ achievement (e.g., Conley, 2012 ; Schwinger et al., 2016 ). An important avenue for future studies on students’ motivation is to further investigate these interactions in different academic domains.

Another limitation that might suggest a potential avenue for future research is the fact that we used only grades as an indicator of academic achievement. Although, grades are of high practical relevance for the students, they do not necessarily indicate how much students have learned, how much they know and how creative they are in the respective domain (e.g., Walton and Spencer, 2009 ). Moreover, there is empirical evidence that the prediction of academic achievement differs according to the particular criterion that is chosen (e.g., Lotz et al., 2018 ). Using standardized test performance instead of grades might lead to different results.

Our study is also limited to 11th and 12th graders attending the highest academic track in Germany. More balanced samples are needed to generalize the findings. A recent study ( Ben-Eliyahu, 2019 ) that investigated the relations between different motivational constructs (i.e., goal orientations, expectancies, and task values) and self-regulated learning in university students revealed higher relations for gifted students than for typical students. This finding indicates that relations between different aspects of motivation might differ between academically selected samples and unselected samples.

Finally, despite the advantages of relative weight analyses, this procedure also has some shortcomings. Most important, it is based on manifest variables. Thus, differences in criterion validity might be due in part to differences in measurement error. However, we are not aware of a latent procedure that is comparable to relative weight analyses. It might be one goal for methodological research to overcome this shortcoming.

We conducted the present research to identify how different aspects of students’ motivation uniquely contribute to differences in students’ achievement. Our study demonstrated the relative importance of students’ ability self-concepts, their task values, learning goals, and achievement motives for students’ grades in different academic subjects above and beyond intelligence and prior achievement. Findings thus broaden our knowledge on the role of students’ motivation for academic achievement. Students’ ability self-concept turned out to be the most important motivational predictor of students’ grades above and beyond differences in their intelligence and prior grades, even when all predictors were assessed domain-specifically. Out of two students with similar intelligence scores, same prior achievement, and similar task values, goals and achievement motives in a domain, the student with a higher domain-specific ability self-concept will receive better school grades in the respective domain. Therefore, there is strong evidence that believing in own competencies is advantageous with respect to academic achievement. This finding shows once again that it is a promising approach to implement validated interventions aiming at enhancing students’ domain-specific ability-beliefs in school (see also Muenks et al., 2017 ; Steinmayr et al., 2018 ).

Data Availability

Ethics statement.

In Germany, institutional approval was not required by default at the time the study was conducted. That is, why we cannot provide a formal approval by the institutional ethics committee. We verify that the study is in accordance with established ethical guidelines. Participation was voluntarily and no deception took place. Before testing, we received informed consent forms from the parents of the students who were under the age of 18 on the day of the testing. If students did not want to participate, they could spend the testing time in their teacher’s room with an extra assignment. All students agreed to participate. We included this information also in the manuscript.

Author Contributions

RS conceived and supervised the study, curated the data, performed the formal analysis, investigated the results, developed the methodology, administered the project, and wrote, reviewed, and edited the manuscript. AW wrote, reviewed, and edited the manuscript. MS performed the formal analysis, and wrote, reviewed, and edited the manuscript. BS conceived the study, and wrote, reviewed, and edited the manuscript.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Funding. We acknowledge financial support by Deutsche Forschungsgemeinschaft and Technische Universität Dortmund/TU Dortmund University within the funding programme Open Access Publishing.

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20 of the most important academic skills you need for university

University is a place where students are expected to develop a set of academic skills that will help them succeed in their future careers. While it’s true that every university degree has its own unique set of requirements, there are some academic skills that are essential for success in any course. So if you’re wondering which are the most important academic skills to have at university, take a look at our list (as well as how to develop them).

1. Time management

Time management is arguably one of the most important academic skills that students must develop to be successful in university. Students are expected to juggle multiple courses, assignments, and extracurricular activities, not to mention completing everything on time. Meeting deadlines is critical to good grades, as you may be penalised for late assignments, such as capped grades. Therefore, if you work on time management, which includes setting priorities, creating a schedule, and breaking tasks down into smaller, manageable chunks, you’ll probably find everything a little easier.

2. Research skills

It might not seem like you need research skills unless you’re doing a science degree, but you’ll likely need them for a dissertation. From finding relevant sources to critically analysing them to synthesising information, research skills are important. Good research skills also involve knowing how to use different databases, search engines, and citation styles.

3. Writing skills

In addition to research, you’ll no doubt be writing up assignments at some point. So one of the most important skills for university is writing. It’s not simply putting pen to paper, or fingertips to keypad, but it’s the quality of what you write. You’ll need to write concisely, critically and with an academic tone. You’ll also need to be able to organise information into a logical and coherent structure, using evidence to support arguments.

4. Critical thinking skills

To analyse and evaluate information critically, students need to develop critical thinking skills. It involves questioning assumptions, evaluating evidence, and drawing conclusions based on evidence. Developing good critical thinking skills requires recognising biases and assumptions, considering alternative perspectives, and applying logic and reasoning to solve problems. According to the University of Essex , not only is critical thinking an important skill for uni, but the workplace too.

5. Communication

As you navigate through university, you’ll need to be able to interact with lecturers, classmates, flatmates and lots of other people. Strong communication skills involve not only the ability to express oneself clearly and concisely in both verbal and written formats but also active listening and collaboration with others. You’ll no doubt have group projects or have to work with others, so communication here is important. Here’s some tips from a Professor on how to email your lecturer the right way .

6. Study skills 

Knowing how to study, or revise, or cram, is a great tool to have – but it’s also individual. There might be a better time of day that suits you, or you might prefer to do bulk studying last minute. Some good tips on developing study skills involve setting goals, creating a study schedule, and using effective study strategies such as note-taking, summarising, and self-testing. Overall, finding what works for you is the best approach – just don’t avoid studying completely.

7. Digital literacy

One of the most important academic skills for university is digital literacy. In order to succeed academically, students must be proficient in using technology to access and assess information, collaborate with peers, and complete coursework. A lot of the information for classes are also online, on platforms like Moodle, so being able to navigate these will definitely be helpful. Don’t worry if tech isn’t your thing though, there will be lots of courses at your uni to help you out.

8. Problem-solving skills

Problem-solving skills are essential for university, but also for living alone for the first time. You’ll have to think for yourself a lot, which can be quite empowering. For your degree, being able to problem solve is also important as you’ll likely need to use it in assignments. They often involve identifying the problem, developing and implementing a solution, and evaluating the results.

9. Adaptability

Life at uni will throw all sorts of curveballs, so it’s good to demonstrate adaptability. These can be changes in courses, programmes, and the academic environment, as well as outside of uni. Being adaptable will help you navigate these, as well as being able to learn from failures, being open to new ideas and approaches, and being willing to take on new challenges.

10. Self-motivation

University is totally different from school and college. It’s a lot more independent, meaning you’ll have to keep yourself on track. But it’s generally a lot more fun too, as you’ll be learning about something that interests you for your future career. So you’ll need a lot of self-motivation, another important academic skill for university. You’ll need to able to motivate yourself to complete assignments and projects, and keeping your attendance levels high – even when you’ve got a hangover. Some tips to stay motivated include setting goals, breaking tasks down into smaller, manageable chunks, and rewarding accomplishments.

11. Active listening

Active listening involves giving full attention to the speaker, asking clarifying questions, and being able to summarise and reflect on what was said. It’s very easy to spend lectures day dreaming or planning you next night out, but it’s not going to help you get that essay written. An academic paper on active listening recommended tips, such as note taking, making associations and analogies, asking questions, integrating information, making inferences, attending on time, sitting at the front and so on.

12. Critical reading

The ability to critically read written materials is a fundamental academic skill that university students must acquire. Critical reading requires analysing and evaluating various forms of written material, such as textbooks, research articles, and other academic sources. Developing good critical reading skills involves comprehending the author’s intentions and arguments, identifying any biases or assumptions present in the text, and evaluating the credibility and quality of the evidence presented.

13. Presentation skills

Not every university course requires you to do presentations, but it’s likely that at some point in your career you’ll need to ‘present’ something. It can be a great boost of confidence to be able to speak to others about your work or idea. It also allows you to think about things more deeply, so you can explain them to others.  Presentation skills require students to communicate their ideas effectively in front of an audience, which means organising ideas and delivering the message clearly and confidently.

14. Teamwork

One of the most important academic skills for university and for life generally is working as a team. From group projects to sorting out bills in rented student houses, you’ll need to know how to work with others while at uni. Good teamwork skills involve effective communication, active listening, understanding and respecting diverse perspectives, and being able to contribute to the team’s goals.

15. Numeracy skills

Maths is definitely not everyone’s strong suit. But basic numeracy skills are important for students on courses that involve quantitative analysis, such as mathematics, science, and economics. But other subjects will also require a degree of numeracy skill, where you might need to use SPSS, Jamovi or other statistical software to analyse research. Usually, universities have workshops which will allow you to develop these skills with extra help, so don’t worry if numbers scare you!

16. Self-reflection

Self-reflection is an important academic skill for university that allows students to assess their own learning and development. It involves reflecting on your own strengths and weaknesses, identifying areas for improvement, and setting goals for personal growth. Journalling is a popular way of doing this, but you can also find other methods.

17. Emotional intelligence

Having high emotional intelligence can help you deal with the ups and downs of student life. University is exciting, but it can also be an emotional or anxious time. This is where emotional intelligence can help. Knowing how to manage your own emotions and understand the emotions of others is important, especially in emotionally charged situations.

18. Cultural competence

At university, you’ll likely be going to classes full of people with different backgrounds, ethnicities, cultures and perspectives. So having cultural competence is a requirement for uni. Cultural competence is a crucial academic skill that enables students to engage with people from diverse cultural backgrounds in an effective and respectful manner. It requires understanding and valuing different cultural norms, values, and beliefs, and the ability to communicate and collaborate effectively across cultural boundaries. It requires ongoing learning, self-reflection, and a commitment to challenging cultural biases and promoting diversity and inclusion.

19. Networking

To begin with, networking involves identifying and engaging with people who have relevant knowledge and expertise in the student’s field of study. It can help you find opportunities and really get involved in the field you want to develop a career in. You can start with talking to your tutors and attending university events, which will let you liaise with staff working in your industry.

20. Entrepreneurship

If you want to make it as a millionaire, start developing your entrepreneurial skills now! Entrepreneurship is an important academic skill that can make university even more interesting. You’ll need to develop creative thinking and innovation, and think about solving problems. If you want to read about how some entrepreneurs made their huge net worth, check out our article on Steven Bartlett .

Last Updated on March 20, 2024

Published on August 2, 2023

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Develop your academic skills

Tips, advice, and opportunities for academic skills development

Where to get help with your academic study skills

• Library Skills .
• Academic Communication Centre .
• Digital Skills Development .
• LinkedIn Learning UCL .

Develop the right skills for your future

It is a good idea to think about how the academic skills you are developing are setting you up to succeed in your future professions. UCL Careers has created a skills hub to help you d evelop the skills, strengths, and qualities employers are typically looking for.

Browse academic skills by subject-area

With your UCL username and password, you're able to access over 16,000 courses through LinkedIn Learning for free. 

Academic Writing 

Ucl writing support and resources .

• UCL Academic Communication Centre  offers tutorials, workshops, courses, webinars, writing retreats and asynchronous resources to support students across UCL with their writing.
• IOE Academic Writing Centre  provides tutorials, webinars and online resources to IOE students.
• Students’ Union UCL Language + Writing  peer-to-peer support for students with English as an additional language.
• UCL’s Survey of English Usage  produces apps on academic writing (free), spelling and punctuation (free) and grammar (various costs).
• UCL Student Disability Services  has produced some excellent guides on reading, note-taking, essay writing, revision techniques and time management.
• Academic Integrity  at UCL provides guidance on areas such as referencing conventions.
• UCL also has a licence for   LinkedIn Learning,  the online video training provider. LinkedIn Learning has several short courses on writing, such as writing in plain English.

External Writing Resources 

• Guide to writing essays, the Royal Literary Fund.
• Guide to writing dissertations, the Royal Literary Fund.
• How to write in Plain English,  the Plain English Campaign (pdf).
• Essay and Report Writing Skills Course, The Open University (free course).
• Writing What You Know , The Open University (free course).
• Writing in Plain English , LinkedIn Learning.

Digital Skills 

• Digital Education at UCL Moodle course , supporting you to be a successful digital learner.
• Digital Skills Development , UCL home page to book online and face-to-face courses.
• UCL DigiLearn , A library of online videos covering UCL IT essentials.
• Succeeding in a Digital World Course , The Open University (free course).

Presenting 

• How to give a good (enough) presentation , UCL.
• Creating accessible PowerPoint presentations , UCL Digital Skills Development.
• Talk the Talk , The Open University (free course).
• Delivery Tips for Speaking in Public , LinkedIn Learning.
• Giving a talk or making a presentation : study skills guide from UCL SSEES.
• Giving a presentation : UCL Institute of Archaeology study skills guide.

Finding information, referencing and Plagiarism

• Searching for information , Libraryskills@UCL.
• Evaluating information , Libraryskills@UCL.
• Kick-starting your literature review , UCL Digital Skills Development.
• References, citations, and avoiding plagiarism , UCL Libguides.
• Referencing and Plagiarism , UCL PDF.
• Reference Management Software , UCL Libguides.
• Academic Integrity  at UCL:  What is Academic Integrity, why is it important, and what happens if you breach it?
• UCL’s notetaking tips .
• UCL Notetaking Techniques Course .
• The Open University How to Take Notes Course .
• The Open University Effective Notetaking Course , LinkedIn Learning.

Critical thinking, reading and writing

• Critical Thinking , The Open University.
• Developing your Thinking Skills , The Open University.
• Critical Thinking, LinkedIn Learning.
• Critical Reading and Writing, UCL.
• How to be a Critical Reader , The Open University.
• Groups and Teamwork , The Open University.
• Working with Diverse Teams , The Open University.
• What's the difference between collaboration and collusion?  UCL Academic Integrity course.

Independent Learning 

• Independent research , Libraryskills@UCL.
• Improving your own learning and performance , The Open University.
• Personal Productivity , LinkedIn Learning UCL playlist.

Research Skills

• Short UCL courses on " Research Skills ".
• Free  research skills courses from the Open University.

Academic Skills: Definition, Examples, How To Improve Them

• By HIGH5 Content & Review Team
• August 31, 2023
• Professional skills

Achieving academic success requires more than just hard work – it involves strategically developing and applying a range of skills suited to your unique talents and abilities. These talents, known as strengths, can be identified through a comprehensive assessment like the HIGH5 test . The skills that allow students to capitalize on their strengths and excel academically are referred to as academic skills.

By taking the HIGH5 test and understanding your greatest strengths, you can prioritize honing the most relevant academic skills for your natural way of thinking and working. In this article, we will cover how you can seek out academic skills, attain them, and use these skills to your advantage in life.

What Are Academic Skills? Definition & Meaning

Academic skills are the traits and academic strategies that help you become a better student. They prepare you for your career, help you stay focused and motivated, get you exposed to new ways of thinking, and so much more. These skills are more than just innate, though.

Environment, such as parental motivation and asking kids difficult questions to broaden their horizons, plays a role. Learning strategies, studying strategies, and attention all help you absorb as much as possible at school. These tasks will translate into highly developed academic abilities.

Regardless of the particular skills, academic or study skills help you acquire good grades and may even help you enjoy school more. At times, academic and study abilities are categorized together, as they are intertwined. They are typically taught to high schoolers and college students but can be learned at any time.

If a skill helps you study efficiently, attain a desirable grade, stay focused, and retain information, it is a study skill. Such an essential skill is not only applicable to one field of study, too. An immense benefit of these abilities is their versatility and range of applicability.

Importance of Academic Skills for Students & Their Benefits

There are numerous benefits to using academic skills effectively. The key is to identify and capitalize on your unique strengths through a validated assessment like the HIGH5 test. For example, those with strong writing abilities can become more persuasive by leaning into their talent for verbal expression. Similarly, students gifted with curiosity and analytical thinking can leverage their natural research strengths to learn about the world and process information deeply. Taking the HIGH5 test provides personalized insights into your greatest skills, empowering you to strategically develop and apply them across academic pursuits.

In a more general sense, academic/study skills help students succeed in school and even in extracurricular activities. They can focus for longer, communicate better, attain higher test grades, remember more of their lectures, and so much more.

10 Benefits of Academic Skills

The following list will provide you with detailed benefits of boosting academic abilities:

• Increased ability to focus and get work done (increased time management skills)
• More enthusiasm and passion at school, especially when learning about a new topic
• Higher test grades from more efficient studying
• Being able to effectively communicate your problems with teachers so that they can assist you
• Greater ability to recall information and apply it to the real world
• An increased understanding of how you learn and the best ways to maximize study time
• Increased goal-planning skills and a more goal-oriented mindset
• A boost in your self-confidence and increased desirability to venture outside of your comfort zone
• Greater desirability to improve and more interest in new academic skill development
• More teamwork and stronger communication within those teams

12 Examples of Academic Skills

While some believe “academic” strategies and skills only apply to the scholarly world, this is not entirely accurate. Academic skills can also benefit individuals in the workplace.

In fact, one of the great benefits of learning such skills early on is the ability to transfer them to your lifelong career.

Many of the benefits one gains in school can also be transferred to their work. Below is a list of a few academic skills and the benefits they bring to your career.

Pro Tip From HIGH5 Maintaining focus and avoiding procrastination can be challenging for some, while others seem to naturally excel at time management. If this skill is one of your strengths identified by the HIGH5 test , build on it by experimenting with different productivity techniques like the Pomodoro method or personal kanban boards. However, if time management is not an innate strength, consider working with a coach or finding an accountability partner to systematically develop habits that compensate in this area.

1. Time management

When you are a student, managing your time translates toward maximizing your study time. However, time management in the workplace does not necessarily mean “working as much as possible.” It also involves prioritizing tasks, planning, setting goals, and much more.

As an employee, you will often have to meet deadlines. Managing time is crucial for that. To consistently meet your goals, you must also work with deadlines or quotas. The idea of working smarter , and not always harder, is included in effective time management.

You should learn about your distractions and which environments maximize your productivity. Schedules, reminders, timers, and planners can all help you build your time management abilities.

2. Research skills

When you think back to your secondary school years, specifically literacy class, what comes to mind? Likely, you will remember the long and arduous essays you had to write. Or, complex school projects may come to mind. Regardless, both of these tasks involve a high level of research if you wish to be successful.

Proper research involves finding credible sources, reading data, interpreting it, knowing the questions you need to answer, and understanding where to search for those answers. To effectively design a product, you may need to research development practices and regulations. You need to evaluate your place in the market, which involves research. Careers in journalism and medicine both benefit from this skill the most, though.

3. Reading comprehension

Undoubtedly, every worker will have to read instructions, script, or some other form of writing during the workday. The ability to truly understand this writing is known as reading comprehension.

Students require this ability to understand tasks, homework questions, tests, and project requirements, and perform research for tests as well as projects. You will continue using this skill after you graduate. Employees also need to clearly understand the directions given to them.

Written communication is also common, so this skill will be applied there as well. When gathering information online, you will need to use reading comprehension. If you want to boost your comprehension levels, consider reading more books, increasing your vocabulary, or searching for specific industry terms.

4. Computer skills

You may believe that computer skills are only necessary for coders and engineers, but this is not the case. In today’s digitalized world, knowing how to operate electronic devices is key to success. It can boost your productivity and help you research better. If you wish to create a schedule, send an email, or create a report or graph, you will need to utilize software and hardware.

Many industries rely on specific software to boost efficiency as well. For instance, Google Docs is used as opposed to paper document sharing. Or, marketing platforms such as Facebook Ads are utilized. Knowing some basic computer skills can truly benefit you in any career.

5. Self-discipline

There are ways to use extrinsic, or outside, motivation to your advantage. However, relying solely on others to motivate you is risky. You must also have self-motivation and intrinsic motivation . Similarly to time management, motivation can help you prioritize tasks and set clear goals.

You are also more inclined to achieve those goals if you are motivated. Many individuals have a natural tendency to procrastinate. Self-discipline will help you overcome this bad habit. Instead, you will focus on what truly matters and achieve goals, even without direct supervision. You can utilize management skills to boost motivation by creating schedules and due dates for yourself.

6. Critical thinking

Critical thinking is a universally needed trait. It helps you analyze information and creatively solve problems. With critical thinking, even complex problems and tasks are easier to understand. In virtually any workplace setting, you will encounter setbacks and hardships. During these moments, critical thinking is needed to overcome problems.

You can address inefficiency and mistakes by using critical thinking skills. Critical thought also breeds innovation and helps you maintain a competitive advantage over other firms and candidates. Mindfulness, industry-related knowledge, and speaking to mentors can boost your ability to think critically.

7. Group work

Even the most independent jobs require some level of group work and communication. As a student, you will need to participate in group projects. You may also need to discuss topics or assignments in group settings. If you know how to work with a group, many other skills will follow.

Teamwork leads to increased conflict resolution skills, better communication, increased collaboration skills, and being a better leader. Throughout your career, you may need to work with others in your department or even multiple departments at once. To improve your collaboration skills, you can try volunteering or participating in non-work-related group activities, such as team sports.

8. Presentation and public speaking skills

Students, employees, and employers alike will all need to give presentations. Public speaking abilities allow you to appear confident, calm your nerves, and effectively communicate a message.

They make you more persuasive and more likely to achieve your goals. Using proper body language, tone, communication style, word choice, and so on all contribute to being a charismatic public speaker.

By giving your audience appropriate visual aids and speaking assertively, you increase your authority and grab the audience’s attention. Take a public speaking class or ask your friends for public speaking feedback.

Writing skills are necessary for a diverse list of fields. You will become a better communicator, retain more information, take clear notes, instruct others clearly, and write quality reports if you increase your ability to write well.

While you may not need to write paper notes often, writing is still a vital skill. You will likely need to write emails, create memos, and report progress, all of which require strong writing abilities. To be informative and persuasive, you must understand how to be a good writer. It may even improve your leadership and collaboration skills. There are many guides you can access to improve your writing. Alternatively, you can also take a writing workshop.

10. Goal planning

There are many benefits that come from setting goals. You become more motivated, feel more engaged, stay productive,  and generally enjoy your job more with goals.

However, you cannot set the best goals without understanding goal planning. Having a specific goal-setting strategy will further increase your productivity and focus.

Once you understand how goals function, you can track your progress. You will understand which strategies are effective and the best ways to maximize your success.

There are many resources that can assist you in creating goals. Keep the acronym SMART in mind when setting a goal: specific, measurable, attainable, relevant, and time-bound.

11. Taking constructive criticism

Taking criticism personally is one way to self-sabotage your career. In school, you consistently get feedback from teachers and other peers.

This may be in the form of comments, or more commonly, through tests and direct communication with parents.

At work, you will likely have performance reviews or progress meetings. There, your supervisors will explain what you are and are not doing well.

If you see feedback as an opportunity to grow, then your ability to increase all of your skills is high. Your overall potential increases.

On the other hand, ignoring criticism robs you of the opportunity to develop your skills and improve.

Try to ask for feedback whenever possible, be an active listener, and avoid impulsive or emotional reactions to processing feedback.

12. Multitasking

Multitasking is a controversial skill. Some say it may decrease your productivity, while others believe the exact opposite.

However, there are ways to effectively leverage multitasking to your benefit. Multitasking is the ability to simultaneously perform multiple tasks.

While you are a student, this usually looks like working on two assignments at once. You may be listening to a lecture while also taking notes, for example.

As an employee, you will need to prioritize and organize tasks to maximize your productivity. Sometimes, this may mean working on two tasks at once.

On the web, you can find a plethora of information on multitasking techniques and how to develop them.

Be careful with using multitasking, though. If the quantity of output starts to decrease quality, it may be time to dud on each task individually.

How to Develop Academic Skills?

Developing academic skills begins with dedication and a customized approach based on your unique strengths profile. Before creating schedules and plans, take the HIGH5 strengths assessment to gain insights into your greatest talents. Then, structure your skill development strategies around leaning into those strengths.

For example, if discipline and focus are strengths, build habits like timeboxing your most crucial tasks each day. However, if strengths like creativity and cognitive risk-taking are more natural, experiment with unstructured learning through immersive projects. Tailoring your approach allows you to develop skills while working from a motivating strengths-based mindset.

Additionally, being someone with strong academic abilities requires a passion for knowledge-seeking and learning. You should be willing to constantly seek out information on how to improve yourself and learn more about your field. One way to do this is to ask for feedback from teachers, colleagues, or bosses. If they have any productivity reports, ask them to see the data.

They may also give you general advice on what to work on. Do not take this personally. Rather, see it as an opportunity to grow and learn new skills. Finally, you should also acquire a few technical skills in addition to communication abilities. Communication is necessary for virtually any field. You will be more productive with this ability. Make yourself available as a team player. If someone needs help, step in and offer assistance.

When working in a team, ensure you play a crucial role and help propel your group to success. When it comes to technical skills, experience is the best way to learn. Writing, for instance, is a technical skill. You can become a better writer by reading other texts, expanding your vocabulary, and attending workshops.

Computer skills are also learned through experience. Experiment with new software when generating schedules or presentations. Consider taking a computer course in school, if possible.

Pro Tip From HIGH5 When improving skills that don’t rely on your strongest talents, use your HIGH5 strengths profile to determine supportive habits. For instance, if public speaking isn’t a strength but relationship-building is, join groups where you can practice presenting among trusted peers first. Or if attention to detail isn’t innate but you have high achievement motivation, use checklists and peer reviews to sharpen your precision. The strengths-based approach provides a roadmap for strategically developing new skills from your motivational sweet spot.

How to Improve Academic Skills?

Before you can improve your skills, you must track them. Understand your baseline skill levels. To do this, you can keep track of them by yourself. For productivity, measure how many projects you finish weekly or how many homework assignments you finish in a quarter.

In terms of communication, you can track the percentage of emails you respond to or how many group projects you volunteer for. Doing so will give you a clear understanding of your current skills. Then, you should seek feedback. Make yourself available to others whenever possible if your goal is a communicator.

Eliminating distractions and setting clear goals should help you improve any academic ability, whether it is a dedication to studying or improving your presentation skills . When you ask for feedback, ensure you get as much information as possible. If you ask a teacher or mentor, follow up by requesting details on how they themselves improved the skill you are focusing on. Through dedication, clear goal setting, and mentor support, you can improve any skill.

Academic Skills for Resumes & How To Add Them

Since academic skills often translate to skills in the workplace, you should include them on your resume. These skills can clearly show employees you have a track record of being a communicator, leader, critical thinker, and so on. By highlighting these skills, you can highlight the best qualities about you as an employee. Thus, the employer may be more attracted to hiring you.

Some skills, however, are more crucial than others. To determine which skills are most important to insert, consider the job and industry you are interested in. Look through the job description and even the employer description. Do they mention any skills directly? See if they allude to any skills as well, such as stating the company values hard work in the employer description.

Then, take a look at the task list that is written in the job description. Think about which academic skills could help you perform those tasks efficiently.

Related: 33 Teacher Interview Questions & How To Prepare for an Interview

If a task is similar to tasks you performed at school, recall which skills you used to perform the task well. For example, if the job lists “group work/projects” as one of your weekly tasks, consider how you collaborated and worked in teams at school. Collaboration, communication, and leadership likely helped you perform the task well at school. Then, these tasks are the best tasks to list on your resume.

Related: 23 Preschool Teacher Interview Questions with Answers

Frequently Asked Questions About Academic Skills

What are the 5 academic skills.

A few skills are universally regarded as important. They include time management, critical thinking, cooperation, technical skills, and motivation. All of these skills will benefit you during school, college, and beyond. Even after you are no longer involved in school, these skills continue to give you an advantage over other individuals.

What are academic skills for university?

In university, you should have strong writing, reading, mathematical, and computer skills. You should be able to clearly process information and retain knowledge. Additionally, time management remains a crucial skill. Prioritizing your tasks and working hard is key to being productive. Finally, being a team player and leader will help you stand out as a particularly dedicated student and will benefit your academic career.

Related: 22 Teaching Assistant Job Interview Questions & Sample Answers

What are the most important academic skills?

If you need to focus on a skill, the following skills are good choices regardless of which industry you plan to enter: time management, leadership, dedication, motivation, communication, critical thinking, and researching. All of them will help you stay productive, increase your value to a team, and make your work more enjoyable.

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5 Strategies for Academic Success: Using Your Strengths

These five tips show you how to keep a clear head and have a successful semester.

Rebecca Bakken

The start of the semester can be a hectic time. You’re juggling your career, classes, family, and friends. Deb Levy , a certified life and business coach, and a Harvard Extension career workshop leader, offers five tips in this video to help you succeed in your coursework.

Know your strengths.

It’s human nature to want to correct weaknesses. But knowing your strengths and how to use them effectively can have a much more substantial effect on success and well-being. So how can you reframe your thinking?

According to Deb Levy, the field of positive psychology offers many useful tools. One in particular—the Character Strengths Test from VIA Institute on Character—can help you gauge your strengths and weaknesses. The test ranks users’ character strengths from strongest to weakest, allowing for an objective view into where you excel and where you may need work.

Once you know what your strengths are, you can play to them. But it’s also important to know that sometimes strengths need to be tempered.

“Every strength if overused becomes a deficit,” says Levy.

For instance, someone who ranks highly in humor might run the risk of making an insensitive or inappropriate comment that could damage relationships.

Making a plan to bolster weaknesses while remaining conscious of strengths can be a great strategy to ensure not just academic success, but personal fulfillment.

Set specific goals.

Achieving your goals depends heavily on how well you can manage your time. Levy recommends making a priority pie that maps out how you’ll divide your time over the course of a semester.

“When you say yes to becoming a student, you have to say no to other things,” she says. “So goal-setting requires a strategic plan for the semester. Students who do better in general are the ones who take time to plan.”

Your priority pie should reflect all your personal, professional, and academic endeavors. For example:

Your priority pie should include not just classes and your work day, but also time for family, studying and homework, and self-care like going to the gym or getting a regular massage.

Levy stresses that the best goals are specific, personal, and flexible.

Prioritize happiness.

Feeling good about what you’re doing and why you’re doing it is the best way to ensure success. According to Levy, happiness often leads to success, but success on its own may not lead to happiness.

As such, prioritizing your own wellness is key to reaching your goals. Levy says well-being  consists of positive emotions, engagement, meaning, and achievement.

“By nature of being in school people are already prioritizing well-being. They’re getting engaged, working on accomplishments,” says Levy.

Read our blog post on work-life balance

Aside from making time for yourself, you can practice building positivity.

One exercise that Levy recommends is writing down three good things at the end of each day. These can be things you’re proud of, things you’re grateful for, or things that simply bring a smile to your face.

Studying subjects that give your life purpose or meaning can also be beneficial.

“People who connect meaning to their goals are more motivated,” says Levy

Be resilient.

Even with a good plan, obstacles will arise. How well you deal with those obstacles depends on your perspective.

In resilience coaching, Levy often refers to the work of psychologist Carol Dweck. Her research identifies two basic mindsets: fixed and growth. Fixed mindsets view mistakes or setbacks as insurmountable. Growth mindsets view them as opportunities for positive change.

If you lean toward a fixed mindset, the good news is that it’s not permanent. No one falls into one mindset 100 percent of the time. Training your brain to see opportunity where you once saw a roadblock is possible.

“Give yourself permission to be human,” Levy says. “Predict you’re going to make mistakes.”

One way to build resilience is by preparing for obstacles with implementation intentions , which are if–then plans designed to help people achieve goals. For example, “If I can’t get the financial aid I need, then I will reallocate money from my vacation or entertainment budgets.”

Setting these intentions gives you a default answer that helps you stick to your plan without having to deliberate or make a snap decision.

Have questions? Contact our Enrollment Services team

Make time to recover.

Rather than avoiding stress altogether, Levy recommends setting aside time to mentally and physically recover.

As a student, you may sometimes fall into a “stretch zone,” where you’re extending yourself to accommodate for different obligations. Periods of stress can actually be positive and motivating if they expand your perception of what’s possible.

But it can lead to chronic stress when you don’t build in time to recover.

Viewing your eight hours of sleep every night as sacrosanct can go a long way toward staving off chronic stress. So before you pull another all-nighter, think about the effects it may have on you the next day.

Taking breaks, setting aside time for meals, and enjoying recreation can help fuel you and keep you on course to achieve your goals.

For more information from Deb Levy on balancing academics with life, check out How to Set Goals and Achieve Balance—In and Outside the Classroom .

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• What Are The 6 Essential Skills For University Students?

Last Updated: 30th June 2021

Author: Rob Needleman

Table of Contents

During your time at university, you will develop valuable, transferable study skills that will support your learning, testing and future career.

Attending a university is an exciting time for students to live independently away from home and to further develop their academic skills from studying at school. The huge step-up from your final years of school makes developing your academic skills mandatory to stay on track and become a successful, high achieving student.

You will develop the skills during your time at university but building a solid foundation now will make the transition from school to higher education much smoother. The graphic below shows the skills we cover in this article. Read on to learn the skills that will help you thrive instead of survive at university. 

Academic Writing Skills

At university, academic writing is a skill students use each day. A must for all degrees is a strong grasp of the English language (international students or not). Being able to write to a good standard is key for coursework assignments such as dissertations and lab reports as well as during exams, answering longer written answers and essay questions.

You are expected to build on what you learnt at A-levels where instead of outlining a point, you have to be able to argue it using appropriate formal language matching the writing style of academic research. If spelling and grammar is an issue for you, it is time to put the work in before you start your degree as lecturers will not appreciate reading an essay that is full of grammatical errors and misspelt words.

You will also be expected to know how to structure your essays   or at least learn how to early on. Your essay content might be unbelievable, but if you cannot present your arguments in a clear and logical way, then you are likely to lose marks.

Referencing and Plagiarism

Two words students fear at the start and learn to manage throughout their studies. When discussing research by other authors, you must acknowledge their work through referencing. This will demonstrate to the reader and/or examiner the quality of your sources and the depth of your research and referencing will also allow the reader to visit the original sources for the complete research. You will come across multiple referencing styles throughout university such as Harvard, MLA, APA etc. but you will probably focus on one main style.  

Plagiarism is something you’ll get used to quickly and have to get used to quickly. There is no copy and pasting information directly into your writing anymore. Paraphrasing is also not enough to avoid plagiarism too, you must always reference the material you used. The same goes with collaborating with students and writing the same or very similar content as your friends. Universities now use software that will inform you and the examiner of the similarity that your writing has with other sources, such as fellow students, research papers and website content like blog posts. You will lose significant marks if you get caught and you will end up in a not so friendly meeting with university staff.

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Critical Thinking Skills

Critical thinking is a skill defined by thinking clearly, rationally and being able to recognise and understand good arguments and then create an assessment from the evidence presented to you. Most students find it difficult at first to initially criticise the experts in the field such as authors of ground-breaking research or even their lecturers. However, this is not being disrespectful or rude, this is essential as long as you back up your arguments with solid and explained evidence. 

Likewise, during your own research, you must be able to think critically about your own work. Ask yourself questions like: did I have a large enough sample size, was I unconsciously biased and am I interpreting my data correctly?

An example of critical thinking is identifying biases . This is a tricky skill but vital for research and incredibly transferable. A sign of a good critical thinker is being able to evaluate information objectively. Setting aside your own personal biases is not easy and identifying the biases from other parties is hard too, but it is necessary to understand different viewpoints. 

Time management Skills

“Prior Proper Planning Prevents Poor Performance”, you’ve likely heard this before but it is completely true. Effective time management is essential for university and it is something that will stay with you when you graduate. 

Time will become very valuable when lectures begin and the assignments start piling up. The way to cope with less time and a larger workload is through managing your time more effectively. It is completely normal to become overwhelmed when you first start university. Do not worry if you find this, it is now the time to start implementing time management strategies to stay on track and prevent yourself from becoming overly stressed.

Our advice is to plan ahead and make sure you are completely aware of deadlines. The key to planning ahead is to be realistic. You will hear stories from coursemates that declare that they can finish a 3,000-word essay the night before the due date and will start revising the morning of the exam. This might be true for some rare students but mostly this is rubbish. Give yourself plenty of time to finish each assignment to a high level and do not set yourself up for failure. Having one month to write an essay does not mean you need to spend a month doing it or then writing it the week before the due date, plan the time for it properly. 

Prioritising will help you greatly. We found the Eisenhower Matrix useful at university and we will work through an example together:

Use of the most important tasks (MITs) will help you significantly. The MIT will be your main focus that day and you will not shift your focus from it unless it is completely necessary. An MIT at university may be to create and practise a presentation to present to your coursemates next week. You will focus solely on creating and preparing for the presentation and park your lab report that is not due in for 2 weeks.

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Reading skills

Like writing, reading will dominate your time at university.

It is important to develop effective reading techniques to improve your speed and to choose the right content to read. When finding reading materials, as part of your active academic reading, there are questions to ask yourself to determine if it is relevant to you:

• Why am I reading this?
• Which sections will be valuable for me?
• How will I benefit from reading this?
• Start Wider Reading with our comprehensive reading lists

There are also different approaches to academic reading depending on the medium, for example, a blog on the qualities of a good doctor or an academic paper on the most effective approaches to cognitive diagnosis. Aston University suggests the following reading techniques: 

Skimming, Scanning and Critical Reading:

Skimming entails looking through text to create a general impression of the content. When skim reading, the reader does not read every word or a paragraph in-depth. Instead, the reader skims the introduction and conclusion of a book, the abstract of a paper and the opening and closing paragraph of a chapter. The aim is to form an impression and then decide if it is worth reading on in more depth.

Scanning is all about looking for a particular piece of information such as data to support or disprove your hypothesis. Whilst scanning, you ignore the content that is not relevant to you and you keep your goal of finding a particular piece of information in the forefront of your mind. This will help the words or images stand out when you run your eyes across the page. Like skimming, this technique will support your decision making of reading the text in-depth or choosing a different text to look through.

Personally, we found skim reading and scanning particularly important when trawling through hundreds of papers for our literature review dissertations in final year. It saved hours of reading less relevant information and the more we used this technique, the faster and more effective we became, so practising frequently will save you a lot of time when you start your own degree.

Critical reading, similar to critical thinking is ensuring you continually analyse, question and evaluate the information in front of you. The Open University  list some useful questions to ask yourself whilst reviewing a text:

• Who is speaking or writing?
• What is their point of view or perspective?
• What ideas and information are presented and how were they obtained?
• Are there unsupported assertions?
• Is the method used to find the evidence sound?
• Is the evidence correct or valid?
• What is fact and what is opinion?
• Are there unreasonable generalisations?
• Is the conclusion reasonable?
• What other perspectives or points of view could there be?

Note-taking skills

You must take notes during tutorials and lectures. The lecturers will provide useful information that will be essential when it comes to exam revision. Some lecturers will speak quickly so try to write very brief notes on what they are saying rather than fall behind writing everything they say. After a lecture has finished, add any comments and fill any gaps in your notes from the presentation slides posted online so that your notes are ready to be used for revision.

Communication Skills

Your student life will not just be reading and writing. University studies will also develop your communication skills. There will be many opportunities for working in teams, a great transferable skill that will look great on your CV. This can occur in group presentations, group projects and lab work. Hopefully, you will also have the opportunity to practice public speaking as we did each year. 

From day one of first year, you will be conversing with senior academics which you may find intimidating. They are experts in the field you are interested in so use the opportunity to ask questions and discuss aspects of your degree, or something you learnt from wider reading that you found fascinating. Make sure you go to your tutorials or supervisions prepared with the work set by tutors, but also with any extra questions you may have.

Attending university will open many doors for you, especially if you are proactive. One of the best ways of doing this is through networking. You will develop strong working and social relationships with your coursemates which is brilliant, but do not overlook the opportunities you have from the senior academics at the university. They themselves will have a bountiful supply of contacts, whether this is for help with your thesis, to gain some data or quotes, or to aid your job searching strategy. 

The key to effective networking is being a good listener, being confident, preparing what you might say and then following up properly after speaking to someone. We are not suggesting leaving business cards with the Economics Senior Lecturer, but asking to connect on LinkedIn and emailing them 48-72 hours after meeting them with an engaging email will go a long way.

Less academic skills and other Soft Skills

We have already mentioned some soft skills in this article such as communication and time management but in this section, we will focus on the less academic skills which are still important for university and life after graduation. 

A crucial skill is being able to budget and manage your finances effectively. Our number one tip is to make use of spreadsheets. They are not the most exciting way to spend your time but very helpful at keeping track of your spending. Like with time management, the key is to be realistic. Spending will be more than you probably expect and your location will affect this. Consider everything from rent to shopping and from drinks on nights out, to textbooks and stationery. Make sure you have a weekly limit on how much you can spend and try to follow this.

Living costs vary across the UK and it is something that catches a lot of students out. You can budget for university, but if you do not budget for the area you will be living in, this can make for a nasty surprise. For example, using the ‘metric’ of a cost of a pint of beer, in Lancaster, a pint can cost around £2.80 but in London, you can expect from £5.20 upwards. Accommodation tends to differ in price across universities so make sure the accommodation is within your budget. You can see the variation in prices in the table below:

Cooking and home skills sound rather strange whilst discussing academic skills but they will be a large part of your time away from studies. Each one of us at UniAdmissions has met a student who did not know how to use a washing machine or couldn’t open a tin of beans, you’ll meet these students too. Learn some staple recipes that are easy to master, such as spaghetti Bolognese and chilli con carne at home before you leave for university. Nutrition goes hand in hand with effective learning and studying, support your academic life by eating properly each day.  

Lastly, self-motivation is a constant theme at university. It will become apparent on a sunny Saturday afternoon when you have two essays due the following week, 5,000 words to write and then you receive a text asking if you would like to go to the beach or play football in the park. 

University life is unstructured which makes motivation important to keep yourself on track and to avoid falling into the cycle of trying to catch up each week. As we discussed in time management, having a good plan will help you stay focused on your goals. Sometimes, setting yourself up in the library away from distractions will help avoid the temptations of a sunny afternoon. Finally, make sure you build in time for leisure activities and reward your hard work!

Final Words

We have covered the essential skills for university including academic reading and time management. You have time to start working on these skills now before you start your degree, to make your transition from school to university much smoother. Your time at university will be great fun but make sure you use the opportunities around you to open every door possible and leave as the best graduate you can be.

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What you need to know about higher education

UNESCO, as the only United Nations agency with a mandate in higher education, works with countries to ensure all students have equal opportunities to access and complete good quality higher education with internationally recognized qualifications. It places special focus on developing countries, notably Africa. 

Why does higher education matter?  

Higher education is a rich cultural and scientific asset which enables personal development and promotes economic, technological and social change. It promotes the exchange of knowledge, research and innovation and equips students with the skills needed to meet ever changing labour markets. For students in vulnerable circumstances, it is a passport to economic security and a stable future. 

What is the current situation? 

Higher education has changed dramatically over the past decades with increasing enrolment, student mobility, diversity of provision, research dynamics and technology. Some 254 million students are enrolled in universities around the world – a number that has more than doubled in the last 20 years and is set to expand. Yet despite the boom in demand, the overall enrolment ratio is 42% with large differences between countries and regions. More than 6.4 million students are pursuing their further education abroad. And among the world’s more than 82 million refugees, only 7% of eligible youth are enrolled in higher education, whereas comparative figures for primary and secondary education are 68% and 34%, respectively ( UNHCR) . The COVID-19 pandemic further disrupted the way higher education was provided.

What does UNESCO do to ensure access for everyone to higher education? 

UNESCO's work is aligned with Target 4.3 of SDG 4 which aims, by 2030, “to ensure equal access for all women and men to affordable quality technical, vocational and tertiary education, including university”. To achieve this, UNESCO supports countries by providing knowledge, evidence-based information and technical assistance in the development of higher education systems and policies based on the equal distribution of opportunities for all students. 

UNESCO supports countries to enhance recognition, mobility and inter-university cooperation through the ratification and implementation of the Global Convention on the Recognition of Qualifications concerning Higher Education and regional recognition conventions . To tackle the low rate of refugee youth in higher education UNESCO has developed the UNESCO Qualifications Passport for Refugees and Vulnerable Migrants , a tool which makes it easier for those groups with qualifications to move between countries. The passport brings together information on educational and other qualifications, language, work history. UNESCO places a special focus on Africa with projects such as the Higher Technical Education in Africa project for a technical and innovative workforce supported by China Funds-in-Trust.  

​​​​​​​How does UNESCO ensure the quality of higher education? 

The explosion in demand for higher education and increasing internationalization means UNESCO is expanding its work on quality assurance, helping Member States countries to establish their own agencies and mechanisms to enhance quality and develop policies particularly in developing countries and based on the Conventions. Such bodies are absent in many countries, making learners more vulnerable to exploitative providers.  

It also facilitates the sharing of good practices and innovative approaches to widen inclusion in higher education. As part of this work, it collaborates with the International Association of Universities to produce the World Higher Education Database which provides information on higher education systems, credentials and institutions worldwide. 

​​​​​​​How does UNESCO keep pace with digital change?  

The expansion of connectivity worldwide has boosted the growth of online and blended learning, and revealed the importance of digital services, such as Artificial Intelligence, Big Data and Higher Education Management Information Systems in helping higher education institutions utilize data for better planning, financing and quality. 

The COVID-19 pandemic has accelerated this transformation and increased the number of providers and the range of degree offerings from cross-border to offshore education. The Organization provides technical support and policy advice on innovative approaches to widening access and inclusion including through the use of ICTs and by developing new types of learning opportunities both on-campus and online. 

How does UNESCO address the needs of a changing job market?

Labour markets are experiencing rapid changes, with increased digitization and greening of economies, but also the rising internationalization of higher education. UNESCO places a strong emphasis on developing science, technology, engineering and mathematics (STEM) education, indispensable to sustainable development and innovation. It aims to strengthen skills development for youth and adults, particularly literacy, TVET, STEM and higher education to meet individual, labour market and societal demands.  

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