Selecting our annual top 10 open-access journal articles after reviewing over 100 nominated papers for consideration is never easy and last year was no exception. Within our defined selection criteria, it’s always difficult to judge what counts as a “good read”, as this depends on your interests and perspectives. In selecting our 7th annual list of “good reads”, we are also conscious of giving profiles to some articles that appear in lesser-known publications, as they may be outside your normal reading in the digital learning area.
This point is emphasised by Macgilchrist, Potter and Williamson (2022) in their excellent article, which asks…
Who are we reading and who are we citing?
Their analysis shows some of the biases in our publication and citation practices by revealing an extensive body of literature in developing countries and/or typically outside of the better-known journals published in the English language. Whether you realise it or not, what you choose to read is a political decision or practice, which says much about your orientation to the literature. What we have attempted to do in selecting our 2022 list of “good reads” is balance the inclusion of several seminal works with those you may not have previously seen through your normal reading channels.
About this Year’s Selections
As in previous years, deciding on the order of the top 10 articles is contentious. Except for our top article, which discusses the entangled nature of pedagogy, the selection order largely reflects the narrative we develop through our brief curated remarks on each work rather than implying one article is measurably better than another. The narrative and order of articles begin with a focus on definitions and conceptual frameworks, with the first few papers addressing different ways of theorising and conceptualising the ecosystem in which digital learning inhabits.
Several of the articles help to illustrate the complexity of what might fall under the umbrella of digital learning and serve to demonstrate the importance of criticality and the role of theorical constructs and conceptual frameworks in shaping our thinking—for better and worse.
We have also included a major review article looking at the framing of learning design versus instructional design, as reflected in the literature. This article continues the focus on the importance of the explicit or implicit theories and language we use to express the nature of our work.
At this point, we pivot to a series of articles with a future-focused perspective. The first of these articles provides a thoughtful piece on the emergence of speculative education fiction as a methodology in helping to frame hopeful (and less optimistic) learning futures. This article provides a bridge to the final three papers that focus on new and emerging technological developments in digital learning.
As you will see from these articles, our selections for 2022 were influenced to some extent by the considerable interest generated late in the year by the launch of ChatGPT-3. We have chosen two major literature reviews on the use of Artificial Intelligence (AI) for teaching, learning and assessment that help to categorise and synthesize the emerging literature in this major development area. If you have a particular interest in AI in higher education, we suggest you also read from last year the systematic review of the top 50 most-cited articles written by Chu et al. (2022) and the cautionary notes Neil Selwyn (2022) offers on future developments in the area. The final article continues a futures-focus theme by providing a literature review that asks whether the Metaverse is a blessing or a curse. In many respects, the answer to this question requires readers to circle back to the entanglement thesis contained in our top article for the year.
Celebrating Open Access
We would like to acknowledge all the authors who appear in our selections and many others whose articles we reviewed in this process. This annual exercise for us is hugely valuable in taking stock of the literature and requires us to go beyond the skim reading we typically do when publications are first released over the course of the year. The decision people make to publish their work in an open-access journal, despite, in many cases, strong institutional pressures to submit manuscripts to more prestigious and higher-ranked closed publications, is a moral and political decision that we aim to strongly endorse through this exercise.
By the Numbers
A quick analysis of the top 10 “good reads” from 2022 reveals that the articles come from nine journals and collectively recognise 44 authors. This is the highest number of individual journals and authors since we began this exercise seven years ago. As Table 1 shows, three articles were written by single male authors, two by co-authors and the remaining five by multiple authors, but it’s not possible, based on names alone, to provide an accurate breakdown by gender across all 10 articles and 44 authors. However, this type of binary analysis has also become increasingly problematic.
One author, Aras Bozkurt, appears twice, which is not the first time he has been featured in our selections. Indeed, Bozhurt was a co-author of three articles in our list of “good reads” for 2021. There are 14 countries represented with seven UK-based authors, five from Finland, four from Canada, the United States and Turkey, two from France and South Africa, with the remaining authors distributed across Ireland, Spain, Palestine, China, India, Korea and Pakistan.
Thus, the “good reads” from 2022 represent a wide geographical spread of authors, although none are from Latin, South America, and Australasia. As Table 2 shows, this is the first time that the Australasian Journal of Educational Technology does not appear on the list, and notably, neither does the highly ranked International Journal of Educational Technology in Higher Education and the International Review of Research in Open and Distributed Learning feature. We believe their omission partly reflects our commitment to identifying open-access articles outside the better-known journals. Table 3 shows that for the first time the top article was published in Postdigital Science and Education, which is the only journal that contributes two paper.
The Top 10 Good Reads
Here are this year’s top 10 “good reads” with brief curated remarks to help explain why each article was selected…
No 1
Fawns, T. (2022). An entangled pedagogy: Looking beyond the pedagogy—technology dichotomy. Postdigital Science and Education, https://doi.org/10.1007/s42438-022-00302-7
This article challenges the validity of a popular slogan that has emerged in recent years—‘Pedagogy first’. It demonstrates why this is a naïve and potentially dangerous mantra to promote as it falls into the trap of pedagogical determinism and fails to recognise the entangled nature of the complex constellation of change forces influencing the current focus on digital learning. The call for ‘pedagogy first’ implies or can be misinterpreted to suggest that technology is just a tool. In this regard, the paper shows that new digital technology influences us, our institutions, and our communities as much as we can influence how technology is deployed for educational purposes. Importantly, following this point, the work also rejects deterministic language claiming that new digital technology is a force driving educational change independent from society. Put simply, the central thesis is woven around the entangled relationship between technology and pedagogy. It responds to binary discourses that do little to help us understand the reality of complexity, uncertainty, and imperfection. In looking beyond the pedagogy—technology dichotomy, an aspirational view is offered of how teachers, students and other stakeholders can engage with collective agency underpinned by values and ethics. The paper makes a valuable contribution to the literature as it demonstrates the complex interdependencies which are a reality of the many and varied educational contexts in which we work.
No 2
Johnson, N., Seaman, J., & Poulin, R. (2022). Defining different modes of learning: Resolving confusion and contention through consensus. Online Learning Journal, 26(3), 91-110. DOI: http://dx.doi.org/10.24059/olj.v26i3.3565
This article contributes to the challenge of defining what constitutes ‘digital learning’ and the many variants. The issue of definitions is not new, with a long history of contentious terms and ill-defined concepts under the historical umbrella of Educational Technology. However, the question of nomenclature has become even more topical following the COVID-19 crisis, with a renewed focus on hybrid forms of teaching and learning. The study reported in this article helps to identify how different teaching modalities and the associated terms we use to describe them largely fall into two big buckets. Importantly, these buckets represent the location in which learning primarily takes place: distance or in-person. While the proposed Modes of Learning Spectrum is unlikely to put an end to definition wars, as ‘distance learning’ is unfortunately associated with the deficit language of ‘remote learning’, and some educators might like to argue all learning is ‘in-person’ even when occurring virtually, the framework provides useful a tool for thinking about different learning experiences by mode. It also highlights the importance of being intentional about the language we use and the meanings we adopt at an institutional and sector-wide level.
No 3
Passey, D. (2022). Theories, theoretical and conceptual frameworks, models and constructs: Limiting research outcomes through misconceptions and misunderstanding. Studies in Technology Enhanced Learning, 1(1), 95-114. https://doi.org/ 10.21428/8c225f6e.56810a1a
This article is particularly relevant to research and doctoral students. The underlying premise is that any research study needs to be firmly anchored within one or more theoretical or conceptual frameworks. However, this is easier said than done and is often “considered a ‘doctoral or research challenge’ in itself” (p. 95). Importantly, the explicit or underlying models, theories or frameworks are crucial in determining how a study might (or might not) contribute to new knowledge. Framed by this assumption, the paper offers several examples of theoretical constructs in the field. It provides a valuable analysis of their roles in drawing on the literature, shaping our perspectives and contributing to new theories and understandings. Several useful recommendations are provided to ensure criticality is paramount when selecting, interpreting, developing, and applying such models, constructs, and frameworks throughout the research process. While the paper is primarily written for doctoral students or those relatively new to undertaking research, it is also valuable reading for more experienced researchers. After all, Bond et al. (2021) showed that many articles and reports published during the COVID-19 crisis lacked a deeper theoretical underpinning and fit the description of emergency remote research.
No 4
Atenas, J., Beetham, H., Bell, F., Cronin, C., Vu Henry, J., & Walji, S. (2022). Feminisms, technologies and learning: Continuities and contestations. Learning, Media and Technology, 47(1), 1-10, DOI: 10.1080/17439884.2022.2041830
This challenging article extends the call for criticality and serves as an editorial for a special issue providing a feminist perspective on learning technology. It speaks to some of the biases and marginalised voices in the literature and across theory, research, and practice. The Editorial begins by illustrating through several previous articles published almost three decades ago how concerns about equity, diversity, and inclusion (EDI) are nothing new in the literature. Indeed, the authors further argue that the gaps and structural issues have become even more hardwired as “…gender and other inequalities are encoded into the technologies we routinely use for learning and everyday life” (Eynon, 2018; cited in Atenas et al., 2022). In (re)exploring the territory and intersections between pedagogy, digital technology, and feminism, the authors anchor digital learning in wider social practice. A notable feature of the paper is a meta-discussion around the open process of editing the journal, followed by insightful commentary illustrating how feminist theory is a diverse repertoire of methods involving critique and interventions. They share a common commitment to activism and critical action for justice. Importantly, the editorial points out that feminists have not ceased to innovate and maintain their hope and resilience, as evidenced by the collection of works in the special issue.
No 5
Downes, S. (2022). Connectivism. Asian Journal of Distance Education, 17(1), 58-87. http://www.asianjde.com/ojs/index.php/AsianJDE/article/view/623
This article takes the award of having the shortest title. It provides a comprehensive overview of Connectivism, one of the most influential theoretical constructs over the previous two decades, influencing thinking about learning and how we understand knowledge in today’s digitally connected world. The central thesis of Connectivism, according to the paper, is “that knowledge is constituted of the sets of connections between entities, such that a change in one entity may result in a change in the other entity, and that learning is the growth, development, modification or strengthening of those connections” (p. 58). There has been considerable debate over the years about whether Connectivism is a new theory of learning, and the article addresses this point. It argues that this is a fundamental misunderstanding of Connectivism even though it does provide an account of learning in the digital age. At the core of the thesis is the crucial role networks and connections play in the learning process, which contribute to knowledge. Importantly, the author distinguishes his interpretation of learning from that adopted or implied by George Siemens‘ (2004) in his original seminal paper on Connectivism. It also outlines how Connectivism differs or can be distinguished from other learning theories. Close attention needs to be given to the following theoretical discussion, which describes how learning occurs. Several practical examples help to illustrate key points, concepts, and principles for the design of networks, our understanding of pedagogy and for engaging in connectivist forms of learning. In this respect, the discussion challenges what we currently measure as learning and has wider implications for how we live and learn in an interconnected world, especially as the Internet’s architecture evolves.
No 6
Saçak, B., Bozkurt, A., & Wagner, E. (2022). Learning design versus instructional design: A bibliometric study through data visualization approaches. Education Sciences, 12, 752, 1-14. https://doi.org/10.3390/educsci12110752
This article responds to the fact that ‘instructional design’ and ‘learning design’ are common terms used to describe a discipline concerned with enhancing the design of teaching, learning and assessment. While the terms share a common goal, they are not always interchangeable. Indeed, they often reflect a different underlining philosophy or approach to designing, implementing, and evaluating effective pedagogies, resources, and environments for learning. Mindful of this point, the study seeks to better understand the similarities and differences between the terms and how they have evolved by mapping the intersections and common themes using text mining and social network analysis. More specifically, a triangulated bibliometric study is reported, which analyses 514 publications (326 for instructional design and 157 for learning design) indexed in the Scopus database. In the case of instructional design, the paper reports four broad themes: Theory-driven approaches; technology-informed designs; instructional design for higher education; and assessment and evaluation. For learning design, four major themes emerged: Design thinking and user experience-driven approaches; online learning informed designs and online environments; analytical approaches for assessment and evaluation; and engagement-based learning design. In comparing these themes, the authors conclude that instructional design, as reflected in the literature, is about developing, assessing, and evaluating instruction, whereas learning design places a stronger focus on “learner engagement and experience, which can be assessed and enhanced by analytical and technological approaches” (p. 1). While the recent adoption of the term ‘learning design experience’ (LDX) is not included in this study, the paper offers a useful ‘ecosystem map’ of what the authors call the instructional and learning design metaverse.
No 7
Houlden, S., & Veletsianos, V. (2022). Impossible dreaming: On speculative education fiction and hopeful learning futures. Postdigital Science and Education. https://doi.org/10.1007/s42438-022-00348-7
This article explores the emergence of speculative fiction as a method for reimagining education futures. Set against the backdrop of the COVID-19 crisis, the authors observe that while speculative fiction offers a powerful lens for examining possible futures, including both the risks and threats and possible changes facing institutions and the education system, the methodology also informs our understanding of the present. In this sense, “futures fictions are not strictly an imagined or fictional endeavour but are concurrently somehow nonfictional in nature” (p. X). Arguably, this point is not fully reflected in some of the speculative fiction produced since the pandemic. However, this line of thinking would benefit from more explicitly anchoring the present and the future in the past. Importantly, many indigenous cultures see time as circular and interconnected with the past, such that Western conceptions of the future based on ‘clock time’ do not fit well with these worldviews. Many indigenous cultures do not distinguish the future from the past. This point raises important questions about who is currently telling the future through the median of speculative fiction. Notwithstanding this critique, the paper speaks to the issue of whose voice is being heard and recognises the power of story in a non-Western, specifically Indigenous ontology. It makes a valuable contribution to the literature by drawing our attention to an increasing tendency towards telling more negative, pessimistic, or apocalyptic stories of the future. Indeed, one of the central tenets of the article is a call to reframe speculative education fiction to develop more hopeful futures. In this respect, the paper conveys a similar message to Atenas et al. (2022) by emphasising agency and community with imagines of hope and more liberatory education futures.
No 8
Holmes, W., & Tuomi, I. (2022). State of the art and practice in AI in education, European Journal of Education, 57(4),542–570. https://doi.org/10.1111/ejed.12533
As the title indicates, this article provides a state-of-the-art account of Artificial Intelligence (AI) in education. Of course, since the article was published, the launch of ChatGPT-3 has placed even greater attention on the problems and possibilities associated with new and emerging AI platforms. Notably, at the time of writing, the authors suggest that ChatGPT-3 is posed to have an even greater impact, although they also note the training involved in producing it is “… estimated to have required as much energy as driving a car to the moon and back, thus generating an equivalent of 85,000 kg of CO2 emissions” (p. 448). The authors begin by addressing the question of what AI is and how we define it? The paper notes that “AI is a complex domain of research that includes many different conceptual approaches and domains of expertise, and sometimes emphasises the point that there is no such a thing as AI” (p. 2). After introducing several competing definitions and the debate about how it should be defined in the European context, the paper discusses an important distinction between data-driven AI and knowledge-driven AI. Importantly, readers are cautioned to be wary of grand claims or sweeping speculative predictions about AI as their validity depends on which of the multiple variations are being discussed in an educational context. To help address this issue, a typology is presented that describes different ways of using AI in education for teaching and learning with three distinct yet overlapping categories: (1) student-focused, (2) teacher-focused, and (3) institution-focused. While recognising the categories are open to conjecture, the remainder of the paper elaborates on each category, with examples of specific AI applications, including whether they are speculative, already researched or commercially available. This taxonomy is probably the most valuable contribution of the article as it describes in practical terms how AI can be applied in education in multiple ways. The discussion is solidly anchored in the literature, with the article concluding with a consideration of the roadblocks on the AI highway. This final section raises some fundamental and controversial issues, including ethics, colonialism, techno-solutionism, and the commercialisation of education, to name a few. Overall, the paper is excellent reading for people trying to make sense of the implications of AI for education, with a critical perspective on the near and longer-term future.
No 9
Celik, I., Dindar, M., Muukkonen, H., & Järvelä, S. (2022). The promises and challenges of artificial intelligence for teachers: A systematic review of research. TechTrends, 66, 616–630. https://doi.org/10.1007/s11528-022-00715-y
This article complements the above paper by providing an overview of research on teachers using artificial intelligence (AI) to support their work. It begins with several underlying premises. Firstly, AI developers know little about learning sciences and lack pedagogical knowledge for its effective implementation in education. Secondly, they often fail to take into consideration the expectations and experiences of AI end-users. Thirdly, teachers are among the most crucial stakeholders for successfully adopting AI in education. While primarily focused on the schooling sector, the basic thesis is that limited attention in AI-based education has been paid to teachers and the nature of their work, a gap in the research the study sets out to address. From the outset, the authors acknowledge that AI does not refer to a single technology and can be used in education differently, as illustrated in the above paper. Six research questions are presented, followed by a description of the literature review methodology, which identified 44 articles suitable for inclusion in this study. Not surprisingly, the authors found that research on teachers’ AI use has intensified in the last four years. In terms of the advantages AI offers teachers, the study reveals three main categories: planning, implementation, and assessment. After summarising these advantages, the paper describes some of the challenges in AI use by teachers, with few surprises based on previous educational technology research. While the study does not address some of the deeper concerns that were raised by Holmes and Tuomi (2022) and contained in last year’s special issue on AI in the European Journal of Education, it helps map the literature. It is also commendable for its strong focus on the teacher. Given the systematic literature review of AI in higher education conducted by Zawacki-Richter et al. (2019) found limited input by educators, this remains an important focus for future research.
No 10
Tlili, A., et al. (2022). Is Metaverse in education a blessing or a curse: a combined content and bibliometric analysis. Smart Learning Environments, 9(24), https://doi.org/10.1186/s40561-022-00205-x
This article claims to provide the first systematic review of the literature on the Metaverse in education. It applies content and bibliometric analysis methods to reveal this research topic’s major trends, focus, and limitations. However, before reporting the research questions, methodology and findings, the authors attempt to define the Metaverse by borrowing an educational definition they acknowledge is techno-centric based on four categories: Augmented Reality (AR), Lifelogging, Mirror Worlds, and Virtual Worlds. Two axes run across these categories: Augmentation versus Simulation and External versus Intimate. A key assumption underpinning the study is that there are generational differences in how people engage with the Metaverse as it evolves, which are worthy of further investigation. Importantly, the review found that few publications explain one or more of the Metaverse categories of technology to a high level of complexity. Moreover, the current literature is dominated by studies from higher education in the fields of Natural Science, Mathematics, and Engineering. Potentially, the most interesting aspect of the analysis relates to the proposed learning scenarios, which try to incorporate more of a pedagogical perspective. While this analysis would benefit from adopting an established pedagogical framework offering greater depth, it shows that most Metaverse applications in education are being used in virtual learning—whatever that means. The discussion then focuses on digital identities followed by a taxonomy of tools consisting of seven categories: immersive, artificial intelligence (AI), game application, educational, modelling and simulation, mobile, sensors, and wearable. Again, some of the analysis and related claims about learner motivation, generational differences, and the tools’ nature would benefit from a greater critique.
While this final paper concludes with several critical questions, a large disconnect exists between these types of systematic literature reviews, which have become increasingly popular, and the ideas put forward by Fawns (2022) and the depth of criticality in other theoretical works in this year’s selection of good reads.
The decision to include a handful of major review articles, some of which adopt a more instrumentalist approach to the field, was influenced by this disconnect. The final article, for example, serves as a useful bookend or rejoinder to our first article, as it helps to demonstrate the importance of the theoretical lenses and critical perspectives we adopt (or not) to interpreting, understanding, and shaping the use of digital learning for better futures in an ever-changing world.
Good Reads from the Closed Literature
Finally, the above selections raise the question of what was published last year in closed journals that we should have on our reading radar? As in previous years, we have identified a single article by Martin et al. (2022) from the wider collection of closed journals or those requiring a fee to access that we think is worthy of reading.
Martin, F. Sun, T., Westine, C., & Ritzhaupt, A. (2022). Examining research on the impact of distance and online learning: A second-order meta-analysis study. Educational Research Review, 6, https://doi.org/10.1016/j.edurev.2022.100438
A wider review of the closed literature is beyond our capacity, but we invite you to consider what you might include in such a list of comparative articles. This year’s chosen article offers an important meta-analysis of the research at a time when the benefits of online learning are being challenged in the post-COVID return to more traditional delivery modes. Hopefully, you can find a way of accessing this publication if your institution or organisation does not provide access.
References
Bond, M., Bedenlier, S., Marín, V.I., Händel, M. (2021). Emergency remote teaching in higher education: Mapping the first global online semester.International Journal of Educational Technology in Higher Education, 18 (50). https://doi.org/10.1186/s41239-021-00282-x
Chu, H-C., Hwang, G-H., Tu, Y-F., & Yang, K-H. (2022). Roles and research trends of artificial intelligence in higher education: A systematic review of the top 50 most-cited articles. Australasian Journal of Educational Technology, 38(3), 22-42. https://ajet.org.au/index.php/AJET/article/view/7526
Holmes, W., & Tuomi, I. (2022). State of the art and practice in AI in education, European Journal of Education, 57(4),542–570. https://doi.org/10.1111/ejed.12533
Macgilchrist, F., Potter, J., & Williamson, B. (2022). Reading internationally: If citing is a political practice, who are we reading and who are we citing? Learning, Media and Technology, 47(4), 407-412, https://doi.org/10.1080/17439884.2022.2140673
Martin, F. Sun, T., Westine, C., & Ritzhaupt, A. (2022). Examining research on the impact of distance and online learning: A second-order meta-analysis study. Educational Research Review, 6, https://doi.org/10.1016/j.edurev.2022.100438
Selwyn, N. (2022). The future of AI and education: Some cautionary notes. European Journal of Education, 57(4), 620-631. https://doi.org/10.1111/ejed.12532
Siemens, G. (2004). Connectivism: A learning theory for the digital age. International Journal of Instructional Technology & Distance Learning, 2(1). http://www.itdl.org/Journal/Jan_05/article01.htm
Zawacki-Richter, O., Marin, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education–where are the educators? International Journal of Educational Technology in Higher Education, 16(1), 39. https://doi.org/10.1186/s41239-019-0171-0
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