Perspective Chapter: Educational Technology under Scrutiny in Higher Education – A Framework for Balancing Environmental, Economic and Social Aspects in a Blended Design

Abstract

Following COVID-19, higher education (HE) has recognised the importance of educational technology (EdTech). With its growing influence on educational design, awareness of its role and impact on the sustainability transition in HE from an economic, environmental and social perspective is needed. Taking a holistic view, this chapter shows the opportunities and drawbacks of using EdTech in HE aiming at developing suggestions for responsible application. Economically, there are concerns because the earnings models of for-profit EdTech companies are focused on obtaining user data and benefit from a lack of transparency in data use, privacy and intellectual property. Environmentally, the use of EdTech can reduce the carbon footprint of HE institutions by opening a virtual space where students can learn and faculty can attend international conferences without commuting or travelling (by plane). However, device disposal and the energy consumption of hardware and data storage must be considered. Socially, using EdTech can foster the development of sustainability competencies if thoughtfully designed by applying pedagogical design principles for sustainability-oriented blended learning. Higher education can take control of a balanced use of EdTech in educational practice by focusing on ethical and human values and adopting a whole-institution approach to sustainability as included in the proposed framework.

1. Introduction

Climate urgency requires everyone to reduce their emissions of greenhouse gas (GHG). Human activities have already evoked global warming with global surface temperature reaching 1.1°C above the temperature measured in 1850–1900 compared to 2011–2020 due to GHG emissions [1]. To mitigate climate change, the world needs a sustainable development approach aimed “to take the bold and transformative steps which are urgently needed to shift the world onto a sustainable and resilient path” ([2], p. 3).

Sustainable Development entails more than taking environmental measures. Already in 1987, the World Commission on Environment and Development (WCED) stated that “economics and ecology must be completely integrated into decision-making and lawmaking processes not just to protect the environment, but also to protect and promote development” [3] (Chapter II, 42) and also that environmental and economic problems are linked to social and political factors. Balancing economic, social and environmental factors served as a premise for the subsequent United Nations (UN) processes culminating in the Sustainable Development Goals (SDGs) [2].

In this chapter, we adopt the same premise for sustainability to study the affordances and drawbacks of educational technology (EdTech) in higher education (HE). EdTech companies are defined “as all the privately owned companies currently involved in the financing, production and distribution of commercial hardware, software, cultural goods, services and platforms for the educational market with the goal of turning a profit” ([4], p. 113). An important part of this educational market are the HE institutions.

1.1 Higher education

Higher education institutions are embedded in local communities linked with industry and business and are globally interconnected with other HE institutions so they have a wide stakeholder community. In many countries since the 1980s and 1990s, HE has been a major part of national strategies to achieve international competitive advantage in ‘knowledge-based economies’ [5]. As such, HE can play a major part in the sustainability challenges of this climate-changed world [6]. But HE’s role of creating value for the knowledge economy has “gradually shifted to an ideal of the ‘data-intensive’ and ‘digital-first university’ of the twenty-first century that creates valuable new digital knowledge and develops digital data skills to support emerging capitalist data economies” ([5], p. 13). One can imagine this development is beneficial to EdTech companies or even encouraged by these (for-profit) companies. Still, the implications for a sustainable society of an academic environment infused with digital technology, data analytics and artificial intelligence are not clear.

Higher education is more than an institution creating and disseminating knowledge. Its purpose is to provide for ‘good education’. In the context of sustainability, good education means acquiring the sustainability competencies needed to address the complex challenges this world faces creating a sustainable future. Competencies are a combination of knowledge, skills and attitudes, needed to accomplish the desired educational outcome [7]. HE should “bring students into a transformational relationship to professional and/or disciplinary knowledge that changes their sense of who they are, how they understand the world, and what they can do to change it” ([5], p. 72). So, this is more than learning digital competency (i.e. using information and communication technology (ICT) and digital devices to accomplish the desired outcome) to support the economy. Students should be well equipped to contribute to an economy that incorporates financial and non-financial values and strives for broad prosperity, i.e. acknowledging the importance of nature, environment, social cohesion, leisure time and happiness [8].

In the coming years, HE must find a balance in how to provide good education using digital technology to its own benefit and that of its students. There are promising opportunities.

1.2 Opportunities of digital technology

Using digital technology, students get a virtual space for their learning next to the physical space they already have when learning at their institution. In this virtual space, students have an abundance of knowledge at their disposal through the internet and they can interact or collaborate with their fellow students or anyone all over the world without the boundaries of time and place. These digital communication affordances may widen the horizon for students because perspectives of students from different disciplinary, national and cultural backgrounds can be taken into account when having group discussions and developing interpersonal or transboundary competencies [9, 10].

Place independence of learning may also provide environmental advantages. When organising on-campus education on fewer days per week, it may decrease the commute of students and campus facilities use [11, 12]. Considering the carbon footprint of a HE institution, the emissions due to student/staff travel and electricity purchased for campus facilities are the largest contributors [11, 13, 14]. On the other side, electronic equipment and infrastructure needed for educational technology also have an impact on the environment through the electricity consumed and the electronic waste (e-waste) generated [13].

In this chapter, we elaborate further on these issues. We balance the economic interests, the environmental dilemmas and the educational quality of EdTech, to end with a Framework for Sustainable Application of EdTech in HE and conclusions.

2. Balancing environmental, economic and educational factors of EdTech

2.1 EdTech and economic interests

The early 1990s are considered to be the beginning of EdTech with the involvement of large tech companies and influential private equity investors. Picciano and Spring [15] define it as the start of “The Great American Education-Industrial Complex”. It is an ominous characterisation as an industrial complex is a socioeconomic concept wherein businesses become entwined in societal or political systems and institutions, creating or bolstering a profit economy from these systems. Such a complex is said to pursue its own interests regardless of, and often at the expense of, the best interests of society and individuals. This development intensified during and after the COVID-19 pandemic in which new networks, coalitions and alliances were established and the commercialisation and privatisation of education increased [16].

2.1.1 Influence of EdTech companies

The networks, coalitions and alliances of EdTech companies increase their influence on government and HE. An example of such an alliance is the collaboration in several projects between the Norwegian Centre for ICT in Education, an executive agency of the Norwegian Ministry of Education and Research, and the New Media Consortium (NMC) [16]. This consortium was founded in 1993 by a group of hardware manufacturers, software developers and publishers. Although NMC has strong alliances with digital media and technology partners, such as Adobe, Apple, Intel and Pearson, their partnership with a governmental organisation was never under discussion. NMC’s influence extends even further with the publication of the so-called Horizon Reports. These yearly reports give NMC’s view on future technology trends in educational environments. For many HE institutions, this is a valuable resource for their educational technology procurement decisions [16]. In addition, academic articles often use publications from the Horizon Reports as background information. The 2020 EDUCAUSE Horizon Report mentions four future scenarios looking forward to the year 2030. In all four scenarios, digital technology plays a major role, transforming higher education into a more flexible, inclusive and personalised organisation, focused on teaching the skills the industry needs. In three of the four scenarios, this is at the expense of Humanities studies. In the most positive scenario Transformation, the student gets an artificial intelligence (AI) companion to “provide oversight, nudging, adaptive mentoring, research assistance, feedback on assignments, and friendly encouragement” (p. 36).

The EdTech marketing strategy is based on the certainty that technology will be needed in future for environmentally sustainable forms of teaching and learning. To make this proposition more attractive, EdTech entrepreneurs promise a ‘technological fix’ to societal problems facing higher education, such as the accessibility of education or having fewer resources for educational purposes due to budget cuts [4]. Particularly during the COVID-19 pandemic, the strategy of making alliances, problem-solving promises, predictions of needing educational technology and the ‘emergency remote teaching’ experiences [17] have not hurt EdTech companies. Because of the pandemic, the investments have grown exponentially. HolonIQ , an education market intelligence company, has calculated that the global venture capital investment in EdTech grew from US$ 500 million in 2010 to US$ 20 billion in 2021 [18]. Around 2020, research identified 20 EdTech unicorns in the world, of which 17 were spread between China and the United States (US) [19] and this number grew to 30 companies in 2023 with a combined value of over US$ 89 billion [20]. An unicorn is a private startup company valued at over US$ 1 billion. It is privately owned and not listed on a share market. That means that the transparency of its strategies and activities is limited. Because of the startup characteristics, the main goal of the private investors is to create the highest return on investment (ROI) in the shortest time possible.

2.1.2 Earnings models of EdTech companies

The platform model seems to have the greatest potential to increase profits for EdTech companies [18]. A digital educational platform creates a virtual space for teachers and students where information can be shared, resources for teaching and learning can be found and assignments can be uploaded. These platforms, also called learning management systems (LMSs), need regular upgrading with new features, can be integrated with other platform services and continuously extract digital data, creating a reliable revenue stream for investors [18]. Digital data gain value through processes like extracting meaningful information, enclosing it, storing, aggregating, analysing and transforming it into intelligence. This encompasses various sources, ranging from scholarly discussions in virtual learning environments to user behaviour data, including click-throughs on platforms, as well as metadata detailing users’ devices, location and internet protocol addresses [19, 21].

The earnings model for for-profit companies is increasingly based on assetisation: creating assets that can be an endless means for returns. In practice, this results in “[charging] subscription fees for access to educational services and resources (monetary rent), integrating together in cross-platform ecosystems, and deriving value from user data through the creation of derivative products (data rent)” ([22], p. 6). Assetisation is not risk-free as privacy issues are just around the corner. The “use of deep neural networks within assetisation can by its very nature be not inspectable and thus inherently opaque. It involves complex, multi-stage decisions hard to scrutinise with human oversight” ([21], p. 21). There are multiple options for creating a return on student platform data. Student platform data might be sold to other companies for advertising purposes or, potentially, for enabling employers to identify and target students with promising competencies [22]. In Europe, the Digital Services Act is meant to protect online users’ rights, filter illegal and harmful content, create new transparency for platform practices and ban targeted advertising to children [23]. Although the new regulations apply to countries that belong to the European Union (EU), it affects EdTech companies globally.

In addition to selling to external partners, data may also be used to improve educational services. Student platform data are the building blocks for Artificial Intelligence for EDucation (AIED) and learning analytics (LA). LA is “the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimising learning and the environments in which it occurs” ([24], p. 34). AI-based methods can turn student data into digital information to establish an individual and adaptive learning system based on the teaching and learning behaviour of the user [25]. As LA is used to improve the learning process, the purpose of AIED is to simulate and predict learning processes, think of making admission decisions, assessment and feedback, intelligent tutoring, profile and prediction of students dropping out [26].

Despite these promising opportunities, HE seems reluctant to implement LA or AIED solutions [25]. A constraining factor for the adoption of LA or AIED seems to be the advanced digital competencies a teacher needs to improve their teaching methods with AI-based functionalities [21, 25]. AI-based methods analyse the pattern of collected student platform data for developing the algorithms that can support the individual learner. These patterns may contain race, gender or other biases. In addition, the constant monitoring of students’ digital behaviour on the platform increases surveillance and can amplify feelings of stress and anxiety around their loss of autonomy [5]. Williamson and Hogan [5] express their concern about this feeling of autonomy loss: “They are building robotised pedagogic environments in which key functions of teaching, such as observing student progress, providing feedback, scaffolding intellectual development, and assessment, are increasingly delegated to or augmented by automated AI technologies”. These and other ethical concerns are acknowledged by international organisations, such as the United Nations Educational, Scientific and Cultural Organization (UNESCO). Although on 25 November 2021, 169 countries agreed on global standards for AI ethics, these are still in the recommendations stage [27, 28] and some EdTech companies complain about the vagueness of the proposed ethical principles [29]. Nguyen et al. [27] have gathered the ethical guidelines for AIED from the different reports and proposed several key ethical principles. One of these principles handles the need for transparency in data usage and accountability in AIED and LA:

“Principle of transparency in data and algorithms: The process of collecting, analysing, and reporting data should be transparent with informed consent and clarity of data ownership, accessibility, and the purposes for how data will be used. The AI algorithms should be explainable and justifiable for specific educational purposes.” ([27], p. 4229).

The development of AI-based solutions becomes even more complex as there is not much generalisable, valid and reliable evidence gathered in research [25]. The European Union is not awaiting this research. In December 2023, the European Parliament reached a political agreement on the Artificial Intelligence Act. With these regulations, they aim to ensure that AI systems respect fundamental rights, safety and ethical principles [30].

Outsourcing course delivery to an online programme management (OPM) company is another way of making a financial return with HE EdTech products. These EdTech companies, for example, Coursera, share the revenue with university partners for massive open online course (MOOC)-related activities, advertising themselves “as having social missions to mobilise new technology to transform and improve not only the reach and quality of higher education but also the life and career prospects of EdTech-facilitated learners” ([31], p. 6). Mirrlees and Alvi [4] refer to MOOC-related activities as a way of making course delivery more efficient by “automating instruction”. The learning content needs updating from time to time but online lectures can be watched multiple times. The reason this alliance is of interest to universities is that in countries worldwide the public sector, which includes education, is focused on efficiency, performance measurement, quality management, marketisation and accountability [5, 21].

Another aspect of the EdTech industry and its earnings model is the issue of intellectual property rights, particularly those of teachers working in a digital learning environment. LMS platforms contain the learning content (video lectures and teaching materials). It is unclear who has control and ownership over this content. If not regulated or contracted properly, what does that mean for academic freedom and content ownership, especially in countries with severe forms of internet censorship and surveillance? [5].

We have raised serious concerns about the involvement of EdTech companies in HE’s online learning ambition. Technological innovations seem to precede the regulations needed to guarantee privacy, autonomy and transparency issues. The European Union takes the lead in filling this gap.

Higher Education and governments should adopt a data governance policy and “have a far stronger role in setting both the educational and regulatory agenda so that education serves the interests of a whole society: children, young people and life-learners, not just private capital investors” ([32], p. 91).

It is in the interest of society that students can develop digital competency [33]. They are the future human capital of a nation. Human capital refers to the economic value of an employee’s professional competencies [33]. The use of EdTech is crucial in this development process, but HE’s policy should be aimed at a human-centred approach.

2.2 EdTech and environmental dilemmas

Educational technology might play a role in decreasing the environmental impact of higher education activities by offering online communication possibilities. It creates opportunities for place-independent delivery of education or conference presentations. This may decrease commute-related travel and international business travel [14], and electricity purchased for campus facilities [11]. In this section, we discuss its impact on HEI’s carbon footprint and the role of EdTech in adding to and reducing this carbon footprint.

2.2.1 Carbon emissions due to commute-related travel of students and staff

The environmental impact of a higher education institution (HEI) can be made transparent when measuring its carbon footprint. An internationally accepted accounting and reporting standard for companies and organisations is the Greenhouse Gas Protocol Initiative [34]. The GHG protocol classifies the emission sources into three scopes: scope 1: the direct emissions, scope 2: indirect emissions due to electricity purchased and scope 3: the indirect emissions as a consequence of HEI’s activities. So, the electricity purchased for campus facilities belongs to scope 2 emissions, whereas the GHG emissions due to student and staff commute, and business travel belong to scope 3 emissions. Various studies acknowledge the significant proportion of student and staff travel, and the electricity purchased for campus facilities on HEI’s carbon footprint [13].

Higher education students worldwide need to commute to their institutions 4 or 5 days per week. The amount of student travel emissions is dependent on how often students commute to attend classes on campus, the campus location and which travel mode they choose for travelling. The impact ranges between approximately 20 and 90 per cent of the overall carbon footprint [14, 35]. This broad range is due to dependencies on the accessibility of the campus, and the reliability and the very existence of the commute data [35].

How and which scope 3 emissions are measured is optional in the GHG protocol and in some studies, commute emissions are allocated to the individual carbon footprint of a student or staff member [36]. The reason why there might be the difficulty of obtaining reliable commute data. Data on commute behaviour can only be obtained by surveying students and staff and especially students are a difficult group to survey. Their limited response is often extrapolated to the whole university [37] or supplemented with parking data or registered student data where privacy issues come into play. Nevertheless, how difficult it may be, the commuting emissions are a direct consequence of HEI’s activities, as students and staff often need to attend obligatory classes or are required to work from campus. Moreover, HEI can influence their commuting emissions by acting appropriately [38].

Most of these measures are directed at trying to change the travel mode of students and staff from carbon-intensive (i.e. single-occupancy petrol cars) to low-carbon modes (i.e. a bicycles or e-bikes) or promoting carpooling [39] and certainly, in car-dependent countries, such as Australia or the United States, this is a well-chosen strategy [39, 40, 41], but there are other options. The Intergovernmental Panel on Climate Change (IPCC) recommends, besides a modal shift, “avoiding journeys where possible—by, for example, (…) utilizing advanced information and communication technologies (ICT)” ([42], p. 603). In HE, EdTech can offer possibilities to decrease student and staff commute [12]. These possibilities relate to the use of digital technologies to enable location-independent learning.

2.2.2 Carbon emissions due to business travel

Academic staff also need to commute but their main contribution to the carbon footprint are their visits to international conferences and seminars, often by plane [43]. These business travels can account for about 3–55 per cent of a HEI’s footprint. Digital technologies can play a role in mitigating the large amount of carbon emissions due to these meetings [44]. While one can dispute whether the digital technology required should be subsumed under the banner of EdTech, it is strongly interrelated and contributing to HE’s carbon footprint. It seems crucial for academics to keep abreast of the latest developments in their field and network in person at these events [45]. The impact and quality of research are dependent on international collaboration and these collaborations are usually initiated and sustained through physical meetings [46].

Although technically possible, as proven during the COVID-19 pandemic, a transition to fully online conferences does not seem to be a desirable solution to the problem of high-carbon transportation for attending. Nevertheless, organising these international meetings should focus on reducing carbon emissions due to travel and there are opportunities enhanced by digital technology, such as hybrid conferences [43, 47]. A large contribution to the total emissions of an international conference is due to a relatively small group of participants [47]. They could present their research and take part in discussions using remote conferencing services. Another possibility is to organise the hybrid conference at two different venues, although this may have the rebound effect that more academics will attend the conference [48]. Both solutions roughly halve travel-related emissions [47, 49].

2.2.3 Energy consumption of EdTech use

Although contributing to decreasing education-related travel emissions, EdTech services are not carbon-neutral. They generate GHG emissions due to the electricity needed to power devices. They provide the necessary video- and audio transfer, and storage data. The volume of these emissions is nation-dependent because electricity can be generated in various ways. Data from the European Environmental Agency (EEA) show that in 2020 producing 1 kWh of electricity in France emitted ca. 60 g of carbon dioxide (CO₂), whereas producing the same amount in Estonia led to 621 g of CO₂ emissions [50]. To evaluate the use of EdTech to decrease the HEI’s carbon footprint, we should compare the carbon impact of student and staff travel with the impact of EdTech use.

Regarding location-independent learning, Caird et al. [11] compared energy consumption with associated carbon emissions generated by distance-based HE teaching models with HE on-campus models. Their findings indicate that distance-based models achieve a carbon reduction of 83 per cent in comparison with on-campus models, mainly due to commute-related student travel and campus site operations [11]. The COVID-19 pandemic forced HE in countries categorised as developed economies to an immediate transition from on-campus to an online environment from home [51]. Some researchers took this opportunity to study the carbon impact of this online learning environment. There are two contradictory studies regarding the carbon impact of the increased use of energy devices needed to study or work from home. Filimonau et al. [52] stated that the carbon impact of devices used for online education was almost equal to that of staff and student commute at Bournemouth University in the United Kingdom (UK), and in China at Wuhan University, Yin et al. [53] concluded that online education can significantly reduce energy consumption and lower carbon emissions when considering transportation and electricity consumption [52, 53]. It should be noted that Filimonau et al. [52] assumed that staff and students used their devices for study or work at home 8 hours a day and 5 days per week which is, in our opinion, highly unlikely.

Clearly, more research is needed with reliable data on student travel and the additional energy required during home education. Still, the study of Yin et al. [53] confirms the results of Caird et al. [11] that online education can significantly decrease energy consumption and associated carbon emissions. HE, in their quest for carbon neutrality, could take advantage of these findings by organising education in a hybrid form (the so-called blended learning), substituting on-campus learning with online learning a few days per week. This would reduce the days students have to commute to their institution to attend classes.

2.2.4 Energy consumption and disposal issues of EdTech

In Section 2, we saw that in future, HE will probably increase the application of AIED and LA. Developing an AI model for AIED involves training deep learning models on vast amounts of data. This consumes a significant amount of energy during both training and validation and these computations have a large carbon footprint [54]. Another issue is that AIED and LA require extensive datasets, usually stored on servers in data centres. These servers not only consume a vast amount of energy to store data but also respond to data requests. Besides energy, water is extensively used for liquid cooling in these data centres [55].

The last issue we need to address in relation to EdTech is the disposal of electronic devices, adding to the generation of electronic waste (e-waste). In 2019, 53.6 million metric tonnes of e-waste was generated and only 17.4 per cent was collected and recycled [56]. E-waste is a health and environmental risk and contains toxic additives or harmful substances such as mercury, which damages the human brain and/or coordination system [56].

The environmental gains of using EdTech to decrease education-related travel (student and staff commute and business travel) are accompanied by concerns about energy consumption and e-waste disposal. Considering HE’s carbon footprint, it seems that decreasing education-related travel outweighs the energy consumption of the devices [11, 14, 53]. Nevertheless, the environmental costs of the development and use of AIED and LA should be part of an environmentally aware approach to EdTech [57].

2.3 EdTech and educational quality

Educational technology will likely play a more significant role in HE shortly, given the impact of the COVID-19 pandemic on HE and the increasing influence of EdTech on government and educational policy, The question remains how will EdTech fulfil this highly influential role? How will they pay attention to all their responsibilities: ethically and sustainably?

As we have seen in the former section, EdTech may be used to lower HE’s carbon footprint if learning activities are scheduled with a clear division between on-campus and online learning days. Thus, organising education can reduce students’ commute to attend on-campus classes. This educational model is called blended learning [58]. As the mission of HE is to provide ‘good education’, blended learning should not compromise or better still, enhance educational quality.

2.3.1 Quality assurance of blended learning

Quality assurance is a complex issue in HE. Good education is difficult to quantify, for instance, measuring the quality of a graduate student might be done by looking at their employability. But how does one measure and assess if this is due to the education this student has received [59]? Focusing on educational outcomes and performance seems hazardous for quality assurance but focusing on the learning and teaching process of how these outcomes are obtained seems to be a better approach. The E-xcellence framework describes benchmarks for quality assurance of e-learning, which are grouped into six key areas: strategic management, curriculum design, course design, course delivery, staff and student support [60].

During the COVID-19 pandemic, the rapid transition to online education in HE revealed the deficiencies in these key areas. During online course delivery, problems arose with infrastructure and availability of devices just as with lecturers’ pedagogic knowledge and experience [61]. This resulted in so-called “emergency remote teaching” [62]. Several problems are caused by the sudden transition and can be solved in time, but some are more difficult to tackle—for example, accessibility to online learning services, a quiet study environment or the well-being of students. Accessibility and study environment are dependent on students’ social-economic status. Students with a low socioeconomic background usually need HEI’s environment for the use of computers and free and fast internet to study online, undisturbed by human and pet intrusions [63, 64]. Not having access to these facilities and experiencing technological problems at home during COVID-19, aroused feelings of anxiety, anger and boredom due to not being able to hear and take the entire online class [65]. These negative emotions were also triggered by increased workload [66] and insufficient digital competency [65]. To a large extent, the severity of these problems was caused by the sudden transition to online learning but also in a carefully planned and designed blended learning unit these accessibility issues and failing technological abilities of faculty and students should be addressed.

2.3.2 Pedagogical design principles for sustainability-oriented blended learning

Zooming in on the design of blended learning, the pedagogical quality of education should not be compromised. As we live in a climate-changed world with complex sustainability challenges, students must be “capable of analysing, evaluating, and synthesizing complex issues and of applying learning in new contexts. At the same time, they appreciate the advantages of cooperating to pursue a common goal” [67]. Transformation to a sustainable world needs ‘change agents’, who are aware of what they can or want to change and know how to take action for implementation [68]. This requires a pedagogical approach that supports students in developing sustainability competencies. These competencies provide the students with the necessary knowledge and skills to analyse systems across different domains, anticipate future challenges, apply ethical values, design and implement transformative interventions and engage stakeholders in the process [68, 69]. The pedagogical design principles of Versteijlen and Wals [10] can be used to guide the design and assess the pedagogical quality of a sustainability-oriented blended learning unit. This is a learning unit organised with a clear division between on-campus and online learning days to decrease student commute and a sustainability-oriented pedagogical approach to learning. This requires a thoughtful design because it is a challenge to combine virtual and physical space in such a way that the strengths of both are exploited and complement each other.

Table 1 shows the usability of EdTech for designing sustainability-oriented blended learning by connecting the design principles of Versteijlen and Wals [10] with their relevance for learning and how EdTech can be supportive. The first two design principles are more general in nature and supportive of the last four design principles, which are about learning activities in which students interact and discuss, acquire knowledge, bring theoretical knowledge into practice and collaborate incorporating different perspectives [10, 70]. In a blended design, these learning activities should be interwoven according to the Conversational Framework of Laurillard [71]. This framework specifies the iterative reflective interactions between student-lecturer and student-fellow students on two contrasting levels: 1. articulating and discussing theory and 2. experimenting and practising on goal-oriented tasks [71].

Design principle	Relevance to learning	EdTech support
Aiming at self-regulation and self-awareness of learning and practice in the student’s learning process	In blended learning, students have more agency over where and when they study. Digital tools can stimulate the development of the necessary self-regulating skills. A reflective environment with digital and physical communication possibilities promotes creating self-awareness of one’s own values	24/7 access to the digital environment, personalised learning plans, learning management tools, online tests and quizzes, online reflective journals, virtual and augmented reality
Fostering a safe and social learning environment	Pointing to a feeling of freedom to express oneself without being afraid of failure is a prerequisite of creating self-awareness. This is best encouraged by the lecturer in the physical space and reinforced in the virtual space.	Communication platforms, social networking, global community tools, video feedback and virtual coffee shop
Facilitating (a)synchronous interaction and discussion among fellow students and with the lecturer to stimulate reflection and critical thinking	Different approaches to learning can be taken into account by offering synchronous as well as asynchronous discussions of topics or feedback.	Online debate platform, web annotation tool, video discussion platform, online tutoring, brainstorming tool
Transforming learning through acquisition and inquiry into an active process based on existing knowledge in which new knowledge is constructed to contribute to sustainability	It motivates students to acquire knowledge through their preferred (online) content representation. Inquiry stimulates system thinking competency. Data are easily accessible using the internet.	Multimedia content, online lectures, digital (formative) tests, virtual classroom, data collection, search engines, interactive tutorials, virtual and augmented reality
Working on authentic and action-oriented tasks with scaffolded and theory-based practice meeting the learning preferences of students	Transfer of learning from the classroom to the professional setting by designing online learning tasks and tools that align with the workplace setting while critically examining sustainability opportunities.	Peer feedback tools, interactive learning, virtual classroom, serious games, lab simulations, personalised assignments
Inter/transdisciplinary collaboration for constructing a shared outcome through participation and negotiation with fellow students in a technologically enhanced learning environment	Developing interpersonal competency through incorporating different perspectives in group discussions for addressing complex social, ecological, technical and other problems to bring about transformative change	Integrated team collaboration, project organisation, digital boards for organising and sharing content, wiki platform.

Table 1.

Usability of EdTech for designing sustainability-oriented blended learning. Based on the pedagogical design principles for sustainability-oriented blended learning [10, 70].

In this section, we discussed whether EdTech in a blended learning design would compromise or enhance educational quality in HE. Provided certain conditions are met, we can say that EdTech improves educational quality and is indispensable in a design for blended learning. These conditions involve the benchmarks for quality assurance of e-learning and measures to ensure the accessibility to learning and well-being of students. The relationship between HE, EdTech companies and their policies and governance should support the development of human capital this climate-changed world needs.

2.4 A sustainability-oriented perspective on EdTech in higher education

With sustainability in mind, we have balanced the drawbacks and affordances of EdTech in HE. In Figure 1, the key concepts of EdTech under scrutiny are depicted in a Framework for Sustainable EdTech Application in higher education. This framework builds upon the framework for a humanist ecosystem of higher education given in Sharma [33], but we adopt a sustainability-oriented perspective on the role of EdTech in the education system. This system is represented by the relationship between EdTech companies, HE and their governance and policies. As stated before, HE plays a crucial role in the sustainability challenges facing the world. This responsibility requires higher education to embed sustainability in all aspects of its policies, a so-called “whole-institution approach” [72]. These aspects relate to education, research, own sustainability-related behavioural practices, community engagement, leadership and ethos, and professional development of staff [73]. We can add EdTech to these aspects. This approach ensures sustainability-oriented (blended) education and research, organised in such a way that the deployment of EdTech is human-centred and environmentally aware.

Figure 1.

Framework for sustainable EdTech application in higher education. Based on the framework for a humanist ecosystem of higher education [33].

3. Conclusion

Educational Technology has become an integral part of the (higher) education system and improves education by offering students a virtual space next to the physical one where they can learn and interact with lecturers and fellow students. This transition has perhaps been accelerated by the COVID-19 pandemic and so many venture capital investors see the market potential of HE and its students who have grown used to being online continuously.

The promises and predictions of Edtech seem to be attractive, but HE institutions have to be vigilant. In this chapter, we have identified being in control and privacy issues, educational quality and sustainability focal points to which we have to pay attention when applying EdTech in HE. In this chapter, we approached EdTech from a sustainable development perspective, balancing economic, environmental and educational factors.

There is a tension between the economic interests of the for-profit EdTech companies, private owners and educational organisations. We have to be on the alert whether the EdTech companies will deliver on the promises they make or even whether those promises and predictions will get in the way of good education. The EdTech companies promise flexible and personalised education but fail to mention that EdTech is not accessible to everyone, can come at the expense of lecturer’s and student’s autonomy and raises serious privacy issues. HE’s and EdTech companies’ policies should ensure that everyone has access to their facilities and that ethical values are upheld. In addition, clarity in data usage and ownership is needed when scrutinising their earnings model of assetisation. This could lead to lower ROIs for the private investors in the EdTech companies, but it may remove some of the reservations HE has about introducing LA and AIED in their educational practices.

Considering the carbon footprint of the HEIs, one of the main sources of carbon emissions is the education-related travel of students and staff. The additional virtual space by using EdTech offers opportunities for organising education in such a way that there is a clear division between on-campus and online learning days during a week. This may reduce student commute. In addition, virtual space can be used during international conferences, decreasing business travel of staff. Still, a thoughtful mix of virtual and physical space is needed because physical encounters still add value to teaching and research. In addition, energy consumption and e-waste issues of EdTech should be considered.

A thoughtful mix can be realised in educational practice by applying the pedagogical design principles for sustainability-oriented blended learning. The experiences of online learning during COVID-19 showed that students’ emotional well-being and self-regulation were an issue but they welcomed the additional time freed up by not having the daily commute [70]. A thoughtful blended design offers ‘the best of both worlds’ and probably will improve educational quality.

The developed Framework for Sustainable EdTech Application in HE contains the most significant points when applying EdTech in educational practice. Some of the ethical issues can be resolved by acknowledging and applying standards for AI ethics [27]. However, HEIs and governments must remain vigilant on privacy and other ethical issues. EdTech use can be supportive of educational quality and sustainable organisation, but HE and Edtech companies must ensure in cooperation that human values and well-being are guaranteed.

Conflict of interest

The authors declare no conflict of interest.