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The rapid advancement of Education Technology (EdTech) offers promising opportunities for educational institutions to integrate sustainable business practices into their operations and curriculum. The integration of EdTech into sustainability education has emerged as a powerful tool to promote environmental awareness, foster sustainable behavior, and address the pressing challenges of climate change and resource depletion. This chapter explores the growing significance of EdTech in sustainability education, analyzing its potential to cultivate a generation of environmentally conscious and responsible global citizens. It also aims at identifying and examining the most prominent emerging EdTech tools specifically designed to promote sustainability in educational settings. Furthermore, it aims to comprehend the institutional elements that have successfully incorporated and expanded the utilization of EdTech tools to promote enduring business practices. Additionally, the chapter addresses the challenges and obstacles faced by educational institutions in adopting and implementing these technologies and propose strategies to overcome these barriers.

Today the research area on technology acceptance is mainly dependent on the theory of technology acceptance model (TAM). The TAM was used in this study primarily for the purpose of providing a basis for determining the impact of various external variables on the adoption of edtech platforms. The TAM is a theory of information systems that suggests steps for learners to take as they adopt and use new technologies. The primary TAM variables for adoption of edtech platforms are evaluated in this study: perceived usefulness (PU) and perceived ease of use (PEOU) by using the factors – perceived enjoyment (PE), information quality, electronic-word of mouth (e-WOM), perceived compatibility, computer self-efficacy and objective usability. By analyzing and defining the relationship between the external variables with respect to the adoption of edtech platform among students, we hope to contextualize the TAM model. The end result provides a clearer understanding of TAM and its growth as a useful model for technology adoption studies and for clarifying the relationship between the uptake of edtech platforms and technological acceptability. The study employed a qualitative methodology and selected publications and research papers about the adoption of technology. These were then carefully assessed, analyzed and scrutinized for the terms of how students adopted edtech platforms. It was proposed that the adoption of an edtech platform may result from proper training in technology usage and its application to real-world scenarios.

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.

Purpose: Post COVID-19 disruptions, a new era of online education has begun in India providing new opportunities for imparting quality education. This study aims to explore, identify and understand the factors motivating students to enrol in online courses and facilitate decision-making for students, EdTech firms and policymakers at government level.

Methodology: The study used predominantly a qualitative research design drawing data from students pursuing graduation/post-graduation from universities in the Delhi NCR region. In the first phase, 10 groups with 8–10 members were formulated, and focus group discussions were held. The deliberations were analyzed to identify and screen factors influencing their choice to enrol in online courses. In the second phase, identified factors were presented to the students for giving their rankings to identified factors.

Findings: The student inputs in focus group discussions led to identification of factors, namely low cost, convenience, accessibility, quality education, personalized attention, availability of expert faculty, scholarship opportunities, attractive course design, availability of internet technologies like Google Meet, credibility of degree, usefulness of knowledge and skills learnt and value of online courses towards employability.

Research Limitations/Implications: The study is limited to students from the Delhi NCR region. Thus, findings cannot be generalized for other regions.

Originality/Value: Existing literature suggests that no study has been conducted in India to explore factors influencing student choice of online education. The growth of EdTech companies and government inclination towards online education necessitates research on student perceptions of online courses.

This chapter examines the key features of online education development, its trends in the world market and, in particular, in the Chinese market, as a successful case of digitalization of education (the annual growth rate of the e-learning market in China on average is 20%). Based on the example of China, the authors identify several drivers of online education growth, including institutional (national education policy), technological (technological potential to introduce digital technologies into education) and financial (inflows of investment, including venture capital, in this industry).

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.

Background: Artificial intelligence (AI) is a booming sector that has profoundly influenced every walk of life, and the education sector is no exception. In education, AI has helped to develop novel teaching and learning solutions that are currently being tested in various contexts. Businesses and governments across the globe have been pouring money into a wide array of implementations, and dozens of EdTech start-ups are being funded to capitalise on this technological force. The penetration of AI in classroom teaching is also a profound matter of discussion. These have garnered massive amounts of student big data and have a significant impact on the life of both students and educators alike.

Purpose: The prime focus of this chapter is to extensively review and analyse the vast literature available on the utilities of AI in health care, learning, and development. The specific objective of thematic exploration of the literature is to explicate the principal facets and recent advances in the development and employment of AI in the latter. This chapter also aims to explore how the EdTech and healthcare–education sectors would witness a paradigm shift with the advent and incorporation of AI.

Design/Methodology/Approach: To provide context and evidence, relevant publications were identified on ScienceDirect, PubMed, and Google Scholar using keywords like AI, education, learning, health care, and development. In addition, the latest articles were also thoroughly reviewed to underscore recent advances in the same field.

Results: The implementation of AI in the learning, development, and healthcare sector is rising steeply, with a projected expansion of about 50% by 2022. These algorithms and user interfaces economically facilitate efficient delivery of the latter.

Conclusions: The EdTech and healthcare sector has great potential for a spectrum of AI-based interventions, providing access to learning opportunities and personalised experiences. These interventions are often economic in the long run compared to conventional modalities. However, several ethical and regulatory concerns should be addressed before the complete adoption of AI in these sectors.

Originality/Value: The value in exploring this topic is to present a view on the potential of employing AI in health care, medical education, and learning and development. It also intends to open a discussion of its potential benefits and a remedy to its shortcomings.

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.

During the Coronavirus crisis (COVID-19) that started in 2019 and at the extensive quarantine regulations, educational institutions, companies, and individuals have reacted by shifting their teaching and learning activities to virtual spaces. Yet, although the use of online learning has increased, it has not been able to achieve the long-promised transformative effect. The COVID-19 crisis has the potential to boost online education overall or at least enable better preparation of the system for the next crisis. Ultimately, to make a digital transformation sustainable, appropriate skills are required. In this study, we adapt the dynamic capabilities foundations creating a theoretical approach to explain how educational institutions have responded to the changing environmental conditions during the COVID-19 pandemic.