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This conceptual study investigates the adoption of education technology (EdTech) products among college students, focusing on identifying the key factors influencing the adoption process within educational institutions. Technology integration in education has rapidly gained prominence, with EdTech offering innovative solutions to enhance teaching and learning experiences. However, understanding the determinants that affect EdTech adoption remains critical for its successful implementation and impact. This paper aims (1) to identify the factors influencing the adoption of EdTech by college students (2) to create a conceptual model that shows the connections between the elements that lead to college students adopting EdTech.

The research employed a mixed-methods approach, combining qualitative data analysis and conceptual modeling to achieve the objectives. The underlying knowledge required to create a qualitative data gathering tool was obtained through a thorough literature analysis on innovation dissemination, educational psychology and technology adoption. College students, teachers and administrators participated in semi-structured interviews, focus groups and surveys to provide detailed perspectives on their attitudes about and experiences with EdTech. The Scopus and Web of Science databases are searched for relevant information in an organized manner in order to determine the factors influencing the adoption of EdTech. Second, an extended version of the technology adoption model is adopted to develop a qualitative data-based conceptual framework to analyze EdTech adoption in the Indian context.

Overall, by highlighting the critical components that emotionally influence college students' adoption of EdTech products in educational institutions, this course adds to the body of information already in existence. The conceptual framework model serves as a roadmap for educational stakeholders seeking to leverage EdTech effectively to enrich the learning environment and improve educational outcomes. By recognizing the significance of the identified factors, academic institutions can make informed decisions to foster a climate conducive to successful EdTech integration.

A comprehensive conceptual framework model was developed based on qualitative data analysis to illustrate the interrelationships between the identified factors influencing EdTech adoption. This model presents a valuable tool for educational institutions, policymakers and EdTech developers to comprehend the complex dynamics of implementing these technological solutions.

The findings of this study demonstrated a number of important variables that affect the uptake of EdTech products in educational settings. These factors encompassed technological infrastructure, ease of use, perceived usefulness, compatibility with existing academic practices, institutional support, financial constraints and individual attitudes towards technology. Additionally, the research explored the significance of institutional preparation for embracing technological advancements as well as the influence of socio-cultural elements.

This chapter is based on the findings of the empirical material gathered in Finland and Sweden through interviews with education and audiovisual (AV) media actors and policymakers in 2017–2018. The aim of the chapter is to discuss the innovation systems of the education sector and Finland and Sweden in general, compare the sectoral innovation models of the two sectors, and conclude with discussing the resulting challenges for policymakers. Our results show that a new EdTech sector employing the competences of the education, information and communication technology, and AV media sectors has begun to emerge and actors in the both countries have eagerly taken actions to boost its development as a business and export field. We discuss the reasons and consequences of this development.

There are five factors acting as a barrier to the effective evaluation of educational technology (edtech), which are as follows: premature timing, inappropriate techniques, rapid change, complexity of context and inconsistent terminology. The purpose of this paper is to identify new evaluation approaches that will address these and reflect on the evaluation imperative for complex technology initiatives.

An initial investigation of traditional evaluative approaches used within the technology domain was broadened to investigate the evaluation practices within social and public policy domains. Realist evaluation, a branch of theory-based evaluation, was identified and reviewed in detail. The realist approach was then refined, proposing two additional necessary steps to support mapping the technical complexity of initiatives.

A refined illustrative example of a realist evaluation framework is presented, including two novel architectural edtech domain reference models to support mapping.

Recommendations include building individual evaluator capacity; adopting the realist framework; the use of architectural edtech domain reference models; phased evaluation to first build theories in technology “context” and then iteratively during complex implementation chains; and community contribution to a shared map of technical and organisational complexity.

This paper makes a novel contribution by arguing the imperative for a theory-based realist approach to help redefine evaluative thinking within the IT and complex system domain. It becomes an innovative proposal with the addition of two domain reference models that tailor the approach for edtech. Its widespread adoption will help build a shared evidence base that synthesizes and surfaces “what works, for whom, in which contexts and why”, benefiting educators, IT managers, funders, policymakers and future learners.

The chapter concludes the section on cross-innovation and convergence processes between audiovisual media industries and the education sector. It addresses, first, that these processes are not driven by any specific technology, but by two broad and interdependent processes – individualisation that makes people in insecure careers search for personalised learning opportunities and the experience economy that produces expectations for learning experiences to be pleasurable and fun, that is, gamified. The chapter demonstrates the emergence of EdTech as a new dialogic subsector operating between the publicly operating education sector and the private media and information and communication technology industries. It demonstrates the inherent institutional diversity in and around this subsector and discusses the nature of the dialogues constituting it. It, lastly, addresses the risks deriving from global platformisation to the education sector and demonstrates how Estonia’s government-run platforms, effectively cross-innovation systems linking teachers, learners and content providers in dynamic ways, could present feasible alternatives to the global platforms.

This chapter focusses on the ethical issues raised by different types of surveillance and the varied ways in which surveillance can be covert. Three case studies are presented which highlight different types of surveillance and different ethical concerns. The first case concerns the use of undercover police to infiltrate political activist groups over a 40-year period in the UK. The second case study examines a joint operation by US and Australian law enforcement agencies: the FBI’s operation Trojan Shield and the AFP’s Operation Ironside. This involved distributing encrypted phone handsets to serious criminal organisations which included a ‘backdoor’ secretly sending encrypted copies of all messages to law enforcement. The third case study analyses the use of emotional artificial intelligence systems in educational digital learning platforms for children where technology companies collect, store and use intrusive personal data in an opaque manner. The authors discuss similarities and differences in the ethical questions raised by these cases, for example, the involvement of the state versus private corporations, the kinds of information gathered and how it is used.

This study aims to identify the most significant factors that influence acceptance of e-learning in India. As e-learning has gained popularity in the wake of the COVID-19 pandemic and continues to be one of the most sustainable methods of education, it is pertinent to examine learners' perception towards its acceptance. There is limited literature available on this subject in India, especially factoring in impact of the pandemic.

This study empirically analyses data of 331 adult e-learners in India, who have enrolled for one of the following e-learning formats: higher education, private coaching, test preparation, re-skilling and online certifications, corporate training and hobby and language-related learning. Their perception is examined on the basis of a model developed using the Unified Theory of Acceptance and Use of Technology model. Data are analysed through structural equation modelling using SPSS and AMOS statistical tools.

The result of the study shows that Infrastructure Dependability, Effectiveness of Design and Content of Courses and Student's Competency with Computers are the top three factors impacting e-learning acceptance in India.

This study makes several theoretical contributions. Additionally, research findings and recommendations will facilitate education providers, corporates in the education industry and policymakers to focus on the significant areas for enhancing the acceptance of e-learning.

This study identifies and confirms important factors that influence e-learning acceptance and suggests opportunities for further in-depth research and analysis.

This chapter concludes the book on cross-innovation between audiovisual media industries and three other sectors – education, health care and tourism. It emphasises, first, the importance of platformisation as a socio-economic and technological process in framing all cross-innovation processes. It highlights how the rather full platformisation of tourism has negatively affected the interest of the tourism industry small and medium-sized enterprises to cooperate with local media and gaming industries in search of new solutions. Relatedly it proposes a generic conflict between platformisation of specific fields and the health of thematic local cross-innovation systems involving media and creative sectors. It then discusses that the inherent fragmentation of the health and education sectors has not allowed their international platformisation, but constitutes challenges to innovators interested in international scalability. It also discusses the reasons why two publicly coordinated cross-innovation processes – one involving the use of virtual reality in health care and another using augmented reality – have given different results – one a relative success and the other not as of yet. At the end of the chapter final definitions of cross-innovation are offered and the operationalisation of the term and the associated conceptual approach are assessed.