Introduction
Over the past decade, the conceptualisation and measurement of ‘student engagement’ has received increasing attention from researchers, practitioners, and policy makers alike. Seminal works such as Astin’s (
1999) theory of involvement, Fredricks, Blumenfeld, and Paris’s (
2004) conceptualisation of the three dimensions of student engagement (behavioural, emotional, cognitive), and sociocultural theories of engagement such as Kahu (
2013) and Kahu and Nelson (
2018), have done much to shape and refine our understanding of this complex phenomenon. However, criticism about the strength and depth of student engagement theorising remains e.g. (Boekaerts,
2016; Kahn,
2014; Zepke,
2018), the quality of which has had a direct impact on the rigour of subsequent research (Lawson & Lawson,
2013; Trowler,
2010), prompting calls for further synthesis (Azevedo,
2015; Eccles,
2016).
In parallel to this increased attention on student engagement, digital technology has become a central aspect of higher education, inherently affecting all aspects of the student experience (Barak,
2018; Henderson, Selwyn, & Aston,
2017; Selwyn,
2016). International recognition of the importance of ICT skills and digital literacy has been growing, alongside mounting recognition of its importance for active citizenship (Choi, Glassman, & Cristol,
2017; OECD,
2015a; Redecker,
2017), and the development of interdisciplinary and collaborative skills (Barak & Levenberg,
2016; Oliver, & de St Jorre, Trina,
2018). Using technology has the potential to make teaching and learning processes more intensive (Kerres,
2013), improve student self-regulation and self-efficacy (Alioon & Delialioğlu,
2017; Bouta, Retalis, & Paraskeva,
2012), increase participation and involvement in courses as well as the wider university community (Junco,
2012; Salaber,
2014), and predict increased student engagement (Chen, Lambert, & Guidry,
2010; Rashid & Asghar,
2016). There is, however, no guarantee of active student engagement as a result of using technology (Kirkwood,
2009), with Tamim, Bernard, Borokhovski, Abrami, and Schmid’s (
2011) second-order meta-analysis finding only a small to moderate impact on student achievement across 40 years. Rather, careful planning, sound pedagogy and appropriate tools are vital (Englund, Olofsson, & Price,
2017; Koehler & Mishra,
2005; Popenici,
2013), as “technology can amplify great teaching, but great technology cannot replace poor teaching” (OECD,
2015b), p. 4.
Due to the nature of its complexity, educational technology research has struggled to find a common definition and terminology with which to talk about student engagement, which has resulted in inconsistency across the field. For example, whilst 77% of articles reviewed by Henrie, Halverson, and Graham (
2015) operationalised engagement from a behavioural perspective, most of the articles did not have a clearly defined statement of engagement, which is no longer considered acceptable in student engagement research (Appleton, Christenson, & Furlong,
2008; Christenson, Reschly, & Wylie,
2012). Linked to this, educational technology research has, however, lacked theoretical guidance (Al-Sakkaf, Omar, & Ahmad,
2019; Hew, Lan, Tang, Jia, & Lo,
2019; Lundin, Bergviken Rensfeldt, Hillman, Lantz-Andersson, & Peterson,
2018). A review of 44 random articles published in 2014 in the journals
Educational Technology Research & Development and
Computers & Education, for example, revealed that more than half had no guiding conceptual or theoretical framework (Antonenko,
2015), and only 13 out of 62 studies in a systematic review of flipped learning in engineering education reported theoretical grounding (Karabulut-Ilgu, Jaramillo Cherrez, & Jahren,
2018). Therefore, calls have been made for a greater understanding of the role that educational technology plays in affecting student engagement, in order to strengthen teaching practice and lead to improved outcomes for students (Castañeda & Selwyn,
2018; Krause & Coates,
2008; Nelson Laird & Kuh,
2005).
A reflection upon prior research that has been undertaken in the field is a necessary first step to engage in meaningful discussion on how to foster student engagement in the digital age. In support of this aim, this article provides a synthesis of student engagement theory research, and systematically maps empirical higher education research between 2007 and 2016 on student engagement in educational technology. Synthesising the vast body of literature on student engagement (for previous literature and systematic reviews, see Additional file
1), this article develops “a tentative theory” in the hopes of “plot[ting] the conceptual landscape…[and chart] possible routes to explore it” (Antonenko,
2015, pp. 57–67) for researchers, practitioners, learning designers, administrators and policy makers. It then discusses student engagement against the background of educational technology research, exploring prior literature and systematic reviews that have been undertaken. The systematic review search method is then outlined, followed by the presentation and discussion of findings.
Discussion
The findings of this study confirm those of previous research, with the most prolific countries being the US, UK, Australia, Taiwan and China. This is rather representative of the field, with an analysis of instructional design and technology research from 2007 to 2017 listing the most productive countries as the US, Taiwan, UK, Australia and Turkey (Bodily, Leary, & West,
2019). Likewise, an analysis of 40 years of research in
Computers & Education (CAE) found that the US, UK and Taiwan accounted for 49.9% of all publications (Bond,
2018). By contrast, a lack of African research was apparent in this review, which is also evident in educational technology research in top tier peer-reviewed journals, with only 4% of articles published in the
British Journal of Educational Technology (
BJET) in the past decade (Bond,
2019b) and 2% of articles in the
Australasian Journal of Educational Technology (AJET) (Bond,
2018) hailing from Africa. Similar results were also found in previous literature and systematic reviews (see Table
1), which again raises questions of literature search and inclusion strategies, which will be further discussed in the limitations section.
Whilst other reviews of educational technology and student engagement have found studies to be largely STEM focused (Boyle et al.,
2016; Li et al.,
2017; Lundin et al.,
2018; Nikou & Economides,
2018), this corpus features a more balanced scope of research, with the fields of Arts & Humanities (42 studies, 17.3%) and Education (42 studies, 17.3%) constituting roughly one third of all studies in the corpus - and Natural Sciences, Mathematics & Statistics, nevertheless, assuming rank 3 with 38 studies (15.6%). Beyond these three fields, further research is needed within underrepresented fields of study, in order to gain more comprehensive insights into the usage of educational technology tools (Kay & LeSage,
2009; Nikou & Economides,
2018).
Results of the systematic map further confirm the focus that prior educational technology research has placed on undergraduate students as the target group and participants in technology-enhanced learning settings e.g. (Cheston et al.,
2013; Henrie et al.,
2015). With the overwhelming number of 146 studies researching undergraduate students—compared to 33 studies on graduate students and 23 studies investigating both study levels—this also indicates that further investigation into the graduate student experience is needed. Furthermore, the fact that 41 studies do not report on the study level of their participants is an interesting albeit problematic fact, as implications might not easily be drawn for application to one’s own specific teaching context if the target group under investigation is not clearly denominated. A more precise reporting of participants’ details, as well as specification of the study context (country, institution, study level to name a few) is needed to transfer and apply study results to practice—being then able to take into account why some interventions succeed and others do not.
In line with other studies e.g. (Henrie et al.,
2015), this review has also demonstrated that student engagement remains an under-theorised concept, that is often only considered fragmentally in research. Whilst studies in this review have often focused on isolated aspects of student engagement, their results are nevertheless interesting and valuable. However, it is important to relate these individual facets to the larger framework of student engagement, by considering how these aspects are connected and linked to each other. This is especially helpful to integrate research findings into practice, given that student engagement and disengagement are rarely one-dimensional; it is not enough to focus only on one aspect of engagement, but also to look at aspects that are adjacent to it (Pekrun & Linnenbrink-Garcia,
2012). It is also vital, therefore, that researchers develop and refine an understanding of student engagement, and make this explicit in their research (Appleton et al.,
2008; Christenson et al.,
2012).
Reflective of current conversations in the field of educational technology (Bond,
2019b; Castañeda & Selwyn,
2018; Hew et al.,
2019), as well as other reviews (Abdool et al.,
2017; Hunsu et al.,
2016; Kaliisa & Picard,
2017; Lundin et al.,
2018), a substantial number of studies in this corpus did not have any theoretical underpinnings. Kaliisa and Picard (
2017) argue that, without theory, research can result in disorganised accounts and issues with interpreting data, with research effectively “sit[ting] in a void if it’s not theoretically connected” (Kara,
2017), p. 56. Therefore, framing research in educational technology with a stronger theoretical basis, can assist with locating the “field’s disciplinary alignment” (Crook,
2019), p. 486 and further drive conversations forward.
The application of methods in this corpus was interesting in two ways. First, it is noticeable that quantitative studies are prevalent across the 243 articles in the sample. The number of studies employing qualitative research methods in the sample was comparatively low (56 studies as opposed to 84 mixed method studies and 103 quantitative studies). This is also reflected in the educational technology field at large, with a review of articles published in
BJET and
Educational Technology Research & Development (ETR&D) from 2002 to 2014 revealing that 40% of articles used quantitative methods, 26% qualitative and 13% mixed (Baydas, Kucuk, Yilmaz, Aydemir, & Goktas,
2015), and likewise a review of educational technology research from Turkey 1990–2011 revealed that 53% of articles used quantitative methods, 22% qualitative and 10% mixed methods (Kucuk, Aydemir, Yildirim, Arpacik, & Goktas,
2013). Quantitative studies primarily show that an intervention has worked or not when applied to e.g. a group of students in a certain setting as done in the study on using mobile apps on student performance in engineering education by Jou, Lin, and Tsai (
2016), however, not all student engagement indicators can actually be measured in this way. The lower numbers of affective and cognitive engagement found in the studies in the corpus, reflect a wider call to the field to increase research on these two domains (Henrie et al.,
2015; Joksimović et al.,
2018; O’Flaherty & Phillips,
2015; Schindler et al.,
2017). Whilst it is arguably more difficult to measure these two than behavioural engagement, the use of more rigorous and accurate surveys could be one possibility, as they can “capture unobservable aspects” (Henrie et al.,
2015), p. 45 such as student feelings and information about the cognitive strategies they employ (Finn & Zimmer,
2012). However, they are often lengthy and onerous, or subject to the limitations of self-selection.
Whereas low numbers of qualitative studies researching student engagement and educational technology were previously identified in other student engagement and technology reviews (Connolly et al.,
2012; Kay & LeSage,
2009; Lundin et al.,
2018), it is studies like that by Lopera Medina (
2014) in this sample, which reveal
how people perceive this educational experience and the actual
how of the process. Therefore, more qualitative and ethnographic measures should also be employed, such as student observations with thick descriptions, which can help shed light on the complexity of teaching and learning environments (Fredricks et al.,
2004; Heflin, Shewmaker, & Nguyen,
2017). Conducting observations can be costly, however, both in time and money, so this is suggested in combination with computerised learning analytic data, which can provide measurable, objective and timely insight into how certain manifestations of engagement change over time (Henrie et al.,
2015; Ma et al.,
2015).
Whereas other results of this review have confirmed previous results in the field, the technology tools that were used in the studies and considered in their relation to student engagement in this corpus deviate. Whilst Henrie et al. (
2015) found that the most frequently researched tools were discussion forums, general websites, LMS, general campus software and videos, the studies here focused predominantly on LMS, discussion forums, videos, recorded lectures and chat. Furthermore, whilst Schindler et al. (
2017) found that digital games, web-conferencing software and Facebook were the most effective tools at enhancing student engagement, this review found that it was rather
text-based tools,
knowledge organisation & sharing, and
multimodal production tools.
Limitations
During the execution of this systematic review, we tried to adhere to the method as rigorously as possible. However, several challenges were also encountered - some of which are addressed and discussed in another publication (Bedenlier,
2020b) - resulting in limitations to this study. Four large, general educational research databases were searched, which are international in scope. However, by applying the criterion of articles published in English, research published on this topic in languages other than English was not included in this review. The same applies to research documented in, for example, grey literature, book chapters or monographs, or even articles from journals that are not indexed in the four databases searched. Another limitation is that only research published within the period 2007–2016 was investigated. Whilst we are cognisant of this being a restriction, we also think that the technological advances and the implications to be drawn from this time-frame relate more meaningfully to the current situation, than would have been the case for technologies used in the 1990s see (Bond,
2019b). The sampling strategy also most likely accounts for the low number of studies from certain countries, e.g. in South America and Africa.
Studies included in this review represent various academic fields, and they also vary in the rigour with which they were conducted. Harden and Gough (
2012) stress that the appraisal of quality and relevance of studies “ensure[s] that only the most appropriate, trustworthy and relevant studies are used to develop the conclusions of the review” (p. 154), we have included the criterion of being a peer reviewed contribution as a formal inclusion criterion from the beginning. In doing so, we reason that studies met a baseline of quality as applicable to published research in a specific field - otherwise they would not have been accepted for publication by the respective community. Finally, whilst the studies were diligently read and coded, and disagreements also discussed and reconciled, the human flaw of having overlooked or misinterpreted information provided in the individual articles cannot fully be excluded.
Finally, the results presented here provide an initial window into the overall body of research identified during the search, and further research is being undertaken to provide deeper insight into discipline specific use of technology and resulting student engagement using subsets of this sample (Bedenlier,
2020a; Bond, M., Bedenlier, S., Buntins, K., Kerres, M., & Zawacki-Richter, O.: Facilitating student engagement through educational technology: A systematic review in the field of education, forthcoming).
Recommendations for future work and implications for practice
Whilst the evidence map presented in this article has confirmed previous research on the nexus of educational technology and student engagement, it has also elucidated a number of areas that further research is invited to address. Although these findings are similar to that of previous reviews, in order to more fully and comprehensively understand student engagement as a multi-faceted construct, it is not enough to focus only on indicators of engagement that can easily be measured, but rather the more complex endeavour of uncovering and investigating those indicators that reside below the surface. This also includes the careful alignment of theory and methodological design, in order to both adequately analyse the phenomenon under investigation, as well as contributing to the soundly executed body of research within the field of educational technology. Further research is invited in particular into how educational technology affects cognitive and affective engagement, whilst considering how this fits within the broader sociocultural framework of engagement (Bond,
2019a). Further research is also invited into how educational technology affects student engagement within fields of study beyond Arts & Humanities, Education and Natural Sciences, Mathematics & Statistics, as well as within graduate level courses. The use of more qualitative research methods is particularly encouraged.
The findings of this review suggest that research gaps exist with particular combinations of tools, study levels and modes of delivery. With respect to study level, the use of assessment tools with graduate students, as well as knowledge organisation & sharing tools with undergraduate students, are topics researched far less than expected. The use of text-based tools in Engineering, Health & Welfare and Natural Sciences, Mathematics & Statistics, as well as the use of multimodal production tools outside of these disciplines, are also areas for future research, as is the use of assessment tools in the fields of Education and Arts & Humanities in particular.
With 109 studies in this systematic review using a blended learning design, this is a confirmation of the argument that online distance education and traditional face-to-face education are becoming increasingly more integrated with one another. Whilst this indicates that a lot of educators have made the move from face-to-face teaching to technology-enhanced learning, this also makes a case for the need for further professional development, in order to apply these tools effectively within their own teaching contexts, with this review indicating that further research is needed in particlar into the use of social networking tools in online/distance education. The question also needs to be asked, not only why the number of published studies are low within certain countries and regions, but also to enquire into the nature of why that is the case. This entails questioning the conditions under which research is being conducted, potentially criticising publication policies of major, Western-based journals, but also ultimately to reflect on one’s search strategy and research assumptions as a Western educator-researcher.
Based on the findings of this review, educators within higher education institutions are encouraged to use text-based tools, knowledge, organisation and sharing tools, and multimodal production tools in particular and, whilst any technology can lead to disengagement if not employed effectively, to be mindful that website creation tools (blogs and ePortfolios), social networking tools and assessment tools have been found to be more disengaging than engaging in this review. Therefore, educators are encouraged to ensure that students receive sufficient and ongoing training for any new technology used, including those that might appear straightforward, e.g. blogs, and that they may require extra writing support. Ensure that discussion/blog topics are interesting, that they allow student agency, and they are authentic to students, including the use of social media. Social networking tools that augment student professional learning networks are particularly useful. Educators should also be aware, however, that some students do not want to mix their academic and personal lives, and so the decision to use certain social platforms could be decided together with students.
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