a systematic literature review on internet of things in education benefits and challenges

• DOI: 10.1111/jcal.12383
• Corpus ID: 209070400

A systematic literature review on Internet of things in education: Benefits and challenges

• M. Kassab , J. Defranco , P. Laplante
• Published in Journal of Computer Assisted… 1 April 2020
• Computer Science, Education

110 Citations

Transforming education with the internet of things: a journey into smarter learning environments.

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Investigating the impact of IoT-Based smart laboratories on students’ academic performance in higher education

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Journal of Applied Research in Higher Education

ISSN : 2050-7003

Article publication date: 16 January 2024

The Internet of things (IoT), an emerging research field, offers solutions to several problems and may result in a paradigm shift in various areas, including education. However, this approach has been under-utilised. Therefore, this research investigates and highlights the primary factors that influence the impact of the IoT on education and reveals the current state of academic research to manage higher education (HE) resources effectively and efficiently.

Design/methodology/approach

Data from 35 academic papers were collected and analysed to understand the current situation and assess the readiness of HE to adopt IoT. A literature review is a well-established method for developing knowledge and interpreting issues under consideration. This study systematically analysed the various research methodologies used to adopt IoT, summarising the content of the studies and highlighting the main factors that may affect IoT adoption in HE.

The authors examined 95 papers; 35 were investigated and analysed. The literature review and analysis of academic papers revealed the factors influencing the adoption of IoT technology in HE.

Originality/value

By examining the evidence, this study contributes to understanding the context and supplements existing research. It conducts a systematic literature review to assess the impact of the IoT on the educational process, proposes future research directions and presents findings that aid the efficient management of HE resources.

• Internet of things (IoT)
• Higher education (HE)
• Smart campus
• Smart university
• Digital transformation
• Smart education
• Systematic literature review

Acknowledgements

This article was financially supported by the State Research Agency of the Spanish Ministry of Science and Innovation (MCIN/AEI/10.13039/50110 0 011033), via the SPUR project (ref. PID2020-117021GB-I00).

Kandil, O. , Rosillo, R. , Abd El Aziz, R. and De La Fuente, D. (2024), "Investigating the impact of the Internet of Things on higher education: a systematic literature review", Journal of Applied Research in Higher Education , Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/JARHE-05-2023-0223

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Internet of Things in Education: Opportunities and Challenges

• Conference paper
• First Online: 11 July 2023
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• Krešimir Rakić   ORCID: orcid.org/0000-0003-3447-6253 7  

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1827))

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• International Conference on Digital Transformation in Education and Artificial Intelligence Application

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The basic concept of Internet of Things is the ability to upgrade everyday objects with identification, sensor, network, and processing capabilities that will enable them to communicate with each other, as well as with other devices and services via the Internet. Improved in this way, these objects become smart objects, because they require minimal or even no human intervention to generate, exchange, collect, analyze, and manage data. The numerous possibilities of IoT provide great potential for its application in various areas of human life. In this paper, a comprehensive review of IoT implementation research is given, with a special emphasis on its application in education. The opportunities and advantages that IoT provides to educational institutions and all stakeholders in the learning and teaching process are listed and categorized. Challenges that institutions face when introducing IoT in their daily work are also listed, as well as suggestions for possible solutions for each of the challenges.

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Rakić, K. (2023). Internet of Things in Education: Opportunities and Challenges. In: Vasić, D., Kundid Vasić, M. (eds) Digital Transformation in Education and Artificial Intelligence Application. MoStart 2023. Communications in Computer and Information Science, vol 1827. Springer, Cham. https://doi.org/10.1007/978-3-031-36833-2_8

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Impacts of digital technologies on education and factors influencing schools' digital capacity and transformation: A literature review

Stella timotheou.

1 CYENS Center of Excellence & Cyprus University of Technology (Cyprus Interaction Lab), Cyprus, CYENS Center of Excellence & Cyprus University of Technology, Nicosia-Limassol, Cyprus

Ourania Miliou

Yiannis dimitriadis.

2 Universidad de Valladolid (UVA), Spain, Valladolid, Spain

Sara Villagrá Sobrino

Nikoleta giannoutsou, romina cachia.

3 JRC - Joint Research Centre of the European Commission, Seville, Spain

Alejandra Martínez Monés

Andri ioannou, associated data.

Data sharing not applicable to this article as no datasets were generated or analysed during the current study.

Digital technologies have brought changes to the nature and scope of education and led education systems worldwide to adopt strategies and policies for ICT integration. The latter brought about issues regarding the quality of teaching and learning with ICTs, especially concerning the understanding, adaptation, and design of the education systems in accordance with current technological trends. These issues were emphasized during the recent COVID-19 pandemic that accelerated the use of digital technologies in education, generating questions regarding digitalization in schools. Specifically, many schools demonstrated a lack of experience and low digital capacity, which resulted in widening gaps, inequalities, and learning losses. Such results have engendered the need for schools to learn and build upon the experience to enhance their digital capacity and preparedness, increase their digitalization levels, and achieve a successful digital transformation. Given that the integration of digital technologies is a complex and continuous process that impacts different actors within the school ecosystem, there is a need to show how these impacts are interconnected and identify the factors that can encourage an effective and efficient change in the school environments. For this purpose, we conducted a non-systematic literature review. The results of the literature review were organized thematically based on the evidence presented about the impact of digital technology on education and the factors that affect the schools’ digital capacity and digital transformation. The findings suggest that ICT integration in schools impacts more than just students’ performance; it affects several other school-related aspects and stakeholders, too. Furthermore, various factors affect the impact of digital technologies on education. These factors are interconnected and play a vital role in the digital transformation process. The study results shed light on how ICTs can positively contribute to the digital transformation of schools and which factors should be considered for schools to achieve effective and efficient change.

Introduction

Digital technologies have brought changes to the nature and scope of education. Versatile and disruptive technological innovations, such as smart devices, the Internet of Things (IoT), artificial intelligence (AI), augmented reality (AR) and virtual reality (VR), blockchain, and software applications have opened up new opportunities for advancing teaching and learning (Gaol & Prasolova-Førland, 2021 ; OECD, 2021 ). Hence, in recent years, education systems worldwide have increased their investment in the integration of information and communication technology (ICT) (Fernández-Gutiérrez et al., 2020 ; Lawrence & Tar, 2018 ) and prioritized their educational agendas to adapt strategies or policies around ICT integration (European Commission, 2019 ). The latter brought about issues regarding the quality of teaching and learning with ICTs (Bates, 2015 ), especially concerning the understanding, adaptation, and design of education systems in accordance with current technological trends (Balyer & Öz, 2018 ). Studies have shown that despite the investment made in the integration of technology in schools, the results have not been promising, and the intended outcomes have not yet been achieved (Delgado et al., 2015 ; Lawrence & Tar, 2018 ). These issues were exacerbated during the COVID-19 pandemic, which forced teaching across education levels to move online (Daniel, 2020 ). Online teaching accelerated the use of digital technologies generating questions regarding the process, the nature, the extent, and the effectiveness of digitalization in schools (Cachia et al., 2021 ; König et al., 2020 ). Specifically, many schools demonstrated a lack of experience and low digital capacity, which resulted in widening gaps, inequalities, and learning losses (Blaskó et al., 2021 ; Di Pietro et al, 2020 ). Such results have engendered the need for schools to learn and build upon the experience in order to enhance their digital capacity (European Commission, 2020 ) and increase their digitalization levels (Costa et al., 2021 ). Digitalization offers possibilities for fundamental improvement in schools (OECD, 2021 ; Rott & Marouane, 2018 ) and touches many aspects of a school’s development (Delcker & Ifenthaler, 2021 ) . However, it is a complex process that requires large-scale transformative changes beyond the technical aspects of technology and infrastructure (Pettersson, 2021 ). Namely, digitalization refers to “ a series of deep and coordinated culture, workforce, and technology shifts and operating models ” (Brooks & McCormack, 2020 , p. 3) that brings cultural, organizational, and operational change through the integration of digital technologies (JISC, 2020 ). A successful digital transformation requires that schools increase their digital capacity levels, establishing the necessary “ culture, policies, infrastructure as well as digital competence of students and staff to support the effective integration of technology in teaching and learning practices ” (Costa et al, 2021 , p.163).

Given that the integration of digital technologies is a complex and continuous process that impacts different actors within the school ecosystem (Eng, 2005 ), there is a need to show how the different elements of the impact are interconnected and to identify the factors that can encourage an effective and efficient change in the school environment. To address the issues outlined above, we formulated the following research questions:

a) What is the impact of digital technologies on education?

b) Which factors might affect a school’s digital capacity and transformation?

In the present investigation, we conducted a non-systematic literature review of publications pertaining to the impact of digital technologies on education and the factors that affect a school’s digital capacity and transformation. The results of the literature review were organized thematically based on the evidence presented about the impact of digital technology on education and the factors which affect the schools’ digital capacity and digital transformation.

Methodology

The non-systematic literature review presented herein covers the main theories and research published over the past 17 years on the topic. It is based on meta-analyses and review papers found in scholarly, peer-reviewed content databases and other key studies and reports related to the concepts studied (e.g., digitalization, digital capacity) from professional and international bodies (e.g., the OECD). We searched the Scopus database, which indexes various online journals in the education sector with an international scope, to collect peer-reviewed academic papers. Furthermore, we used an all-inclusive Google Scholar search to include relevant key terms or to include studies found in the reference list of the peer-reviewed papers, and other key studies and reports related to the concepts studied by professional and international bodies. Lastly, we gathered sources from the Publications Office of the European Union ( https://op.europa.eu/en/home ); namely, documents that refer to policies related to digital transformation in education.

Regarding search terms, we first searched resources on the impact of digital technologies on education by performing the following search queries: “impact” OR “effects” AND “digital technologies” AND “education”, “impact” OR “effects” AND “ICT” AND “education”. We further refined our results by adding the terms “meta-analysis” and “review” or by adjusting the search options based on the features of each database to avoid collecting individual studies that would provide limited contributions to a particular domain. We relied on meta-analyses and review studies as these consider the findings of multiple studies to offer a more comprehensive view of the research in a given area (Schuele & Justice, 2006 ). Specifically, meta-analysis studies provided quantitative evidence based on statistically verifiable results regarding the impact of educational interventions that integrate digital technologies in school classrooms (Higgins et al., 2012 ; Tolani-Brown et al., 2011 ).

However, quantitative data does not offer explanations for the challenges or difficulties experienced during ICT integration in learning and teaching (Tolani-Brown et al., 2011 ). To fill this gap, we analyzed literature reviews and gathered in-depth qualitative evidence of the benefits and implications of technology integration in schools. In the analysis presented herein, we also included policy documents and reports from professional and international bodies and governmental reports, which offered useful explanations of the key concepts of this study and provided recent evidence on digital capacity and transformation in education along with policy recommendations. The inclusion and exclusion criteria that were considered in this study are presented in Table ​ Table1 1 .

Inclusion and exclusion criteria for the selection of resources on the impact of digital technologies on education

To ensure a reliable extraction of information from each study and assist the research synthesis we selected the study characteristics of interest (impact) and constructed coding forms. First, an overview of the synthesis was provided by the principal investigator who described the processes of coding, data entry, and data management. The coders followed the same set of instructions but worked independently. To ensure a common understanding of the process between coders, a sample of ten studies was tested. The results were compared, and the discrepancies were identified and resolved. Additionally, to ensure an efficient coding process, all coders participated in group meetings to discuss additions, deletions, and modifications (Stock, 1994 ). Due to the methodological diversity of the studied documents we began to synthesize the literature review findings based on similar study designs. Specifically, most of the meta-analysis studies were grouped in one category due to the quantitative nature of the measured impact. These studies tended to refer to student achievement (Hattie et al., 2014 ). Then, we organized the themes of the qualitative studies in several impact categories. Lastly, we synthesized both review and meta-analysis data across the categories. In order to establish a collective understanding of the concept of impact, we referred to a previous impact study by Balanskat ( 2009 ) which investigated the impact of technology in primary schools. In this context, the impact had a more specific ICT-related meaning and was described as “ a significant influence or effect of ICT on the measured or perceived quality of (parts of) education ” (Balanskat, 2009 , p. 9). In the study presented herein, the main impacts are in relation to learning and learners, teaching, and teachers, as well as other key stakeholders who are directly or indirectly connected to the school unit.

The study’s results identified multiple dimensions of the impact of digital technologies on students’ knowledge, skills, and attitudes; on equality, inclusion, and social integration; on teachers’ professional and teaching practices; and on other school-related aspects and stakeholders. The data analysis indicated various factors that might affect the schools’ digital capacity and transformation, such as digital competencies, the teachers’ personal characteristics and professional development, as well as the school’s leadership and management, administration, infrastructure, etc. The impacts and factors found in the literature review are presented below.

Impacts of digital technologies on students’ knowledge, skills, attitudes, and emotions

The impact of ICT use on students’ knowledge, skills, and attitudes has been investigated early in the literature. Eng ( 2005 ) found a small positive effect between ICT use and students' learning. Specifically, the author reported that access to computer-assisted instruction (CAI) programs in simulation or tutorial modes—used to supplement rather than substitute instruction – could enhance student learning. The author reported studies showing that teachers acknowledged the benefits of ICT on pupils with special educational needs; however, the impact of ICT on students' attainment was unclear. Balanskat et al. ( 2006 ) found a statistically significant positive association between ICT use and higher student achievement in primary and secondary education. The authors also reported improvements in the performance of low-achieving pupils. The use of ICT resulted in further positive gains for students, namely increased attention, engagement, motivation, communication and process skills, teamwork, and gains related to their behaviour towards learning. Evidence from qualitative studies showed that teachers, students, and parents recognized the positive impact of ICT on students' learning regardless of their competence level (strong/weak students). Punie et al. ( 2006 ) documented studies that showed positive results of ICT-based learning for supporting low-achieving pupils and young people with complex lives outside the education system. Liao et al. ( 2007 ) reported moderate positive effects of computer application instruction (CAI, computer simulations, and web-based learning) over traditional instruction on primary school student's achievement. Similarly, Tamim et al. ( 2011 ) reported small to moderate positive effects between the use of computer technology (CAI, ICT, simulations, computer-based instruction, digital and hypermedia) and student achievement in formal face-to-face classrooms compared to classrooms that did not use technology. Jewitt et al., ( 2011 ) found that the use of learning platforms (LPs) (virtual learning environments, management information systems, communication technologies, and information- and resource-sharing technologies) in schools allowed primary and secondary students to access a wider variety of quality learning resources, engage in independent and personalized learning, and conduct self- and peer-review; LPs also provide opportunities for teacher assessment and feedback. Similar findings were reported by Fu ( 2013 ), who documented a list of benefits and opportunities of ICT use. According to the author, the use of ICTs helps students access digital information and course content effectively and efficiently, supports student-centered and self-directed learning, as well as the development of a creative learning environment where more opportunities for critical thinking skills are offered, and promotes collaborative learning in a distance-learning environment. Higgins et al. ( 2012 ) found consistent but small positive associations between the use of technology and learning outcomes of school-age learners (5–18-year-olds) in studies linking the provision and use of technology with attainment. Additionally, Chauhan ( 2017 ) reported a medium positive effect of technology on the learning effectiveness of primary school students compared to students who followed traditional learning instruction.

The rise of mobile technologies and hardware devices instigated investigations into their impact on teaching and learning. Sung et al. ( 2016 ) reported a moderate effect on students' performance from the use of mobile devices in the classroom compared to the use of desktop computers or the non-use of mobile devices. Schmid et al. ( 2014 ) reported medium–low to low positive effects of technology integration (e.g., CAI, ICTs) in the classroom on students' achievement and attitude compared to not using technology or using technology to varying degrees. Tamim et al. ( 2015 ) found a low statistically significant effect of the use of tablets and other smart devices in educational contexts on students' achievement outcomes. The authors suggested that tablets offered additional advantages to students; namely, they reported improvements in students’ notetaking, organizational and communication skills, and creativity. Zheng et al. ( 2016 ) reported a small positive effect of one-to-one laptop programs on students’ academic achievement across subject areas. Additional reported benefits included student-centered, individualized, and project-based learning enhanced learner engagement and enthusiasm. Additionally, the authors found that students using one-to-one laptop programs tended to use technology more frequently than in non-laptop classrooms, and as a result, they developed a range of skills (e.g., information skills, media skills, technology skills, organizational skills). Haßler et al. ( 2016 ) found that most interventions that included the use of tablets across the curriculum reported positive learning outcomes. However, from 23 studies, five reported no differences, and two reported a negative effect on students' learning outcomes. Similar results were indicated by Kalati and Kim ( 2022 ) who investigated the effect of touchscreen technologies on young students’ learning. Specifically, from 53 studies, 34 advocated positive effects of touchscreen devices on children’s learning, 17 obtained mixed findings and two studies reported negative effects.

More recently, approaches that refer to the impact of gamification with the use of digital technologies on teaching and learning were also explored. A review by Pan et al. ( 2022 ) that examined the role of learning games in fostering mathematics education in K-12 settings, reported that gameplay improved students’ performance. Integration of digital games in teaching was also found as a promising pedagogical practice in STEM education that could lead to increased learning gains (Martinez et al., 2022 ; Wang et al., 2022 ). However, although Talan et al. ( 2020 ) reported a medium effect of the use of educational games (both digital and non-digital) on academic achievement, the effect of non-digital games was higher.

Over the last two years, the effects of more advanced technologies on teaching and learning were also investigated. Garzón and Acevedo ( 2019 ) found that AR applications had a medium effect on students' learning outcomes compared to traditional lectures. Similarly, Garzón et al. ( 2020 ) showed that AR had a medium impact on students' learning gains. VR applications integrated into various subjects were also found to have a moderate effect on students’ learning compared to control conditions (traditional classes, e.g., lectures, textbooks, and multimedia use, e.g., images, videos, animation, CAI) (Chen et al., 2022b ). Villena-Taranilla et al. ( 2022 ) noted the moderate effect of VR technologies on students’ learning when these were applied in STEM disciplines. In the same meta-analysis, Villena-Taranilla et al. ( 2022 ) highlighted the role of immersive VR, since its effect on students’ learning was greater (at a high level) across educational levels (K-6) compared to semi-immersive and non-immersive integrations. In another meta-analysis study, the effect size of the immersive VR was small and significantly differentiated across educational levels (Coban et al., 2022 ). The impact of AI on education was investigated by Su and Yang ( 2022 ) and Su et al. ( 2022 ), who showed that this technology significantly improved students’ understanding of AI computer science and machine learning concepts.

It is worth noting that the vast majority of studies referred to learning gains in specific subjects. Specifically, several studies examined the impact of digital technologies on students’ literacy skills and reported positive effects on language learning (Balanskat et al., 2006 ; Grgurović et al., 2013 ; Friedel et al., 2013 ; Zheng et al., 2016 ; Chen et al., 2022b ; Savva et al., 2022 ). Also, several studies documented positive effects on specific language learning areas, namely foreign language learning (Kao, 2014 ), writing (Higgins et al., 2012 ; Wen & Walters, 2022 ; Zheng et al., 2016 ), as well as reading and comprehension (Cheung & Slavin, 2011 ; Liao et al., 2007 ; Schwabe et al., 2022 ). ICTs were also found to have a positive impact on students' performance in STEM (science, technology, engineering, and mathematics) disciplines (Arztmann et al., 2022 ; Bado, 2022 ; Villena-Taranilla et al., 2022 ; Wang et al., 2022 ). Specifically, a number of studies reported positive impacts on students’ achievement in mathematics (Balanskat et al., 2006 ; Hillmayr et al., 2020 ; Li & Ma, 2010 ; Pan et al., 2022 ; Ran et al., 2022 ; Verschaffel et al., 2019 ; Zheng et al., 2016 ). Furthermore, studies documented positive effects of ICTs on science learning (Balanskat et al., 2006 ; Liao et al., 2007 ; Zheng et al., 2016 ; Hillmayr et al., 2020 ; Kalemkuş & Kalemkuş, 2022 ; Lei et al., 2022a ). Çelik ( 2022 ) also noted that computer simulations can help students understand learning concepts related to science. Furthermore, some studies documented that the use of ICTs had a positive impact on students’ achievement in other subjects, such as geography, history, music, and arts (Chauhan, 2017 ; Condie & Munro, 2007 ), and design and technology (Balanskat et al., 2006 ).

More specific positive learning gains were reported in a number of skills, e.g., problem-solving skills and pattern exploration skills (Higgins et al., 2012 ), metacognitive learning outcomes (Verschaffel et al., 2019 ), literacy skills, computational thinking skills, emotion control skills, and collaborative inquiry skills (Lu et al., 2022 ; Su & Yang, 2022 ; Su et al., 2022 ). Additionally, several investigations have reported benefits from the use of ICT on students’ creativity (Fielding & Murcia, 2022 ; Liu et al., 2022 ; Quah & Ng, 2022 ). Lastly, digital technologies were also found to be beneficial for enhancing students’ lifelong learning skills (Haleem et al., 2022 ).

Apart from gaining knowledge and skills, studies also reported improvement in motivation and interest in mathematics (Higgins et. al., 2019 ; Fadda et al., 2022 ) and increased positive achievement emotions towards several subjects during interventions using educational games (Lei et al., 2022a ). Chen et al. ( 2022a ) also reported a small but positive effect of digital health approaches in bullying and cyberbullying interventions with K-12 students, demonstrating that technology-based approaches can help reduce bullying and related consequences by providing emotional support, empowerment, and change of attitude. In their meta-review study, Su et al. ( 2022 ) also documented that AI technologies effectively strengthened students’ attitudes towards learning. In another meta-analysis, Arztmann et al. ( 2022 ) reported positive effects of digital games on motivation and behaviour towards STEM subjects.

Impacts of digital technologies on equality, inclusion and social integration

Although most of the reviewed studies focused on the impact of ICTs on students’ knowledge, skills, and attitudes, reports were also made on other aspects in the school context, such as equality, inclusion, and social integration. Condie and Munro ( 2007 ) documented research interventions investigating how ICT can support pupils with additional or special educational needs. While those interventions were relatively small scale and mostly based on qualitative data, their findings indicated that the use of ICTs enabled the development of communication, participation, and self-esteem. A recent meta-analysis (Baragash et al., 2022 ) with 119 participants with different disabilities, reported a significant overall effect size of AR on their functional skills acquisition. Koh’s meta-analysis ( 2022 ) also revealed that students with intellectual and developmental disabilities improved their competence and performance when they used digital games in the lessons.

Istenic Starcic and Bagon ( 2014 ) found that the role of ICT in inclusion and the design of pedagogical and technological interventions was not sufficiently explored in educational interventions with people with special needs; however, some benefits of ICT use were found in students’ social integration. The issue of gender and technology use was mentioned in a small number of studies. Zheng et al. ( 2016 ) reported a statistically significant positive interaction between one-to-one laptop programs and gender. Specifically, the results showed that girls and boys alike benefitted from the laptop program, but the effect on girls’ achievement was smaller than that on boys’. Along the same lines, Arztmann et al. ( 2022 ) reported no difference in the impact of game-based learning between boys and girls, arguing that boys and girls equally benefited from game-based interventions in STEM domains. However, results from a systematic review by Cussó-Calabuig et al. ( 2018 ) found limited and low-quality evidence on the effects of intensive use of computers on gender differences in computer anxiety, self-efficacy, and self-confidence. Based on their view, intensive use of computers can reduce gender differences in some areas and not in others, depending on contextual and implementation factors.

Impacts of digital technologies on teachers’ professional and teaching practices

Various research studies have explored the impact of ICT on teachers’ instructional practices and student assessment. Friedel et al. ( 2013 ) found that the use of mobile devices by students enabled teachers to successfully deliver content (e.g., mobile serious games), provide scaffolding, and facilitate synchronous collaborative learning. The integration of digital games in teaching and learning activities also gave teachers the opportunity to study and apply various pedagogical practices (Bado, 2022 ). Specifically, Bado ( 2022 ) found that teachers who implemented instructional activities in three stages (pre-game, game, and post-game) maximized students’ learning outcomes and engagement. For instance, during the pre-game stage, teachers focused on lectures and gameplay training, at the game stage teachers provided scaffolding on content, addressed technical issues, and managed the classroom activities. During the post-game stage, teachers organized activities for debriefing to ensure that the gameplay had indeed enhanced students’ learning outcomes.

Furthermore, ICT can increase efficiency in lesson planning and preparation by offering possibilities for a more collaborative approach among teachers. The sharing of curriculum plans and the analysis of students’ data led to clearer target settings and improvements in reporting to parents (Balanskat et al., 2006 ).

Additionally, the use and application of digital technologies in teaching and learning were found to enhance teachers’ digital competence. Balanskat et al. ( 2006 ) documented studies that revealed that the use of digital technologies in education had a positive effect on teachers’ basic ICT skills. The greatest impact was found on teachers with enough experience in integrating ICTs in their teaching and/or who had recently participated in development courses for the pedagogical use of technologies in teaching. Punie et al. ( 2006 ) reported that the provision of fully equipped multimedia portable computers and the development of online teacher communities had positive impacts on teachers’ confidence and competence in the use of ICTs.

Moreover, online assessment via ICTs benefits instruction. In particular, online assessments support the digitalization of students’ work and related logistics, allow teachers to gather immediate feedback and readjust to new objectives, and support the improvement of the technical quality of tests by providing more accurate results. Additionally, the capabilities of ICTs (e.g., interactive media, simulations) create new potential methods of testing specific skills, such as problem-solving and problem-processing skills, meta-cognitive skills, creativity and communication skills, and the ability to work productively in groups (Punie et al., 2006 ).

Impacts of digital technologies on other school-related aspects and stakeholders

There is evidence that the effective use of ICTs and the data transmission offered by broadband connections help improve administration (Balanskat et al., 2006 ). Specifically, ICTs have been found to provide better management systems to schools that have data gathering procedures in place. Condie and Munro ( 2007 ) reported impacts from the use of ICTs in schools in the following areas: attendance monitoring, assessment records, reporting to parents, financial management, creation of repositories for learning resources, and sharing of information amongst staff. Such data can be used strategically for self-evaluation and monitoring purposes which in turn can result in school improvements. Additionally, they reported that online access to other people with similar roles helped to reduce headteachers’ isolation by offering them opportunities to share insights into the use of ICT in learning and teaching and how it could be used to support school improvement. Furthermore, ICTs provided more efficient and successful examination management procedures, namely less time-consuming reporting processes compared to paper-based examinations and smooth communications between schools and examination authorities through electronic data exchange (Punie et al., 2006 ).

Zheng et al. ( 2016 ) reported that the use of ICTs improved home-school relationships. Additionally, Escueta et al. ( 2017 ) reported several ICT programs that had improved the flow of information from the school to parents. Particularly, they documented that the use of ICTs (learning management systems, emails, dedicated websites, mobile phones) allowed for personalized and customized information exchange between schools and parents, such as attendance records, upcoming class assignments, school events, and students’ grades, which generated positive results on students’ learning outcomes and attainment. Such information exchange between schools and families prompted parents to encourage their children to put more effort into their schoolwork.

The above findings suggest that the impact of ICT integration in schools goes beyond students’ performance in school subjects. Specifically, it affects a number of school-related aspects, such as equality and social integration, professional and teaching practices, and diverse stakeholders. In Table ​ Table2, 2 , we summarize the different impacts of digital technologies on school stakeholders based on the literature review, while in Table ​ Table3 3 we organized the tools/platforms and practices/policies addressed in the meta-analyses, literature reviews, EU reports, and international bodies included in the manuscript.

The impact of digital technologies on schools’ stakeholders based on the literature review

Tools/platforms and practices/policies addressed in the meta-analyses, literature reviews, EU reports, and international bodies included in the manuscript

Additionally, based on the results of the literature review, there are many types of digital technologies with different affordances (see, for example, studies on VR vs Immersive VR), which evolve over time (e.g. starting from CAIs in 2005 to Augmented and Virtual reality 2020). Furthermore, these technologies are linked to different pedagogies and policy initiatives, which are critical factors in the study of impact. Table ​ Table3 3 summarizes the different tools and practices that have been used to examine the impact of digital technologies on education since 2005 based on the review results.

Factors that affect the integration of digital technologies

Although the analysis of the literature review demonstrated different impacts of the use of digital technology on education, several authors highlighted the importance of various factors, besides the technology itself, that affect this impact. For example, Liao et al. ( 2007 ) suggested that future studies should carefully investigate which factors contribute to positive outcomes by clarifying the exact relationship between computer applications and learning. Additionally, Haßler et al., ( 2016 ) suggested that the neutral findings regarding the impact of tablets on students learning outcomes in some of the studies included in their review should encourage educators, school leaders, and school officials to further investigate the potential of such devices in teaching and learning. Several other researchers suggested that a number of variables play a significant role in the impact of ICTs on students’ learning that could be attributed to the school context, teaching practices and professional development, the curriculum, and learners’ characteristics (Underwood, 2009 ; Tamim et al., 2011 ; Higgins et al., 2012 ; Archer et al., 2014 ; Sung et al., 2016 ; Haßler et al., 2016 ; Chauhan, 2017 ; Lee et al., 2020 ; Tang et al., 2022 ).

Digital competencies

One of the most common challenges reported in studies that utilized digital tools in the classroom was the lack of students’ skills on how to use them. Fu ( 2013 ) found that students’ lack of technical skills is a barrier to the effective use of ICT in the classroom. Tamim et al. ( 2015 ) reported that students faced challenges when using tablets and smart mobile devices, associated with the technical issues or expertise needed for their use and the distracting nature of the devices and highlighted the need for teachers’ professional development. Higgins et al. ( 2012 ) reported that skills training about the use of digital technologies is essential for learners to fully exploit the benefits of instruction.

Delgado et al. ( 2015 ), meanwhile, reported studies that showed a strong positive association between teachers’ computer skills and students’ use of computers. Teachers’ lack of ICT skills and familiarization with technologies can become a constraint to the effective use of technology in the classroom (Balanskat et al., 2006 ; Delgado et al., 2015 ).

It is worth noting that the way teachers are introduced to ICTs affects the impact of digital technologies on education. Previous studies have shown that teachers may avoid using digital technologies due to limited digital skills (Balanskat, 2006 ), or they prefer applying “safe” technologies, namely technologies that their own teachers used and with which they are familiar (Condie & Munro, 2007 ). In this regard, the provision of digital skills training and exposure to new digital tools might encourage teachers to apply various technologies in their lessons (Condie & Munro, 2007 ). Apart from digital competence, technical support in the school setting has also been shown to affect teachers’ use of technology in their classrooms (Delgado et al., 2015 ). Ferrari et al. ( 2011 ) found that while teachers’ use of ICT is high, 75% stated that they needed more institutional support and a shift in the mindset of educational actors to achieve more innovative teaching practices. The provision of support can reduce time and effort as well as cognitive constraints, which could cause limited ICT integration in the school lessons by teachers (Escueta et al., 2017 ).

Teachers’ personal characteristics, training approaches, and professional development

Teachers’ personal characteristics and professional development affect the impact of digital technologies on education. Specifically, Cheok and Wong ( 2015 ) found that teachers’ personal characteristics (e.g., anxiety, self-efficacy) are associated with their satisfaction and engagement with technology. Bingimlas ( 2009 ) reported that lack of confidence, resistance to change, and negative attitudes in using new technologies in teaching are significant determinants of teachers’ levels of engagement in ICT. The same author reported that the provision of technical support, motivation support (e.g., awards, sufficient time for planning), and training on how technologies can benefit teaching and learning can eliminate the above barriers to ICT integration. Archer et al. ( 2014 ) found that comfort levels in using technology are an important predictor of technology integration and argued that it is essential to provide teachers with appropriate training and ongoing support until they are comfortable with using ICTs in the classroom. Hillmayr et al. ( 2020 ) documented that training teachers on ICT had an important effecton students’ learning.

According to Balanskat et al. ( 2006 ), the impact of ICTs on students’ learning is highly dependent on the teachers’ capacity to efficiently exploit their application for pedagogical purposes. Results obtained from the Teaching and Learning International Survey (TALIS) (OECD, 2021 ) revealed that although schools are open to innovative practices and have the capacity to adopt them, only 39% of teachers in the European Union reported that they are well or very well prepared to use digital technologies for teaching. Li and Ma ( 2010 ) and Hardman ( 2019 ) showed that the positive effect of technology on students’ achievement depends on the pedagogical practices used by teachers. Schmid et al. ( 2014 ) reported that learning was best supported when students were engaged in active, meaningful activities with the use of technological tools that provided cognitive support. Tamim et al. ( 2015 ) compared two different pedagogical uses of tablets and found a significant moderate effect when the devices were used in a student-centered context and approach rather than within teacher-led environments. Similarly, Garzón and Acevedo ( 2019 ) and Garzón et al. ( 2020 ) reported that the positive results from the integration of AR applications could be attributed to the existence of different variables which could influence AR interventions (e.g., pedagogical approach, learning environment, and duration of the intervention). Additionally, Garzón et al. ( 2020 ) suggested that the pedagogical resources that teachers used to complement their lectures and the pedagogical approaches they applied were crucial to the effective integration of AR on students’ learning gains. Garzón and Acevedo ( 2019 ) also emphasized that the success of a technology-enhanced intervention is based on both the technology per se and its characteristics and on the pedagogical strategies teachers choose to implement. For instance, their results indicated that the collaborative learning approach had the highest impact on students’ learning gains among other approaches (e.g., inquiry-based learning, situated learning, or project-based learning). Ran et al. ( 2022 ) also found that the use of technology to design collaborative and communicative environments showed the largest moderator effects among the other approaches.

Hattie ( 2008 ) reported that the effective use of computers is associated with training teachers in using computers as a teaching and learning tool. Zheng et al. ( 2016 ) noted that in addition to the strategies teachers adopt in teaching, ongoing professional development is also vital in ensuring the success of technology implementation programs. Sung et al. ( 2016 ) found that research on the use of mobile devices to support learning tends to report that the insufficient preparation of teachers is a major obstacle in implementing effective mobile learning programs in schools. Friedel et al. ( 2013 ) found that providing training and support to teachers increased the positive impact of the interventions on students’ learning gains. Trucano ( 2005 ) argued that positive impacts occur when digital technologies are used to enhance teachers’ existing pedagogical philosophies. Higgins et al. ( 2012 ) found that the types of technologies used and how they are used could also affect students’ learning. The authors suggested that training and professional development of teachers that focuses on the effective pedagogical use of technology to support teaching and learning is an important component of successful instructional approaches (Higgins et al., 2012 ). Archer et al. ( 2014 ) found that studies that reported ICT interventions during which teachers received training and support had moderate positive effects on students’ learning outcomes, which were significantly higher than studies where little or no detail about training and support was mentioned. Fu ( 2013 ) reported that the lack of teachers’ knowledge and skills on the technical and instructional aspects of ICT use in the classroom, in-service training, pedagogy support, technical and financial support, as well as the lack of teachers’ motivation and encouragement to integrate ICT on their teaching were significant barriers to the integration of ICT in education.

School leadership and management

Management and leadership are important cornerstones in the digital transformation process (Pihir et al., 2018 ). Zheng et al. ( 2016 ) documented leadership among the factors positively affecting the successful implementation of technology integration in schools. Strong leadership, strategic planning, and systematic integration of digital technologies are prerequisites for the digital transformation of education systems (Ređep, 2021 ). Management and leadership play a significant role in formulating policies that are translated into practice and ensure that developments in ICT become embedded into the life of the school and in the experiences of staff and pupils (Condie & Munro, 2007 ). Policy support and leadership must include the provision of an overall vision for the use of digital technologies in education, guidance for students and parents, logistical support, as well as teacher training (Conrads et al., 2017 ). Unless there is a commitment throughout the school, with accountability for progress at key points, it is unlikely for ICT integration to be sustained or become part of the culture (Condie & Munro, 2007 ). To achieve this, principals need to adopt and promote a whole-institution strategy and build a strong mutual support system that enables the school’s technological maturity (European Commission, 2019 ). In this context, school culture plays an essential role in shaping the mindsets and beliefs of school actors towards successful technology integration. Condie and Munro ( 2007 ) emphasized the importance of the principal’s enthusiasm and work as a source of inspiration for the school staff and the students to cultivate a culture of innovation and establish sustainable digital change. Specifically, school leaders need to create conditions in which the school staff is empowered to experiment and take risks with technology (Elkordy & Lovinelli, 2020 ).

In order for leaders to achieve the above, it is important to develop capacities for learning and leading, advocating professional learning, and creating support systems and structures (European Commission, 2019 ). Digital technology integration in education systems can be challenging and leadership needs guidance to achieve it. Such guidance can be introduced through the adoption of new methods and techniques in strategic planning for the integration of digital technologies (Ređep, 2021 ). Even though the role of leaders is vital, the relevant training offered to them has so far been inadequate. Specifically, only a third of the education systems in Europe have put in place national strategies that explicitly refer to the training of school principals (European Commission, 2019 , p. 16).

Connectivity, infrastructure, and government and other support

The effective integration of digital technologies across levels of education presupposes the development of infrastructure, the provision of digital content, and the selection of proper resources (Voogt et al., 2013 ). Particularly, a high-quality broadband connection in the school increases the quality and quantity of educational activities. There is evidence that ICT increases and formalizes cooperative planning between teachers and cooperation with managers, which in turn has a positive impact on teaching practices (Balanskat et al., 2006 ). Additionally, ICT resources, including software and hardware, increase the likelihood of teachers integrating technology into the curriculum to enhance their teaching practices (Delgado et al., 2015 ). For example, Zheng et al. ( 2016 ) found that the use of one-on-one laptop programs resulted in positive changes in teaching and learning, which would not have been accomplished without the infrastructure and technical support provided to teachers. Delgado et al. ( 2015 ) reported that limited access to technology (insufficient computers, peripherals, and software) and lack of technical support are important barriers to ICT integration. Access to infrastructure refers not only to the availability of technology in a school but also to the provision of a proper amount and the right types of technology in locations where teachers and students can use them. Effective technical support is a central element of the whole-school strategy for ICT (Underwood, 2009 ). Bingimlas ( 2009 ) reported that lack of technical support in the classroom and whole-school resources (e.g., failing to connect to the Internet, printers not printing, malfunctioning computers, and working on old computers) are significant barriers that discourage the use of ICT by teachers. Moreover, poor quality and inadequate hardware maintenance, and unsuitable educational software may discourage teachers from using ICTs (Balanskat et al., 2006 ; Bingimlas, 2009 ).

Government support can also impact the integration of ICTs in teaching. Specifically, Balanskat et al. ( 2006 ) reported that government interventions and training programs increased teachers’ enthusiasm and positive attitudes towards ICT and led to the routine use of embedded ICT.

Lastly, another important factor affecting digital transformation is the development and quality assurance of digital learning resources. Such resources can be support textbooks and related materials or resources that focus on specific subjects or parts of the curriculum. Policies on the provision of digital learning resources are essential for schools and can be achieved through various actions. For example, some countries are financing web portals that become repositories, enabling teachers to share resources or create their own. Additionally, they may offer e-learning opportunities or other services linked to digital education. In other cases, specific agencies of projects have also been set up to develop digital resources (Eurydice, 2019 ).

Administration and digital data management

The digital transformation of schools involves organizational improvements at the level of internal workflows, communication between the different stakeholders, and potential for collaboration. Vuorikari et al. ( 2020 ) presented evidence that digital technologies supported the automation of administrative practices in schools and reduced the administration’s workload. There is evidence that digital data affects the production of knowledge about schools and has the power to transform how schooling takes place. Specifically, Sellar ( 2015 ) reported that data infrastructure in education is developing due to the demand for “ information about student outcomes, teacher quality, school performance, and adult skills, associated with policy efforts to increase human capital and productivity practices ” (p. 771). In this regard, practices, such as datafication which refers to the “ translation of information about all kinds of things and processes into quantified formats” have become essential for decision-making based on accountability reports about the school’s quality. The data could be turned into deep insights about education or training incorporating ICTs. For example, measuring students’ online engagement with the learning material and drawing meaningful conclusions can allow teachers to improve their educational interventions (Vuorikari et al., 2020 ).

Students’ socioeconomic background and family support

Research show that the active engagement of parents in the school and their support for the school’s work can make a difference to their children’s attitudes towards learning and, as a result, their achievement (Hattie, 2008 ). In recent years, digital technologies have been used for more effective communication between school and family (Escueta et al., 2017 ). The European Commission ( 2020 ) presented data from a Eurostat survey regarding the use of computers by students during the pandemic. The data showed that younger pupils needed additional support and guidance from parents and the challenges were greater for families in which parents had lower levels of education and little to no digital skills.

In this regard, the socio-economic background of the learners and their socio-cultural environment also affect educational achievements (Punie et al., 2006 ). Trucano documented that the use of computers at home positively influenced students’ confidence and resulted in more frequent use at school, compared to students who had no home access (Trucano, 2005 ). In this sense, the socio-economic background affects the access to computers at home (OECD, 2015 ) which in turn influences the experience of ICT, an important factor for school achievement (Punie et al., 2006 ; Underwood, 2009 ). Furthermore, parents from different socio-economic backgrounds may have different abilities and availability to support their children in their learning process (Di Pietro et al., 2020 ).

Schools’ socioeconomic context and emergency situations

The socio-economic context of the school is closely related to a school’s digital transformation. For example, schools in disadvantaged, rural, or deprived areas are likely to lack the digital capacity and infrastructure required to adapt to the use of digital technologies during emergency periods, such as the COVID-19 pandemic (Di Pietro et al., 2020 ). Data collected from school principals confirmed that in several countries, there is a rural/urban divide in connectivity (OECD, 2015 ).

Emergency periods also affect the digitalization of schools. The COVID-19 pandemic led to the closure of schools and forced them to seek appropriate and connective ways to keep working on the curriculum (Di Pietro et al., 2020 ). The sudden large-scale shift to distance and online teaching and learning also presented challenges around quality and equity in education, such as the risk of increased inequalities in learning, digital, and social, as well as teachers facing difficulties coping with this demanding situation (European Commission, 2020 ).

Looking at the findings of the above studies, we can conclude that the impact of digital technologies on education is influenced by various actors and touches many aspects of the school ecosystem. Figure  1 summarizes the factors affecting the digital technologies’ impact on school stakeholders based on the findings from the literature review.

Factors that affect the impact of ICTs on education

The findings revealed that the use of digital technologies in education affects a variety of actors within a school’s ecosystem. First, we observed that as technologies evolve, so does the interest of the research community to apply them to school settings. Figure  2 summarizes the trends identified in current research around the impact of digital technologies on schools’ digital capacity and transformation as found in the present study. Starting as early as 2005, when computers, simulations, and interactive boards were the most commonly applied tools in school interventions (e.g., Eng, 2005 ; Liao et al., 2007 ; Moran et al., 2008 ; Tamim et al., 2011 ), moving towards the use of learning platforms (Jewitt et al., 2011 ), then to the use of mobile devices and digital games (e.g., Tamim et al., 2015 ; Sung et al., 2016 ; Talan et al., 2020 ), as well as e-books (e.g., Savva et al., 2022 ), to the more recent advanced technologies, such as AR and VR applications (e.g., Garzón & Acevedo, 2019 ; Garzón et al., 2020 ; Kalemkuş & Kalemkuş, 2022 ), or robotics and AI (e.g., Su & Yang, 2022 ; Su et al., 2022 ). As this evolution shows, digital technologies are a concept in flux with different affordances and characteristics. Additionally, from an instructional perspective, there has been a growing interest in different modes and models of content delivery such as online, blended, and hybrid modes (e.g., Cheok & Wong, 2015 ; Kazu & Yalçin, 2022 ; Ulum, 2022 ). This is an indication that the value of technologies to support teaching and learning as well as other school-related practices is increasingly recognized by the research and school community. The impact results from the literature review indicate that ICT integration on students’ learning outcomes has effects that are small (Coban et al., 2022 ; Eng, 2005 ; Higgins et al., 2012 ; Schmid et al., 2014 ; Tamim et al., 2015 ; Zheng et al., 2016 ) to moderate (Garzón & Acevedo, 2019 ; Garzón et al., 2020 ; Liao et al., 2007 ; Sung et al., 2016 ; Talan et al., 2020 ; Wen & Walters, 2022 ). That said, a number of recent studies have reported high effect sizes (e.g., Kazu & Yalçin, 2022 ).

Current work and trends in the study of the impact of digital technologies on schools’ digital capacity

Based on these findings, several authors have suggested that the impact of technology on education depends on several variables and not on the technology per se (Tamim et al., 2011 ; Higgins et al., 2012 ; Archer et al., 2014 ; Sung et al., 2016 ; Haßler et al., 2016 ; Chauhan, 2017 ; Lee et al., 2020 ; Lei et al., 2022a ). While the impact of ICTs on student achievement has been thoroughly investigated by researchers, other aspects related to school life that are also affected by ICTs, such as equality, inclusion, and social integration have received less attention. Further analysis of the literature review has revealed a greater investment in ICT interventions to support learning and teaching in the core subjects of literacy and STEM disciplines, especially mathematics, and science. These were the most common subjects studied in the reviewed papers often drawing on national testing results, while studies that investigated other subject areas, such as social studies, were limited (Chauhan, 2017 ; Condie & Munro, 2007 ). As such, research is still lacking impact studies that focus on the effects of ICTs on a range of curriculum subjects.

The qualitative research provided additional information about the impact of digital technologies on education, documenting positive effects and giving more details about implications, recommendations, and future research directions. Specifically, the findings regarding the role of ICTs in supporting learning highlight the importance of teachers’ instructional practice and the learning context in the use of technologies and consequently their impact on instruction (Çelik, 2022 ; Schmid et al., 2014 ; Tamim et al., 2015 ). The review also provided useful insights regarding the various factors that affect the impact of digital technologies on education. These factors are interconnected and play a vital role in the transformation process. Specifically, these factors include a) digital competencies; b) teachers’ personal characteristics and professional development; c) school leadership and management; d) connectivity, infrastructure, and government support; e) administration and data management practices; f) students’ socio-economic background and family support and g) the socioeconomic context of the school and emergency situations. It is worth noting that we observed factors that affect the integration of ICTs in education but may also be affected by it. For example, the frequent use of ICTs and the use of laptops by students for instructional purposes positively affect the development of digital competencies (Zheng et al., 2016 ) and at the same time, the digital competencies affect the use of ICTs (Fu, 2013 ; Higgins et al., 2012 ). As a result, the impact of digital technologies should be explored more as an enabler of desirable and new practices and not merely as a catalyst that improves the output of the education process i.e. namely student attainment.

Conclusions

Digital technologies offer immense potential for fundamental improvement in schools. However, investment in ICT infrastructure and professional development to improve school education are yet to provide fruitful results. Digital transformation is a complex process that requires large-scale transformative changes that presuppose digital capacity and preparedness. To achieve such changes, all actors within the school’s ecosystem need to share a common vision regarding the integration of ICTs in education and work towards achieving this goal. Our literature review, which synthesized quantitative and qualitative data from a list of meta-analyses and review studies, provided useful insights into the impact of ICTs on different school stakeholders and showed that the impact of digital technologies touches upon many different aspects of school life, which are often overlooked when the focus is on student achievement as the final output of education. Furthermore, the concept of digital technologies is a concept in flux as technologies are not only different among them calling for different uses in the educational practice but they also change through time. Additionally, we opened a forum for discussion regarding the factors that affect a school’s digital capacity and transformation. We hope that our study will inform policy, practice, and research and result in a paradigm shift towards more holistic approaches in impact and assessment studies.

Study limitations and future directions

We presented a review of the study of digital technologies' impact on education and factors influencing schools’ digital capacity and transformation. The study results were based on a non-systematic literature review grounded on the acquisition of documentation in specific databases. Future studies should investigate more databases to corroborate and enhance our results. Moreover, search queries could be enhanced with key terms that could provide additional insights about the integration of ICTs in education, such as “policies and strategies for ICT integration in education”. Also, the study drew information from meta-analyses and literature reviews to acquire evidence about the effects of ICT integration in schools. Such evidence was mostly based on the general conclusions of the studies. It is worth mentioning that, we located individual studies which showed different, such as negative or neutral results. Thus, further insights are needed about the impact of ICTs on education and the factors influencing the impact. Furthermore, the nature of the studies included in meta-analyses and reviews is different as they are based on different research methodologies and data gathering processes. For instance, in a meta-analysis, the impact among the studies investigated is measured in a particular way, depending on policy or research targets (e.g., results from national examinations, pre-/post-tests). Meanwhile, in literature reviews, qualitative studies offer additional insights and detail based on self-reports and research opinions on several different aspects and stakeholders who could affect and be affected by ICT integration. As a result, it was challenging to draw causal relationships between so many interrelating variables.

Despite the challenges mentioned above, this study envisaged examining school units as ecosystems that consist of several actors by bringing together several variables from different research epistemologies to provide an understanding of the integration of ICTs. However, the use of other tools and methodologies and models for evaluation of the impact of digital technologies on education could give more detailed data and more accurate results. For instance, self-reflection tools, like SELFIE—developed on the DigCompOrg framework- (Kampylis et al., 2015 ; Bocconi & Lightfoot, 2021 ) can help capture a school’s digital capacity and better assess the impact of ICTs on education. Furthermore, the development of a theory of change could be a good approach for documenting the impact of digital technologies on education. Specifically, theories of change are models used for the evaluation of interventions and their impact; they are developed to describe how interventions will work and give the desired outcomes (Mayne, 2015 ). Theory of change as a methodological approach has also been used by researchers to develop models for evaluation in the field of education (e.g., Aromatario et al., 2019 ; Chapman & Sammons, 2013 ; De Silva et al., 2014 ).

We also propose that future studies aim at similar investigations by applying more holistic approaches for impact assessment that can provide in-depth data about the impact of digital technologies on education. For instance, future studies could focus on different research questions about the technologies that are used during the interventions or the way the implementation takes place (e.g., What methodologies are used for documenting impact? How are experimental studies implemented? How can teachers be taken into account and trained on the technology and its functions? What are the elements of an appropriate and successful implementation? How is the whole intervention designed? On which learning theories is the technology implementation based?).

Future research could also focus on assessing the impact of digital technologies on various other subjects since there is a scarcity of research related to particular subjects, such as geography, history, arts, music, and design and technology. More research should also be done about the impact of ICTs on skills, emotions, and attitudes, and on equality, inclusion, social interaction, and special needs education. There is also a need for more research about the impact of ICTs on administration, management, digitalization, and home-school relationships. Additionally, although new forms of teaching and learning with the use of ICTs (e.g., blended, hybrid, and online learning) have initiated several investigations in mainstream classrooms, only a few studies have measured their impact on students’ learning. Additionally, our review did not document any study about the impact of flipped classrooms on K-12 education. Regarding teaching and learning approaches, it is worth noting that studies referred to STEM or STEAM did not investigate the impact of STEM/STEAM as an interdisciplinary approach to learning but only investigated the impact of ICTs on learning in each domain as a separate subject (science, technology, engineering, arts, mathematics). Hence, we propose future research to also investigate the impact of the STEM/STEAM approach on education. The impact of emerging technologies on education, such as AR, VR, robotics, and AI has also been investigated recently, but more work needs to be done.

Finally, we propose that future studies could focus on the way in which specific factors, e.g., infrastructure and government support, school leadership and management, students’ and teachers’ digital competencies, approaches teachers utilize in the teaching and learning (e.g., blended, online and hybrid learning, flipped classrooms, STEM/STEAM approach, project-based learning, inquiry-based learning), affect the impact of digital technologies on education. We hope that future studies will give detailed insights into the concept of schools’ digital transformation through further investigation of impacts and factors which influence digital capacity and transformation based on the results and the recommendations of the present study.

Acknowledgements

This project has received funding under Grant Agreement No Ref Ares (2021) 339036 7483039 as well as funding from the European Union’s Horizon 2020 Research and Innovation Program under Grant Agreement No 739578 and the Government of the Republic of Cyprus through the Deputy Ministry of Research, Innovation and Digital Policy. The UVa co-authors would like also to acknowledge funding from the European Regional Development Fund and the National Research Agency of the Spanish Ministry of Science and Innovation, under project grant PID2020-112584RB-C32.

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A systematic literature review on Internet of things in education: Benefits and challenges

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With close to 20.4 billion devices connected to the Internet to be deployed by 2020, Internet of things (IoT) is already being leveraged in diverse sectors. Now, because of the ubiquitous nature of IoT devices, schools and academic institutions are looking to incorporate IoT in educational activities. With the increased use of IoT in the education domain, it is of utmost importance to study how this technology with its distinguished system functions such as sensing and decision making can support and challenge the pedagogical processes for all interrelated actors (faculty, students, and staff) as well as all involved assets (e.g., libraries, classrooms, and labs). Although there have been several contributions on the inclusion of IoT into the education domain, there is still a lack of consolidated and coherent views on this subject. Hence, we are motivated to close the gap of knowledge and embarked on mapping out the published studies available. This study presents the results of a systematic literature review focusing on the benefits and the challenges faced in education in integrating IoT into the curriculum and educational environments. Different mapping views of the extracted studies are provided as long as a summary of the already implemented tools and a list of gap research questions yet to be investigated.

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• Education Engineering & Materials Science 100%
• Internet of things Engineering & Materials Science 98%
• Internet Social Sciences 73%
• literature Social Sciences 49%
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• Curricula Engineering & Materials Science 20%
• educational activities Social Sciences 17%
• Students Engineering & Materials Science 14%

T1 - A systematic literature review on Internet of things in education

T2 - Benefits and challenges

AU - Kassab, Mohamad

AU - DeFranco, Joanna

AU - Laplante, Phillip

N1 - Publisher Copyright: © 2019 John Wiley & Sons, Ltd

PY - 2020/4/1

Y1 - 2020/4/1

N2 - With close to 20.4 billion devices connected to the Internet to be deployed by 2020, Internet of things (IoT) is already being leveraged in diverse sectors. Now, because of the ubiquitous nature of IoT devices, schools and academic institutions are looking to incorporate IoT in educational activities. With the increased use of IoT in the education domain, it is of utmost importance to study how this technology with its distinguished system functions such as sensing and decision making can support and challenge the pedagogical processes for all interrelated actors (faculty, students, and staff) as well as all involved assets (e.g., libraries, classrooms, and labs). Although there have been several contributions on the inclusion of IoT into the education domain, there is still a lack of consolidated and coherent views on this subject. Hence, we are motivated to close the gap of knowledge and embarked on mapping out the published studies available. This study presents the results of a systematic literature review focusing on the benefits and the challenges faced in education in integrating IoT into the curriculum and educational environments. Different mapping views of the extracted studies are provided as long as a summary of the already implemented tools and a list of gap research questions yet to be investigated.

AB - With close to 20.4 billion devices connected to the Internet to be deployed by 2020, Internet of things (IoT) is already being leveraged in diverse sectors. Now, because of the ubiquitous nature of IoT devices, schools and academic institutions are looking to incorporate IoT in educational activities. With the increased use of IoT in the education domain, it is of utmost importance to study how this technology with its distinguished system functions such as sensing and decision making can support and challenge the pedagogical processes for all interrelated actors (faculty, students, and staff) as well as all involved assets (e.g., libraries, classrooms, and labs). Although there have been several contributions on the inclusion of IoT into the education domain, there is still a lack of consolidated and coherent views on this subject. Hence, we are motivated to close the gap of knowledge and embarked on mapping out the published studies available. This study presents the results of a systematic literature review focusing on the benefits and the challenges faced in education in integrating IoT into the curriculum and educational environments. Different mapping views of the extracted studies are provided as long as a summary of the already implemented tools and a list of gap research questions yet to be investigated.

UR - http://www.scopus.com/inward/record.url?scp=85074992670&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85074992670&partnerID=8YFLogxK

U2 - 10.1111/jcal.12383

DO - 10.1111/jcal.12383

M3 - Article

AN - SCOPUS:85074992670

SN - 0266-4909

JO - Journal of Computer Assisted Learning

JF - Journal of Computer Assisted Learning

Implications Of Internet Of Things (IoT) On The Education For Students With Disabilities: A Systematic Literature Review

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Earlier decision on detection of ransomware identification: a comprehensive systematic literature review.

1. Introduction

• Provides a detailed overview of how ransomware has developed over time, focusing on its mechanisms, types, and the vectors used for attacks.
• Conducts a comprehensive review of the current approaches in ransomware detection. In addition, emphasizes the techniques and methods used at various stages of detection.
• Highlights how ML is being employed to improve ransomware detection.
• Identifies the gaps in current research and suggests potential areas for future investigations to enhance the cybersecurity field’s defense against ransomware attacks.

2. Papers Selection for Literature Review

2.1. methodology, 2.2. search string, 2.3. data sources, 2.4. screening process, 3. background, 3.1. overview of ransomware attacks, 3.2. types of ransomware.

• Encrypting Ransomware: This type is the most common and involves encrypting the victim’s files with a strong encryption algorithm, making them inaccessible without a decryption key. Notable examples include Cryptowall, WannaCry, and Cryptolocker. The victim can see the files but cannot open them unless they pay the ransom to obtain the decryption key.
• Non-Encrypting Ransomware: Also known as locker ransomware, this type locks you out of your entire device, not just specific files. The data remain unharmed but inaccessible. To regain access, the victim must pay a ransom. Examples include CTB-Locker and Winlock.
• Scareware: also known as fake antivirus, scareware tries to convince the victim that their device is infected by showing a false warning and then asking for payment to access the full version of the software to remove or mitigate the risk. Scareware typically uses social engineering methods rather than encrypting the files or devices to scare the victims and then force them to pay.
• PC/Workstation ransomware: This type targets personal computers and workstations, exploiting vulnerabilities in Windows, macOS, or Linux systems. Examples include the infamous WannaCry attack, which specifically targeted Windows systems using a network exploit.
• Mobile ransomware: Targeting mobile devices, this type of ransomware affects smartphones and tablets, primarily through malicious apps or compromised websites. Android devices are more frequently targeted due to the ease of installing apps from third-party sources.
• IoT ransomware: IoT devices, such as smart home gadgets and industrial sensors, are increasingly being targeted due to their poor security measures. Attacks on these devices can lead to significant disruptions, especially when they affect critical infrastructure.
• Individual users: This group is often the easiest target due to less stringent security practices. Attackers exploit this by using deceptive emails or malicious websites to initiate ransomware infections.
• Enterprises: Businesses are targeted for their valuable data and deeper financial resources. Attacks may involve sophisticated strategies to infiltrate network defenses and encrypt critical business data.
• Government and critical infrastructure: Attacks on government systems and critical infrastructure aim to cause significant disruption, often impacting national security, healthcare, and essential services.
• Online Services: Cloud services and online platforms, such as social media and banking services, are also targeted, with attackers aiming to encrypt or steal large amounts of data to demand higher ransoms.

3.3. Ransomware Attack Vectors

3.4. evolution of ransomware, 3.5. ransomware encryption techniques.

• Generate the key: A unique key is generated to be used in symmetric encryption.
• Encrypt the files: The victim’s files are encrypted by ransomware using a single secret key. Ransomware targets the victim’s sensitive information and files, such as documents, photos, and videos.
• Protect the key: To prevent key recovery by the victim, ransomware encrypts it until payment is made. Then, the encrypted key is saved on the attacker’s servers.
• Advanced Encryption Standard (AES): AES is one example of a symmetric encryption algorithm. It is secure and cannot be cracked easily. The key length used in the AES algorithm to encrypt victims’ files is 128-, 192-, or 256-bit [ 25 ].
• Generate the keys: a pair of keys is generated to be used in asymmetric encryption.
• Encrypt the file using the public key: the victim’s files are encrypted using the public key.
• Protect the private key: the private key is stored on the attacker’s servers until payment is made by the victim.
• Examples of asymmetric encryption algorithms: RSA encryption: RSA is one example of an asymmetric encryption algorithm. It contains two keys, which are the public key and the private key. The public key is used for the encryption algorithm, which is used to encrypt the victim’s files, and the private key is used for the decryption algorithm, which is used for the decryption and stored remotely on the attacker’s servers [ 26 ]. Elliptic Curve Cryptography (ECC): ECC is another example of an asymmetric encryption algorithm. ECC key length is shorter than RSA and more secure. As with RSA, ECC consists of two keys, which are public and private—one for encrypting the files and another for decrypting [ 27 ].

3.6. Signs of a Ransomware Attack

3.7. challenges in early detection of ransomware, 3.8. the role of artificial intelligence to improve ransomware detection.

Click here to enlarge figure

• Deep learning: Deep learning (DL) techniques are proposed to solve the restrictions of traditional ransomware detection methods, which help to improve reliability, accuracy, and performance. It is suitable for dealing with an unorganized dataset that requires minimal or no human intervention because of its self-learning capabilities. They operate particularly well at identifying text- and image-based ransomware because of how well they can categorize voice, text, and image data. DL methods can be problematic for general-purpose applications, especially those with tiny datasets or sizes, as they require a large quantity of data to train them. High processing power requirements and trouble adjusting to real-world datasets are two further issues with DL [ 46 ].
• Artificial neural networks: Artificial neural network techniques are used in a broad range, which makes them suitable for detecting many kinds and variations of ransomware data, including variants that target images and text. Because of their capacity for ongoing learning, neural networks make an ideal choice for recognizing zero-day attacks and adjusting to new ransomware data. Neural networks can detect many types of ransomware data and adjust to new threats due to their versatility. However, because of the black-box nature of the technology and their reliance on hardware, these techniques can be susceptible to data dependencies, making it more difficult for human analysts to keep an eye on data processing and spot anomalies [ 47 ].
• Ransomware behavioral analysis: One successful study used ML as a defense mechanism against ransomware attacks. The analysis considered seven ransomware and seven benign software samples to distinguish between benign and malicious software with low false negative and false positive rates. Values from different ransomware, such as Dynamic Link Libraries (DLLs), were extracted in this study. DLLs are a type of file used in Windows operating systems to hold multiple codes and procedures that are shared among various applications. Essentially, DLLs allow programs to use functionalities that are stored in separate files rather than having to include them within the program itself. This not only helps in saving space but also promotes code reuse and modular programming. When a program runs, it can call upon a DLL file to perform certain functions, which helps in efficient memory usage and reduces the application’s load time because it only loads the necessary parts. DLLs are crucial for the operating system to manage shared resources effectively, enabling smoother and more performance-efficient operation of software on your computer. Early detection of ransomware attacks and alerting the user about the existing threat are considered a main feature of this proposed system [ 48 ].
• Anomaly detection in network traffic: In [ 49 ], AI algorithms and ML techniques were used to detect anomalies by analyzing network traffic. This process is performed by labeling normal and abnormal features and utilizing ML to detect the unusual status of the network. The system succeeded in isolating harmful activities, allowing early detection, and taking the necessary preventive measures.
• Signature-based ransomware detection: ML models were used in some systems that aim to detect ransomware signatures. Ransomware tends to constantly change its signatures to prevent detection by traditional detection techniques. ML models are constantly updated to identify new forms of ransomware, which allows for early detection and appropriate decision-making [ 19 ].

3.9. Preventive Measures and Best Practices

• Employee education and awareness: Increasing individuals’ awareness of the dangers of ransomware and educating them on cybersecurity best practices, such as detecting suspicious messages and avoiding downloading files or programs from suspicious or unreliable links [ 13 ].
• Strong password policies: Forcing the user to use strong and complex passwords. In addition, it is necessary to change the passwords regularly and use password management programs for better management and security [ 50 ].
• Multi-factor authentication (MFA): Using multi-layer protection to safeguard sensitive data or files such as passwords, voice recognition, and facial recognition [ 51 ].
• Regular backups: Regular backups of sensitive data are made to mitigate the damage in case hackers gain access to the original data [ 52 ].
• Timely updates: Ensure that all programs and operating systems are updated to the latest version and allow automatic updating of these preventive programs once connected to the Internet [ 22 ].
• Network segmentation and access Control: Applying the principle of network segmentation to isolate important data from other data. In addition, implementing the least privilege principle by granting privileges to users as needed to perform tasks [ 53 ].

3.10. Regulatory and Legal Considerations

3.11. future trends in ransomware, 4. comprehensive analysis of ransomware: detection, prevention, and trends, 4.1. indicators of potential ransomware incidence.

• Excessive File Operations: A noticeable rise in file access activities. For example, opening or attempting to open a large number of files in a short time frame. This may indicate an ongoing ransomware attack.
• Altered Input/Output Behavior: The input and output patterns where the structure and volume of data being processed significantly change.
• High Volume of Write Operations: A large increase in write or overwrite operations on the system could suggest that files are being encrypted by ransomware.
• Use of Encryption Functions: The call of Application Programming Interfaces (APIs) by a process not typically associated with.
• Rapid File Modification Requests: Frequent requests to read, modify, or delete files within a short period of time. These could be signs of ransomware attempting to encrypt or erase data.
• Unusual Network Communications: Initiating communications with a command-and-control (C2) server. This is a common step for ransomware to receive instructions or transmit encryption keys.
• Registry Key Modifications: Unexpected changes in the keys associated with system startup or file associations.

4.2. Ransomware Attack Framework

• Target Identification: the initial phase involves selecting and identifying vulnerable systems or networks as potential targets for the attack.
• Infection Vector Distribution: this step encompasses executing the ransomware through chosen delivery mechanisms—this could be by phishing emails, compromised websites, or malicious downloads.
• Ransomware Installation: after successful entry into the system, the ransomware installs itself.
• Encryption Key Generation and Retrieval: the ransomware then generates an encryption key to lock the victim’s files.
• File Access: targeting the data that are valuable to the user.
• Data Encryption: this phase encrypts the victim’s files, making them inaccessible without the decryption key.
• Post-Encryption Operations: After encryption, the ransomware may perform additional actions, such as deleting system backups.
• Ransom Demand: Finally, the attacker demands a ransom from the victim, often in a cryptocurrency.

4.3. Behavior Patterns of Ransomware Attacks

• Type A Behavior: Ransomware directly encrypts the original files without creating copies. The steps include opening, reading, encrypting, and then closing the files. Sometimes, it may also rename the encrypted files to indicate they have been compromised.
• Type B Behavior: Ransomware removes the original files from their location, creates encrypted copies, and then returns these encrypted versions to the original directory. The encrypted files might have different names from the originals, satisfying their encryption status.
• Type C Behavior: Reading the original files and creating separate encrypted versions. The original files are deleted to eliminate any trace of the unencrypted data. The deletion is typically achieved through file movement operations that overwrite the originals.

4.4. Comparison of Ransomware Detection Methods

4.5. effectiveness of current ransomware detection approaches, 4.6. taxonomy of ransomware detection technique.

• Static Analysis: This involves checking the code of a suspicious file without running it [ 5 ]. The process includes examining the file structure, identifying any embedded strings (like text), and looking for known malicious patterns. To detect ransomware, some tools and studies focus on analyzing the parts of a file that do not change. However, as ransomware evolves, these static methods might not always work, especially with ransomware that hides its true nature [ 13 ].
• Dynamic Analysis: The suspicious file is actually run in a controlled environment to observe what it does [ 5 ]. This might include looking at the file’s behavior, which files it tries to change [ 5 ], and how it interacts with the computer’s system. Various studies have used dynamic analysis to understand how ransomware behaves during an attack. This approach has been effective in detecting new types of ransomware but requires careful setup to avoid actual damage [ 13 ].
• Hybrid Analysis: Combines static and dynamic methods for a more comprehensive examination by looking at both the file’s code and its behavior when executed. This approach aims to detect ransomware that might pass through with just one type of analysis. Hybrid analysis has shown promise in identifying ransomware early in the infection process. It benefits from the strengths of both static and dynamic analysis. Therefore, it offers a stronger detection method.

4.7. Emerging Trends in Ransomware

4.8. ransomware avoidance strategies.

• Keep software up to date: Regularly updating the operating system and all applications is crucial. These updates often include patches for security vulnerabilities that ransomware attackers exploit.
• Unknown emails and downloads: Avoid opening emails or downloading attachments from unknown or suspicious sources. Cybercriminals often use phishing emails to spread ransomware.
• Use browser security features: Enable security features in web browsers that can block malicious websites and downloads. Disabling JavaScript and Java on untrusted sites can also help prevent ransomware from being downloaded on your device.
• Limit access to important files: Use features like “Controlled Folder Access” on Windows to prevent unauthorized applications from modifying protected folders. This step is particularly effective in stopping ransomware from encrypting your files.
• Backup your data: Regularly back up your data and ensure that backups are stored in a secure location and disconnected from your main network. As a result, if you do fall victim to a ransomware attack, you can restore your data from the backup without paying the ransom.
• Use security software: Employ antivirus and anti-ransomware software to detect and prevent ransomware threats. Keep this software up to date to protect against the latest ransomware variants.

5. Real-World Ransomware Incidents

• WannaCry Global Ransomware Attack (2017): In May 2017, the WannaCry ransomware attack spread across over 150 countries and infected more than 250,000 computers [ 64 ]. The attack exploited a vulnerability in Microsoft Windows in which a patch had been released but not widely applied [ 64 ]. One of the victims of this attack was the UK’s National Health Service (NHS). The ransomware encrypted files and demanded Bitcoin payments to release the encrypted data [ 64 ]. The attack highlighted the importance of regular software updated and the strong impact of ransomware on critical infrastructure and services. It also marked a turning point in encouraging global awareness and efforts to combat cyber threats.
• Colonial Pipeline Attack (2021) The Colonial Pipeline ransomware attack in May 2021 underscored the vulnerability of critical infrastructure to cyberattacks [ 65 ]. The Colonial Pipeline, which carries gasoline and jet fuel over 5500 miles (about 8850 km) between Texas and New York [ 65 ], was forced to shut down operations due to a ransomware attack by a group known as DarkSide [ 65 ]. This disruption led to a significant increase in gas prices, panic buying, and fuel shortages across the Eastern United States [ 65 ]. The company paid a ransom of nearly USD 5 million in cryptocurrency to regain access to their systems [ 65 ]. This incident encouraged the U.S. government to issue new cybersecurity directives for pipeline operators [ 65 ]; moreover, it emphasized the national security implications of ransomware attacks.
• Atlanta City Government Attack (2018) In March 2018, the city government of Atlanta, Georgia, was hit by a ransomware attack [ 66 ]. This attack hit a big part of its digital infrastructure [ 66 ]. The SamSam ransomware attack affected multiple city services, which included court proceedings, bill payments, and law enforcement activities [ 66 ]. These affected services demonstrated how ransomware could damage the day-to-day operations of a city. They demanded a ransom of USD 51,000 in Bitcoin but the city chose not to pay [ 66 ]. The recovery and mitigation efforts cost the city an estimated USD 17 million [ 66 ]. This incident provided motivation to other cities across the United States to strengthen their cybersecurity defenses.
• University of California, San Francisco (UCSF) Attack (2020): The University of California, San Francisco (UCSF), fell victim to a ransomware attack in June 2020. This attack targeted the School of Medicine’s IT infrastructure [ 67 ]. They faced the potential loss of critical academic research data, including work related to COVID-19 [ 67 ]. UCSF chose to pay a ransom of over USD 1.14 million [ 67 ]. The NetWalker ransomware group was responsible for the attack [ 67 ]. They exploited vulnerabilities in unsecured networks [ 67 ]. This incident satisfied the complex ethical and financial decisions ransomware victims must take when critical scientific research is in danger.

6. Comparison with Other Review Papers

7. related study.

8. Open Challenges and Limitations

9. future directions, 9.1. development of new detection algorithms, 9.2. integration of ai and ml, 9.3. impact of emerging technologies, 9.4. improved data collection and sharing, 9.5. development of resilient backup solutions, 10. conclusions, author contributions, institutional review board statement, informed consent statement, data availability statement, acknowledgments, conflicts of interest, abbreviations.

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Share and Cite

Albshaier, L.; Almarri, S.; Rahman, M.M.H. Earlier Decision on Detection of Ransomware Identification: A Comprehensive Systematic Literature Review. Information 2024 , 15 , 484. https://doi.org/10.3390/info15080484

Albshaier L, Almarri S, Rahman MMH. Earlier Decision on Detection of Ransomware Identification: A Comprehensive Systematic Literature Review. Information . 2024; 15(8):484. https://doi.org/10.3390/info15080484

Albshaier, Latifa, Seetah Almarri, and M. M. Hafizur Rahman. 2024. "Earlier Decision on Detection of Ransomware Identification: A Comprehensive Systematic Literature Review" Information 15, no. 8: 484. https://doi.org/10.3390/info15080484

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Implications of Internet of Things (IoT) on the Education for students with disabilities: A Systematic Literature Review

International Journal of Research Publications

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