The concept of student engagement has become somewhat of an enigma for educators and researchers, with ongoing discussions about its nature and complexity, and criticism about the depth and breadth of theorising and operationalisation within empirical research (e.g. Kahn, 2014; Zepke, 2018a). The role that digital technology plays in affecting student engagement is a particular area of interest, as it has become a central feature within the student educational experience (Henderson, Selwyn and Aston, 2017; Selwyn, 2016). Recognition is growing of the importance of digital literacy and information and communications technology (ICT) skills (Organisation for Economic Co-operation and Development [OECD], 2015; Redecker, 2017), as is evidence of technology’s potential to increase self-efficacy, self-regulation and involvement within the wider educational community (Alioon and Delialioğlu, 2019; Junco, 2012). The field of educational technology has, however, lacked theoretical guidance (Antonenko, 2015; Karabulut-Ilgu, Jaramillo Cherrez and Jahren, 2018), with the operationalisation and understanding of student engagement being a particular issue (Henrie, Halverson and Graham, 2015). Calls have been made, therefore, for a strengthening of theoretical understanding and the use of theory within empirical research in the field (e.g. Hennessy et al. 2019; Hew et al. 2019), as well as for further understanding of how educational technology can affect student engagement in particular (e.g. Castañeda and Selwyn, 2018; Nelson Laird and Kuh, 2005). Although recent efforts have investigated the interplay of engagement and educational technology, these have been limited to informal learning contexts (e.g. MOOCs, see Joksimović et al. 2018) and online learning in higher education (e.g. Redmond et al. 2018).
This paper forms part of the first author’s PhD by publication, which is an exploration into the complexity of the ever-evolving concept of student engagement, in an effort to gain further understanding of how technology interacts with and affects aspects of the learning environment in both school and higher education contexts. It also forms the theoretical basis of a larger research project on student engagement and technology in higher education.1 The present paper presents a bioecological student engagement framework developed by the first author, in order to guide and ground further research on this complex topic. The model includes influences on student engagement at the macro, exo, meso and micro levels, with a particular focus on the microsystem – the student’s immediate learning environment – as this is where practitioners are able to exert the most influence. Recommendations are then provided on how the framework can be used by practitioners, and how it can help improve practice.
Student engagement has long been recognised as an enigmatic and multifaceted meta-construct (Appleton, Christenson and Furlong, 2008; Fredricks, Blumenfeld and Paris, 2004), with seminal works such as Astin’s (1999) theory of involvement and Kahu’s (2013; Kahu and Nelson, 2018) sociocultural conceptualisation of engagement, influencing ongoing conversations about the nature of and research into engagement (e.g. Boekaerts, 2016; Eccles, 2016). Often confused with motivation, which is seen as an antecedent and the force that energises behaviour (Lim, 2004; Reschly and Christenson, 2012), engagement is defined as:
The energy and effort that students employ within their learning community, observable via any number of behavioural, cognitive or affective indicators across a continuum. It is shaped by a range of structural and internal influences, including the complex interplay of relationships, learning activities and the learning environment. The more students are engaged and empowered within their learning community, the more likely they are to channel that energy back into their learning, leading to a range of short and long term outcomes, that can likewise further fuel engagement. (Bond et al. Manuscript in preparation: 2–3)
This definition arose in part out of literature stressing the importance of agentic engagement (Reeve, 2012; Reeve and Tseng, 2011); the more students have a say within their learning environment, the more engagement and achievement are likely to increase (Peters et al. 2019; Reeve, 2013; Zepke, 2018b), the more likely they are then to feedback positively into the learning environment (Matos et al. 2018). The concept of social engagement (Finn and Zimmer, 2012; Linnenbrink-Garcia, Rogat and Koskey, 2011), where students’ affect is influenced by social elements within the learning environment, is also represented within the acknowledgement of social, alongside internal, influences.
Cognitive, affective and behavioural engagement are the three widely accepted dimensions of student engagement (Fredricks et al. 2004; Fredricks, Filsecker and Lawson, 2016). Cognitive engagement relates to deep learning strategies, self-regulation and understanding; affective engagement relates to positive reactions to the learning environment, peers and teachers, as well as their sense of belonging and interest; and behavioural engagement relates to participation, persistence and positive conduct. However, each dimension of engagement comprises a range of indicators (see Table 1), experienced on a continuum at varying times (Coates, 2007; Payne, 2017), depending on their activation (low or high) and valence (positive or negative) (Pekrun and Linnenbrink-Garcia, 2012). The term ‘indicators’ is used here, following the use by Fredricks et al. (2004), and is understood in the sense of indicating or being a manifestation of student engagement and is expressed—and eventually observable and measurable—through cognitive, affective or behavioural action or reaction. The authors do, however, acknowledge that sometimes these are referred to as ‘facets’ of engagement (e.g. Coates, 2009). It is also important to note that, although not discussed at length in the present paper, disengagement needs to be included as well, when talking about engagement; not necessarily as a distinct concept, but rather as residing on the other side of a continuum of (dis)engagement, expressed either as an active action of disengaging from a learning context or even as a character trait (e.g. Chipchase et al. 2017).
|Cognitive engagement||Affective engagement||Behavioural engagement|
|Integrating ideas||Sense of belonging||Attention/focus|
|Critical thinking||Satisfaction||Developing agency|
|Setting learning goals||Curiosity||Attendance|
|Operational reasoning||Interest||Homework completion|
|Trying to understand||Sense of wellbeing||Positive conduct|
|Deep learning||Manages expectations||Participation/involvement|
|Learning from peers||Enjoyment||Asking teacher or peers for help|
|Justifying decisions||Pride||Assuming responsibility|
|Doing extra to learn more||Desire to do well||Developing multidisciplinary skills|
|Follow through/care/thoroughness||Positive interactions with peers and teachers||Supporting and encouraging peers|
|Positive self-perceptions and self-efficacy||Sense of connectedness to school/university/within classroom||Interaction (peers, teacher, content, technology)|
|Preference for challenging tasks|
|Teaching self and peers||Positive attitude about learning/values learning||Study habits/accessing course material|
|Use of sophisticated learning strategies||Time on task/staying on task/persistence|
|Positive perceptions of teacher support|
Engagement does not occur in a vacuum; rather, it is impacted and influenced by many contextual factors, and it is vital that these wider influences be considered when exploring student engagement (Appleton et al. 2008; Kahu, 2013; Quin, 2017). Within her conceptual framework of student engagement in higher education, Kahu (2013, p. 766) differentiated between sociocultural influences, such as the political and social environment; structural influences, such as the university context and student background; and psychosocial influences, such as the teaching environment, teacher-student relationships and student motivation. By considering the wider sociopolitical context that influences student engagement, a more holistic and clearer understanding of the concept can be gained, which allows educators more insight into how to further build engagement and ultimately improve outcomes for students (Appleton et al. 2008). Kahu’s framework has been criticised, however, for a lack of clear focus on what students were engaging with (Ashwin and McVitty, 2015), which resulted in a revised framework emphasising the ‘educational interface’ (Kahu and Nelson, 2018). However, given the emphasis that has been placed on the possibility of technology playing a formative role in student engagement (Coates, 2007; Nelson Laird and Kuh, 2005; Schindler et al. 2017), further theorising of how technology fits within a framework of engagement is warranted.
Bronfenbrenner and colleagues (e.g. Bronfenbrenner, 1979, 1986; Bronfenbrenner and Ceci, 1994) developed a bioecological model of external influences affecting families and child development, used to guide a range of research on child learning and parent engagement (e.g. Ansong et al. 2017; Heatly and Votruba-Drzal, 2018). This model has been particularly useful in educational practice, as it provides a conceptual framework for understanding how multiple settings and actors influence students at the same time (e.g. Sontag, 1996). Nested within a system of intertwined milieus, the individual student sits at the centre of the microsystem, which encompasses their immediate setting, e.g. classroom, or home. The mesosystem level represents the interactions between microsystems, as well as between the micro and exosystems. The exosystem includes the wider social structures that impact on the learner, such as educational institutions, the media, government, the world of work and social services, and the macrosystem encompasses the wider economic, social, legal, political and educational systems in which the other systems are located. This model was used, in conjunction with Schwab’s (1973) framework of curriculum redevelopment, to develop a bioecological model of influences on student engagement, as the theoretical framework for a case study on flipped learning in secondary classrooms (Bond, 2019). The interconnected dimensions of curriculum, students, teachers and milieus (school, classrooms, family/parents, community) within Schwab’s (1973) framework, as well as the inclusion of technology by Willis et al. (2018) in their study of parent engagement with their child’s learning, allowed the first author to visualise more easily the interconnected, fluid relationship between the external influences on student engagement. This model is a vehicle through which to explore and visualise further how technology affects student engagement.
There are a range of structural and psychosocial influences that affect the learning environment, learning processes, student engagement and subsequent outcomes at all levels of the bioecological model (see Figure 1). Drawing on educational technology literature from two systematic reviews (Bond, Manuscript in preparation; Bond et al. Manuscript in preparation), as well as wider literature, technological influences on student engagement are examined at each of the macro, exo, meso and microsystem levels.
The rapid onset of digitalisation is having, and will continue to have, a profound effect on governmental policy and educational institutions (EDUCAUSE, 2018). Each country is reacting to digital transformation in different ways, with some, e.g., Germany (see Bond et al. 2018), investing heavily in research and development, including specific funding calls for research projects. The German government sponsored higher education think tank, Hochschulforum Digitalisierung, has recognised that “the use of digital media contributes to the improvement of higher education teaching”; however, “there is no shortage of digital teaching and learning innovations at universities but their structural and strategic advancement is deficient” (Hochschulforum Digitalisierung, 2016: n.p.). Therefore, funding is being provided by the Bundesministerium für Bildung und Forschung (BMBF – German Ministry of Education and Research) on the topics of ‘Adaptive learning and assessment environments’, ‘Interactivity and multimediality of digital learning environments’, ‘Researching theory and practice in digital learning environments’, and digitalisation in higher education (Bundesministerium für Bildung und Forschung, Referat Digitaler Wandel in der Bildung, 2018), alongside peer-to-peer coaching for institution leaders and educators, to implement digital learning strategies and develop technological pedagogical skills. These projects will inform teaching and learning, and influence technology integration (infrastructure) and application (within the classroom) (Hochschulforum Digitalisierung, 2016).
In Australia, digitalisation has meant the introduction of a National Broadband Network (NBN), in an attempt to “bridge the digital divide” (NBN Co., 2018: 2), as well as boost the national gross domestic product. However, the process has been marred by cost blowouts (Tucker, 2015) and delays (Alizadeh, 2017), with Australia still lagging well behind other nations in Internet speed, ranked 50th in the world (Akamai, 2017). This has had implications for families, especially those in rural areas where the NBN has yet to roll out and/or who cannot afford to buy credit on pre-paid Internet dongles or mobile phones. For example, within a case study on the flipped learning approach in rural South Australia (Bond, 2019), a lack of access to the NBN has contributed to reduced parent engagement with students’ learning and within the school community, as well as having had a direct impact on students’ ability to engage with their learning.
Institutions that develop a culture of student success, with high expectations of both students and staff, and that invest in support services and infrastructure, such as reliable Internet connections and technology (e.g. desktop computers, wifi repeaters), are far more likely to promote positive student engagement (Almarghani and Mijatovic, 2017; Peters et al. 2019; Umbach and Wawrzynski, 2005; Zepke, 2018a). Institutional leadership and attitudes have a direct bearing on student learning, as well as on teacher attitudes towards using educational technology (Cheng and Weng, 2017). This includes institutional policies on teacher professional development and the expectation of technology use within teaching and learning (Gerick, Eickelmann and Bos, 2017), policies about staffing of classes (Hill and Tyson, 2009), which may impede the development of effective relationships between educators, students and their families, as well as policies on student technology use, such as Bring Your Own Device (BYOD) programs (Adhikari, Mathrani and Scogings, 2016). It is particularly important to remain cognisant of potential digital divide issues (Adams Becker et al. 2018), including student ownership and use of devices that are incompatible with institutional devices, as this can impact participation and engagement (Bond, 2019).
The mesosystem level reflects the relationships between elements of the exosystem and the microsystem. However, it also represents a student’s background and social milieu (Eng, Szmodis and Mulsow, 2014), and the interplay of their (family) socioeconomic status and geographical location. This can impact on family income and their ability to afford devices (Adhikari et al. 2016; Hohlfeld, Ritzhaupt and Barron, 2010; Warschauer and Xu, 2018), as well as their access to the Internet (Beckmann, 2010; Bond, 2019), and thereby affect their attitudes towards technology (Hollingworth et al. 2011). Therefore, it is vital that low-cost hardware and software are made available to students and families, to reduce this digital divide (Adams Becker et al. 2018; Daniels and Holtman, 2014), but also that institutions conduct needs analyses, so as to deepen understanding of real and potential barriers for students and families (Education Endowment Foundation, 2018; Goodall and Vorhaus, 2011). Further ideas for increasing technology access include opening up computer labs to students and families (Lewin and Luckin, 2010) or establishing loan equipment schemes (Hohlfeld et al. 2010).
The microsystem technology-enhanced learning environment is reflective of other models that have focused on the relationship between learner-teacher-content (Bundick et al. 2014; Martin and Bolliger, 2018; Moore, 1989), including interaction with peers, teachers, authentic and worthwhile tasks (Kearsley and Shneiderman, 1998; Lim, 2004), and technology (Koehler and Mishra, 2005). These ‘external’ relationships, or the ‘inter-individual factors’ (Bundick et al. 2014), play a vital role in ongoing student wellbeing, sense of connectedness, engagement and success (Aldridge and McChesney, 2018; Wimpenny and Savin-Baden, 2013). It is also important to consider that a student’s life load, including employment, health, finances and family problems, can impact the amount that a student can become actively involved within school or university life (Baron and Corbin, 2012), and to recognise that there are ‘internal’ psychosocial influences (see Figure 2), or ‘intra-individual factors’, that influence student engagement. These include a student’s self-concept, skills, motivation, self-efficacy, self-regulation, subject/discipline interest and wellbeing (Bandura, 1995; Reschly and Christenson, 2012; Zepke, 2014), as well as their prior technology experience and acceptance (Moos and Azevedo, 2009), as negative feelings about technology are related to disengagement (Bartle, Longnecker and Pegrum, 2011; Howard, Ma and Yang, 2016).
There are a variety of factors that influence student engagement when using technology (see Figure 3). Students’ access to technology is an issue, which may also impact on their level of confidence and prior level of experience (Zweekhorst and Maas, 2015). Assuming that technology and the Internet can be accessed, the provision of technical (and sometimes emotional) support is necessary, to ensure not losing students along the way due, for example, to anxiety of receiving lower grades as a result of technology issues (Mejia, 2016). Potential problems can be mitigated through introductory sessions to the technology being used (Shepherd and Hannafin, 2011) or having a continuous technical support team present (Levin, Whitsett and Wood, 2013). Providing thorough and clear explanations of how technology is to be used (Lim, 2004; Peck, 2012; Salaber, 2014), including an emphasis on using ICT for self-directed learning (Sumuer, 2018), and why it is being employed in a specific course setting (Cakir, 2013; Northey et al. 2015; Skinner, 2009) is also helpful, if not necessary, to ensure student engagement. Consideration should be given to allowing students a choice in which technologies are used (Martin and Bolliger, 2018), as familiar technology can eradicate issues of low technology confidence (Northey et al. 2018). Including out-of-class technology activities in assessment has also been shown to improve engagement and student buy-in (Northey et al. 2018; Zhu, 2006).
Engagement is more likely to develop when student-teacher relationships are strong (Martin and Bolliger, 2018; Quin, 2017; Zepke and Leach, 2010; Zhang and Aasheim, 2011) and when students perceive the teacher to be knowledgeable, supportive, invested and effective (Beer, Clark and Jones, 2010; Zhu, 2006) (see Figure 4). Teachers are more likely to employ and be successful using technology when they are confident that they have the skills to use it (Jääskelä, Häkkinen and Rasku-Puttonen, 2017; Marcelo and Yot-Domínguez, 2019). Ongoing professional development is crucial to ensure that teachers have the requisite technology knowledge and skills, and can actually foster student engagement (Bigatel and Williams, 2015). Providing regular, personalised, clear and constructive feedback can also enhance engagement (Ma et al. 2015; Martin and Bolliger, 2018; Whipp and Lorentz, 2009) and influence student agency (Coates, 2007), alongside the use of humour within online discussions (Imlawi, Gregg and Karimi, 2015). By giving feedback in the form of asking questions, students are encouraged to reflect more deeply (Alcaraz-Salarirche et al. 2011). Providing ongoing encouragement to students to contact teachers proactively when needed has also been found to be particularly effective (Leese, 2009), as has providing ongoing attention and follow-up with students (Zhang et al. 2014).
The learner-content relationship is crucial (Xiao, 2017). Therefore content that is relevant and challenging (Bundick et al. 2014; Cakir, 2013; Coates, 2007), and taught using active and collaborative learning techniques (Almarghani and Mijatovic, 2017; Umbach and Wawrzynski, 2005; Wimpenny and Savin-Baden, 2013), has been shown to be highly effective at promoting student engagement (see Figure 5). Designing meaningful learning activities is essential, relating directly to students and/or content. For example, Abate, Gomes and Linton (2011) stress the importance of choosing appropriate and meaningful questions when using audience response systems, to avoid student disengagement. It is important to avoid redundantly doubling up on activities, such as using both online journals and online discussions (Ruckert et al. 2014), and activities should be related to real life (e.g. Alshaikhi and Madini, 2016), as this makes them more useful to students. Likewise, ensuring that technology-enhanced activities are of high quality was found to be one aspect to engage students successfully, the lack of it resulting in students asking for “greater content rigor, depth, and relevancy” (Eick and King Jr., 2012: 29) in, for example, YouTube videos used in class.
Creating learning communities in which students can interact collaboratively with others to build effective peer-peer relationships—with or without technology—is extremely valuable to engagement (Nelson Laird and Kuh, 2005; Northey et al. 2015; Zepke and Leach, 2010) (see Figure 6). Students who collaborate actively in the group space, as part of the flipped learning approach, for example, have been found to experience deeper learning, increased confidence and greater achievement (D’addato and Miller, 2016; de Araujo, Otten and Birisci, 2017; Grypp and Luebeck, 2015; Lee, 2018). Yildiz (2009), in her investigation of social presence in the online classroom, found that knowing what class members look like and having well-meaning social interactions, was conducive to increased confidence and sense of knowing each other. However, students in the study by Sullivan and Longnecker (2014, p. 397) referred to the course requirement of having to post comments to fellow students’ blogs as “the worst aspect of the blog”. Thus, peer interaction, and the value and meaning attached to it, is strongly related to how learning activities and digital tools are designed and used within a course.
Family relationships, level of parent education, and parental involvement and engagement with student learning can play a large role in student engagement (Diogo, Silva and Viana, 2018; Doctoroff and Arnold, 2017; Howell, 2013) (see Figure 7), as well as in students’ motivation towards schooling (Heatly and Votruba-Drzal, 2018), achievement (Castro et al. 2015; Hill and Tyson, 2009), self-efficacy (Vekiri, 2010) and psychological wellbeing (Wong et al. 2018). In particular, families can also affect the level of student involvement with, use of and attitude towards technology (Krause, 2014; Stevenson, 2008), with students also often learning their computing skills from their parents (Ihme and Senkbeil, 2017).
Enhanced student engagement through using technology can lead to a number of short and long term academic and social outcomes (see Figure 8), termed proximal and distal consequences by Kahu (2013). Short term outcomes include increased discipline specific knowledge and higher order thinking skills (Nelson Laird and Kuh, 2005; Salaber, 2014), increased motivation (Akbari et al. 2016), enhanced sense of belonging and wellbeing (Lear, Ansorge and Steckelberg, 2010), and improved relationships through peer-to-peer learning and collaboration (Zweekhorst and Maas, 2015). Long term outcomes include lifelong learning (Karabulut-Ilgu et al. 2018), enhanced personal development (Alioon and Delialioğlu, 2019), and increased involvement in the wider educational community (Chen, Lambert and Guidry, 2010; Junco, 2012).
Bringing these ideas together, the following framework shows the interplay between the TEL microsystem, student engagement and ensuing outcomes (see Figure 9). It reflects the definition of student engagement initially provided, whereby engagement is influenced by a range of internal and external factors. The more students are engaged and empowered within their learning community, the more likely it is that engagement will lead to a range of outcomes, and the more likely it is that this energy, effort and engagement will then feed back into the activities and learning environment.
In this article, the authors have synthesised a range of student engagement and educational technology literature, and sought to present an in-depth analysis of a bioecological student engagement framework, conceptualising how educational technology can influence engagement in the K-12 and higher education classroom. Although the body of literature exploring the interplay between student engagement and technology continues to grow, there is an obvious gap in its theoretical understanding and grounding (e.g. Henrie et al. 2015). With its focus on the macro, exo, meso and micro levels, this framework zooms in on the microsystem of the classroom and its constituents—these are also ultimately the factors that can be impacted by educators and further elaborated on by educational research. Owing to a lack of space in the present paper, further work is needed to examine the macro, exo and meso levels. Although the framework presented in this contribution is only one way of viewing this complex phenomenon, it offers a clear conceptual structure that other researchers, instructional designers, policy advisors and practitioners may find useful, and could help guide future student engagement research.
By understanding the range of influences on student engagement, researchers could choose to focus on how certain factors affect engagement, and use the model presented here to frame their investigation and subsequent results discussion. So too, research may focus on one or all three engagement dimensions (e.g. cognitive engagement), and/or individual or multiple indicators of engagement (e.g. critical thinking and learning from peers). Using the first author’s flipped learning case study as an example (Bond, 2019), the bioecological model was used to frame the results and identify recommendations for schools on successful flipped learning implementation. A new model was then presented, which clearly reflected the influences pertaining to that particular case study. The merit of applying a strong theoretical grounding and framework for analysing student engagement and educational technology is in substantiating research, which is still, however, lacking (Castañeda and Selwyn, 2018). For example, the results of an extensive review of educational technology literature revealed that only 174 of 503 studies (35%) actually used a theoretical framework (Hew et al. 2019), and much research specifically investigating student engagement lacked appropriate definition and operationalisation (Henrie et al. 2015). As Antonenko (2015, p. 53) concisely states, “conceptual frameworks should be viewed as an instrument for organizing inquiry and creating a compelling theory-based and data-driven argument for the importance of the problem, rigor of the method, and implications for further development of theory and enhancement of practice”.
The model presented in this paper is of interest to practitioners to raise and focus their attention to the different layers of their students’ environments. Although most educators have this perspective, this model places technology as an integral part of this environment, identifying it as an influential factor, that can equally be influenced through the educator in his or her practice. Whereas educators are able to influence the meso and macrosystem components only marginally, they do have the power and responsibility to ensure that the microsystem is set up in a way that is conducive to student engagement—especially in regard to using educational technology. This involves reflection on their own ability and confidence in using technology, as well as seeing themselves as facilitators and initiators of technology use within (and outside of) the classroom, as stressed in the analysis of the microsystem components of the framework presented here. Practitioners are encouraged to use the figures provided in this paper (e.g. Figure 4) to conduct periodic (self-)assessments, reflecting on the extent to which these factors are having a positive influence.
Providing ongoing support to enable students’ actual use of technology, as well as ensuring instructor presence throughout the course, has been seen as a crucial element for engaged students. As has been argued, the integration of educational technology facilitates engagement if students find it meaningful, related to real life, and can act without anxiety. In this context, providing opportunities for students to engage agentically in their learning, through activity and technology choice, as well as through collaborative activities, can also enhance engagement. Through thoughtful engagement with and application of technology, and by providing students with opportunities for active participation, student engagement can be nurtured.
1See http://www.researchgate.net/project/Facilitating-student-engagement-with-digital-media-in-higher-education-ActiveLeaRn for further information.
This research resulted from the ActiveLearn project, funded by the Bundesministerium für Bildung und Forschung (BMBF—German Ministry of Education and Research) [grant number 16DHL1007].
The authors have no competing interests to declare.
The first author conducted the literature review and developed the framework. The second author contributed to the conceptualisation of the microsystem. Both authors wrote the conclusion and developed the overall flow of the paper.
Abate, LE, Gomes, A and Linton, A. 2011. Engaging Students in Active Learning: Use of a Blog and Audience Response System. Medical Reference Services Quarterly, 30(1): 12–18. DOI: https://doi.org/10.1080/02763869.2011.540206
Adhikari, J, Mathrani, A and Scogings, C. 2016. Bring Your Own Devices classroom. Interactive Technology and Smart Education, 13(4): 323–343. DOI: https://doi.org/10.1108/ITSE-04-2016-0007
Akamai. 2017. Akamai’s State of the Internet Q1 2017 Report. Available at https://www.akamai.com/uk/en/multimedia/documents/state-of-the-internet/q1-2017-state-of-the-internet-connectivity-report.pdf [Accessed 15 July 2019].
Akbari, E, Naderi, A, Simons, R-J and Pilot, A. 2016. Student engagement and foreign language learning through online social networks. Asian-Pacific Journal of Second and Foreign Language Education, 1(1): 1–22. DOI: https://doi.org/10.1186/s40862-016-0006-7
Alcaraz-Salarirche, N, Gallardo-Gil, M, Herrera-Pastor, D and Serván-Núñez, MJ. 2011. An action research process on university tutorial sessions with small groups: presentational tutorial sessions and online communication. Educational Action Research, 19(4): 549–565. DOI: https://doi.org/10.1080/09650792.2011.625713
Aldridge, JM and McChesney, K. 2018. The relationships between school climate and adolescent mental health and wellbeing: A systematic literature review. International Journal of Educational Research, 88: 121–145. DOI: https://doi.org/10.1016/j.ijer.2018.01.012
Alioon, Y and Delialioğlu, Ö. 2019. The effect of authentic m-learning activities on student engagement and motivation. British Journal of Educational Technology, 50(2): 655–668. DOI: https://doi.org/10.1111/bjet.12559
Alizadeh, T. 2017. The NBN: how a national infrastructure dream fell short. Available at http://theconversation.com/the-nbn-how-a-national-infrastructure-dream-fell-short-77780 [Accessed 15 July 2019].
Almarghani, EM and Mijatovic, I. 2017. Factors affecting student engagement in HEIs – it is all about good teaching. Teaching in Higher Education, 22(8): 940–956. DOI: https://doi.org/10.1080/13562517.2017.1319808
Alshaikhi, D and Madini, AA. 2016. Attitude toward Enhancing Extensive Listening through Podcasts Supplementary Pack. English Language Teaching, 9(7): 32–47. DOI: https://doi.org/10.5539/elt.v9n7p32
Ansong, D, Okumu, M, Bowen, GL, Walker, AM and Eisensmith, SR. 2017. The role of parent, classmate, and teacher support in student engagement: Evidence from Ghana. International Journal of Educational Development, 54: 51–58. DOI: https://doi.org/10.1016/j.ijedudev.2017.03.010
Antonenko, PD. 2015. The instrumental value of conceptual frameworks in educational technology research. Educational Technology Research and Development, 63(1): 53–71. DOI: https://doi.org/10.1007/s11423-014-9363-4
Appleton, JJ, Christenson, SL and Furlong, MJ. 2008. Student engagement with school: Critical conceptual and methodological issues of the construct. Psychology in the Schools, 45(5): 369–386. DOI: https://doi.org/10.1002/pits.20303
Ashwin, P and McVitty, D. 2015. The meanings of student engagement: Implications for policies and practices. In: Curaj, A, Matei, L, Pricopie, R, Salmi, J and Scott, P (eds.), The European Higher Education Area, 343–359. Cham: Springer International Publishing. DOI: https://doi.org/10.1007/978-3-319-20877-0_23
Bandura, A. 1995. Exercise of personal and collective efficacy in changing societies. In: Bandura, A (ed.), Self-efficacy in Changing Societies, 1–45. Cambridge: Cambridge University Press. DOI: https://doi.org/10.1017/CBO9780511527692.003
Baron, P and Corbin, L. 2012. Student engagement: Rhetoric and reality. Higher Education Research & Development, 31(6): 759–772. DOI: https://doi.org/10.1080/07294360.2012.655711
Bartle, E, Longnecker, N and Pegrum, M. 2011. Collaboration, contextualisation and communication using new media: Introducing podcasting into an undergraduate chemistry class. International Journal of Innovation in Science and Mathematics Education, 19(1): 16–28.
Beckmann, EA. 2010. Learners on the move: Mobile modalities in development studies. Distance Education, 31(2): 159–173. DOI: https://doi.org/10.1080/01587919.2010.498081
Beer, C, Clark, K and Jones, D. 2010. Indicators of engagement. In: Steel, CH, Keppell, MJ, Gerbic, P and Housego, S (eds.), Curriculum, technology & transformation for an unknown. Proceedings ascilite Sydney 2010, 75–86.
Boekaerts, M. 2016. Engagement as an inherent aspect of the learning process. Learning and Instruction, 43: 76–83. DOI: https://doi.org/10.1016/j.learninstruc.2016.02.001
Bond, M. 2019. Flipped learning and parent engagement in secondary schools: A South Australian case study. British Journal of Educational Technology, 50(3): 1294–1319. DOI: https://doi.org/10.1111/bjet.12765
Bond, M, Marín, VI, Dolch, C, Bedenlier, S and Zawacki-Richter, O. 2018. Digital transformation in German higher education: student and teacher perceptions and usage of digital media. International Journal of Educational Technology in Higher Education, 15(1): 1–20. DOI: https://doi.org/10.1186/s41239-018-0130-1
Bronfenbrenner, U. 1986. Ecology of the family as a context for human development: Research perspectives. Developmental Psychology, 22(6): 723–742. DOI: https://doi.org/10.1037/0012-16126.96.36.1993
Bronfenbrenner, U and Ceci, SJ. 1994. Nature-Nurture Reconceptualized in Developmental Perspective: A Bioecological Model. Psychological Review, 101(4): 568–586. DOI: https://doi.org/10.1037/0033-295X.101.4.568
Bundesministerium für Bildung und Forschung, Referat Digitaler Wandel in der Bildung. 2018. Bildung digital. Digitale Hochschulbildung. Available at https://www.bmbf.de/de/digitale-hochschullehre-2417.html [Accessed 20 April 2018].
Cakir, H. 2013. Use of blogs in pre-service teacher education to improve student engagement. Computers & Education, 68: 244–252. DOI: https://doi.org/10.1016/j.compedu.2013.05.013
Castañeda, L and Selwyn, N. 2018. More than tools? Making sense of the ongoing digitizations of higher education. International Journal of Educational Technology in Higher Education, 15(1): 211. DOI: https://doi.org/10.1186/s41239-018-0109-y
Castro, M, Expósito-Casas, E, López-Martín, E, Lizasoain, L, Navarro-Asencio, E and Gaviria, JL. 2015. Parental involvement on student academic achievement: A meta-analysis. Educational Research Review, 14: 33–46. DOI: https://doi.org/10.1016/j.edurev.2015.01.002
Chen, P-SD, Lambert, AD and Guidry, KR. 2010. Engaging online learners: The impact of web-based learning technology on college student engagement. Computers & Education, 54(4): 1222–1232. DOI: https://doi.org/10.1016/j.compedu.2009.11.008
Cheng, Y-H and Weng, C-W. 2017. Factors influence the digital media teaching of primary school teachers in a flipped class: A Taiwan case study. South African Journal of Education, 37(1): 1–12. DOI: https://doi.org/10.15700/saje.v37n1a1293
Chipchase, L, Davidson, M, Blackstock, F, Bye, R, Colthier, P, Krupp, N, Dickson, W, Turner, D and Williams, M. 2017. Conceptualising and Measuring Student Disengagement in Higher Education: A Synthesis of the Literature. International Journal of Higher Education, 6(2): 31. DOI: https://doi.org/10.5430/ijhe.v6n2p31
Coates, H. 2007. A model of online and general campus-based student engagement. Assessment & Evaluation in Higher Education, 32(2): 121–141. DOI: https://doi.org/10.1080/02602930600801878
Daniels, AD and Holtman, LB. 2014. The Use of Artefact Production to Achieve Learning Objectives in a Second-Year Zoology Course at an Institute of Higher Learning. Mediterranean Journal of Social Sciences, 5(6): 263–272. DOI: https://doi.org/10.5901/mjss.2014.v5n6p263
de Araujo, Z, Otten, S and Birisci, S. 2017. Mathematics teachers’ motivations for, conceptions of, and experiences with flipped instruction. Teaching and Teacher Education, 62: 60–70. DOI: https://doi.org/10.1016/j.tate.2016.11.006
Doctoroff, GL and Arnold, DH. 2017. Doing homework together: The relation between parenting strategies, child engagement, and achievement. Journal of Applied Developmental Psychology, 48: 103–113. DOI: https://doi.org/10.1016/j.appdev.2017.01.001
Eccles, J. 2016. Engagement: Where to next? Learning and Instruction, 43: 71–75. DOI: https://doi.org/10.1016/j.learninstruc.2016.02.003
Education Endowment Foundation. 2018. Working with parents to support children’s learning. Available at https://educationendowmentfoundation.org.uk/tools/guidance-reports/working-with-parents-to-support-childrens-learning/ [Accessed 18 July 2019].
Educause. 2018. Report from the 2018 EDUCAUSE Task Force on Digital Transformation. Available at https://library.educause.edu/resources/2018/11/report-from-the-2018-educause-task-force-on-digital-transformation [Accessed 18 July 2019].
Eng, S, Szmodis, W and Mulsow, M. 2014. Cambodian Parental Involvement. The Elementary School Journal, 114(4): 573–594. DOI: https://doi.org/10.1086/675639
Finn, J and Zimmer, K. 2012. Student engagement: What is it? Why does it matter? In: Christenson, SL, Reschly, AL and Wylie, C (eds.), Handbook of Research on Student Engagement, 97–131. Boston, MA: Springer US.
Fredricks, JA, Blumenfeld, PC and Paris, AH. 2004. School engagement: Potential of the concept, state of the evidence. Review of Educational Research, 74(1): 59–109. DOI: https://doi.org/10.3102/00346543074001059
Fredricks, JA, Filsecker, M and Lawson, MA. 2016. Student engagement, context and adjustment: Addressing definitional, measurement, and methodological issues. Learning and Instruction, 43: 1–4. DOI: https://doi.org/10.1016/j.learninstruc.2016.02.002
Gerick, J, Eickelmann, B and Bos, W. 2017. School level predictors for the use of ICT in schools and students’ CIL in international comparison. Large-scale Assessments in Education, 5(5): 1–13. DOI: https://doi.org/10.1186/s40536-017-0037-7
Goodall, J and Vorhaus, J. 2011. Review of best practice in parental engagement. Available at https://www.gov.uk/government/publications/review-of-best-practice-in-parental-engagement [Accessed 18 July 2019].
Grypp, L and Luebeck, J. 2015. Rotating Solids and Flipping Instruction. Mathematics Teacher, 109(3): 186–193. DOI: https://doi.org/10.5951/mathteacher.109.3.0186
Heatly, MC and Votruba-Drzal, E. 2018. Developmental precursors of engagement and motivation in fifth grade: Linkages with parent- and teacher-child relationships. Journal of Applied Developmental Psychology, 60: 144–156. DOI: https://doi.org/10.1016/j.appdev.2018.09.003
Henderson, M, Selwyn, N and Aston, R. 2017. What works and why? Student perceptions of ‘useful’ digital technology in university teaching and learning. Studies in Higher Education, 42(8): 1567–1579. DOI: https://doi.org/10.1080/03075079.2015.1007946
Hennessy, S, Mavrikis, M, Girvan, C, Price, S and Winters, N. 2019. BJET Editorial for the 50th Anniversary Volume in 2019: Looking back, reaching forward. British Journal of Educational Technology, 50(1): 5–11. DOI: https://doi.org/10.1111/bjet.12730
Henrie, CR, Halverson, LR and Graham, CR. 2015. Measuring student engagement in technology-mediated learning: A review. Computers & Education, 90: 36–53. DOI: https://doi.org/10.1016/j.compedu.2015.09.005
Hew, KF, Lan, M, Tang, Y, Jia, C and Lo, CK. 2019. Where is the “theory” within the field of educational technology research? British Journal of Educational Technology, 50(3): 956–971. DOI: https://doi.org/10.1111/bjet.12770
Hill, NE and Tyson, DF. 2009. Parental involvement in middle school: A meta-analytic assessment of the strategies that promote achievement. Developmental Psychology, 45(3): 740–763. DOI: https://doi.org/10.1037/a0015362
Hochschulforum Digitalisierung. 2016. Discussion Paper. 20 Theses on Digital Teaching and Learning in Higher Education. Working Paper No. 18. Berlin: Hochschulforum Digitalisierung. Available at https://hochschulforumdigitalisierung.de/sites/default/files/dateien/HFD_AP_Nr%2018_Discussion_Paper.pdf [Accessed 19 July 2019].
Hohlfeld, TN, Ritzhaupt, AD and Barron, AE. 2010. Connecting schools, community, and family with ICT: Four-year trends related to school level and SES of public schools in Florida. Computers & Education, 55(1): 391–405. DOI: https://doi.org/10.1016/j.compedu.2010.02.004
Hollingworth, S, Mansaray, A, Allen, K and Rose, A. 2011. Parents’ perspectives on technology and children’s learning in the home: Social class and the role of the habitus. Journal of Computer Assisted Learning 27(4): 347–360. DOI: https://doi.org/10.1111/j.1365-2729.2011.00431.x
Howard, SK, Ma, J and Yang, J. 2016. Student rules: Exploring patterns of students’ computer-efficacy and engagement with digital technologies in learning. Computers & Education, 101: 29–42. DOI: https://doi.org/10.1016/j.compedu.2016.05.008
Ihme, JM and Senkbeil, M. 2017. Why Adolescents Cannot Realistically Assess Their Own Computer-Related Skills. Zeitschrift Fur Entwicklungspsychologie Und Padagogische Psychologie, 49(1): 24–37. DOI: https://doi.org/10.1026/0049-8637/a000164
Imlawi, J, Gregg, D and Karimi, J. 2015. Student engagement in course-based social networks: The impact of instructor credibility and use of communication. Computers & Education, 88: 84–96. DOI: https://doi.org/10.1016/j.compedu.2015.04.015
Jääskelä, P, Häkkinen, P and Rasku-Puttonen, H. 2017. Teacher beliefs regarding learning, pedagogy, and the use of technology in higher education. Journal of Research on Technology in Education, 49(3–4): 198–211. DOI: https://doi.org/10.1080/15391523.2017.1343691
Joksimović, S, Poquet, O, Kovanović, V, Dowell, N, Mills, C, Gašević, D, Dawson, S, Graesser, AC and Brooks, C. 2018. How Do We Model Learning at Scale? A Systematic Review of Research on MOOCs. Review of Educational Research, 88(1): 43–86. DOI: https://doi.org/10.3102/0034654317740335
Junco, R. 2012. The relationship between frequency of Facebook use, participation in Facebook activities, and student engagement. Computers & Education, 58(1): 162–171. DOI: https://doi.org/10.1016/j.compedu.2011.08.004
Kahn, P. 2014. Theorising student engagement in higher education. British Educational Research Journal, 40(6): 1005–1018. DOI: https://doi.org/10.1002/berj.3121
Kahu, ER. 2013. Framing student engagement in higher education. Studies in Higher Education, 38(5): 758–773. DOI: https://doi.org/10.1080/03075079.2011.598505
Kahu, ER and Nelson, K. 2018. Student engagement in the educational interface: Understanding the mechanisms of student success. Higher Education Research & Development, 37(1): 58–71. DOI: https://doi.org/10.1080/07294360.2017.1344197
Karabulut-Ilgu, A, Jaramillo Cherrez, N and Jahren, CT. 2018. A systematic review of research on the flipped learning method in engineering education. British Journal of Educational Technology, 49(3): 398–411. DOI: https://doi.org/10.1111/bjet.12548
Koehler, M and Mishra, P. 2005. What happens when teachers design educational technology? The development of Technological Pedagogical Content Knowledge. Journal of Educational Computing Research, 32(2): 131–152. DOI: https://doi.org/10.2190/0EW7-01WB-BKHL-QDYV
Krause, L. 2014. Examining Stakeholder Perceptions of Accessibility and Utilization of Computer and Internet Technology in the Selinsgrove Area School District, Drexel University. Available at https://eric.ed.gov/?id=ED569546 [Accessed 7 August 2019].
Lee, M-K. 2018. Flipped classroom as an alternative future class model? implications of South Korea’s social experiment. Educational Technology Research and Development, 66(3): 837–857. DOI: https://doi.org/10.1007/s11423-018-9587-9
Leese, M. 2009. Out of class—out of mind? The use of a virtual learning environment to encourage student engagement in out of class activities. British Journal of Educational Technology, 40(1): 70–77. DOI: https://doi.org/10.1111/j.1467-8535.2008.00822.x
Levin, S, Whitsett, D and Wood, G. 2013. Teaching MSW Social Work Practice in a Blended Online Learning Environment. Journal of Teaching in Social Work, 33(4–5): 408–420. DOI: https://doi.org/10.1080/08841233.2013.829168
Lewin, C and Luckin, R. 2010. Technology to support parental engagement in elementary education: Lessons learned from the UK. Computers & Education, 54(3): 749–758. DOI: https://doi.org/10.1016/j.compedu.2009.08.010
Lim, C. 2004. Engaging learners in online learning environments. TechTrends, 48(4): 16–23. DOI: https://doi.org/10.1007/BF02763440
Linnenbrink-Garcia, L, Rogat, TK and Koskey, KLK. 2011. Affect and engagement during small group instruction. Contemporary Educational Psychology, 36(1): 13–24. DOI: https://doi.org/10.1016/j.cedpsych.2010.09.001
Ma, J, Han, X, Yang, J and Cheng, J. 2015. Examining the necessary condition for engagement in an online learning environment based on learning analytics approach: The role of the instructor. The Internet and Higher Education, 24: 26–34. DOI: https://doi.org/10.1016/j.iheduc.2014.09.005
Marcelo, C and Yot-Domínguez, C. 2019. From chalk to keyboard in higher education classrooms: changes and coherence when integrating technological knowledge into pedagogical content knowledge. Journal of Further and Higher Education, 43(7): 975–988. DOI: https://doi.org/10.1080/0309877X.2018.1429584
Martin, F and Bolliger, DU. 2018. Engagement matters: Student perceptions on the importance of engagement strategies in the online learning environment. Online Learning, 22(1): 205–222. DOI: https://doi.org/10.24059/olj.v22i1.1092
Matos, L, Reeve, J, Herrera, D and Claux, M. 2018. Students’ agentic engagement predicts longitudinal increases in perceived autonomy-supportive teaching: The squeaky wheel gets the grease. The Journal of Experimental Education, 86(4): 579–596. DOI: https://doi.org/10.1080/00220973.2018.1448746
Moore, MG. 1989. Editorial: Three types of interaction. American Journal of Distance Education, 3(2): 1–7. DOI: https://doi.org/10.1080/08923648909526659
Moos, DC and Azevedo, R. 2009. Learning With Computer-Based Learning Environments: A Literature Review of Computer Self-Efficacy. Review of Educational Research, 79(2): 576–600. DOI: https://doi.org/10.3102/0034654308326083
NBN, Co. 2018. The Corporate Plan 2019–22. Available at https://www.nbnco.com.au/content/dam/nbnco2/2018/documents/media-centre/corporate-plan-report-2019-2022.pdf [Accessed 19 July 2019].
Nelson Laird, TF and Kuh, GD. 2005. Student experiences with information technology and their relationship to other aspects of student engagement. Research in Higher Education, 46(2): 211–233. DOI: https://doi.org/10.1007/s11162-004-1600-y
Northey, G, Bucic, T, Chylinski, M and Govind, R. 2015. Increasing student engagement using asynchronous learning. Journal of Marketing Education, 37(3): 171–180. DOI: https://doi.org/10.1177/0273475315589814
Northey, G, Govind, R, Bucic, T, Chylinski, M, Dolan, R and van Esch, P. 2018. The effect of “here and now” learning on student engagement and academic achievement. British Journal of Educational Technology, 49(2): 321–333. DOI: https://doi.org/10.1111/bjet.12589
OECD. 2015. Schooling Redesigned. OECD Publishing. Available at https://www.oecd.org/education/schooling-redesigned-9789264245914-en.htm [Accessed 19 July 2019].
Payne, L. 2017. Student engagement: Three models for its investigation. Journal of Further and Higher Education, 3(2): 1–17. DOI: https://doi.org/10.1080/0309877X.2017.1391186
Peck, JJ. 2012. Keeping it Social: Engaging Students Online and in Class. Asian Social Science, 8(14): 81–90. DOI: https://doi.org/10.5539/ass.v8n14p81
Pekrun, R and Linnenbrink-Garcia, L. 2012. Academic Emotions and Student Engagement. In: Christenson, SL, Reschly, AL and Wylie, C (eds.), Handbook of Research on Student Engagement, 259–282. Boston, MA: Springer US. DOI: https://doi.org/10.1007/978-1-4614-2018-7_12
Peters, H, Zdravkovic, M, João Costa, M, Celenza, A, Ghias, K, Klamen, D, Mossop, L, Rieder, M, Devi Nadarajah, V, Wangsaturaka, D, Wohlin, M and Weggemans, M. 2019. Twelve tips for enhancing student engagement. Medical Teacher, 41(6): 632–637. DOI: https://doi.org/10.1080/0142159X.2018.1459530
Quin, D. 2017. Longitudinal and contextual associations between teacher–student relationships and student engagement. Review of Educational Research, 87(2): 345–387. DOI: https://doi.org/10.3102/0034654316669434
Redecker, C. 2017. European Framework for the Digital Competence of Educators: DigCompEdu. DOI: https://doi.org/10.2760/159770
Redmond, P, Heffernan, A, Abawi, L, Brown, A and Henderson, R. 2018. An online engagement framework for higher education. Online Learning, 22(1): 183–204. DOI: https://doi.org/10.24059/olj.v22i1.1175
Reeve, J. 2012. A self-determination theory perspective on student engagement. In: Christenson, SL, Reschly, AL and Wylie, C (eds.), Handbook of Research on Student Engagement. 149–172. Boston, MA: Springer US. DOI: https://doi.org/10.1007/978-1-4614-2018-7_7
Reeve, J. 2013. How students create motivationally supportive learning environments for themselves: The concept of agentic engagement. Journal of Educational Psychology, 105(3): 579–595. DOI: https://doi.org/10.1037/a0032690
Reeve, J and Tseng, C-M. 2011. Agency as a fourth aspect of students’ engagement during learning activities. Contemporary Educational Psychology, 36(4): 257–267. DOI: https://doi.org/10.1016/j.cedpsych.2011.05.002
Reschly, AL and Christenson, SL. 2012. Jingle, jangle, and conceptual haziness: Evolution and future directions of the engagement construct. In: Christenson, SL, Reschly, AL and Wylie, C (eds.), Handbook of Research on Student Engagement, 3–19. Boston, MA: Springer US. DOI: https://doi.org/10.1007/978-1-4614-2018-7_1
Ruckert, E, McDonald, PL, Birkmeier, M, Walker, B, Cotton, L, Lyons, LB, Straker, HO and Plack, MM. 2014. Using Technology to Promote Active and Social Learning Experiences in Health Professions Education. Online Learning, 18(4): 1–21. DOI: https://doi.org/10.24059/olj.v18i4.515
Salaber, J. 2014. Facilitating student engagement and collaboration in a large postgraduate course using wiki-based activities. The International Journal of Management Education, 12(2): 115–126. DOI: https://doi.org/10.1016/j.ijme.2014.03.006
Schindler, LA, Burkholder, GJ, Morad, OA and Marsh, C. 2017. Computer-based technology and student engagement: a critical review of the literature. International Journal of Educational Technology in Higher Education, 14(1): 25. DOI: https://doi.org/10.1186/s41239-017-0063-0
Schwab, JT. 1973. The Practical 3: Translation into Curriculum. The School Review, 81(4): 501–522. DOI: https://doi.org/10.1080/00220272.2013.798838
Selwyn, N. 2016. Digital downsides: Exploring university students’ negative engagements with digital technology. Teaching in Higher Education, 21(8): 1006–1021. DOI: https://doi.org/10.1080/13562517.2016.1213229
Skinner, E. 2009. Using community development theory to improve student engagement in online discussion: A case study. ALT-J: Research in Learning Technology, 17(2): 89–100. DOI: https://doi.org/10.1080/09687760902951599
Sontag, JC. 1996. Toward a Comprehensive Theoretical Framework for Disability Research. The Journal of Special Education, 30(3): 319–344. DOI: https://doi.org/10.1177/002246699603000306
Stevenson, O. 2008. Ubiquitous presence, partial use: The everyday interaction of children and their families with ICT. Technology, Pedagogy and Education, 17(2): 115–130. DOI: https://doi.org/10.1080/14759390802098615
Sullivan, M and Longnecker, N. 2014. Class blogs as a teaching tool to promote writing and student interaction. Australasian Journal of Educational Technology, 30(4): 390–401. DOI: https://doi.org/10.14742/ajet.322
Sumuer, E. 2018. Factors related to college students’ self-directed learning with technology. Australasian Journal of Educational Technology, 34(4): 29–43. DOI: https://doi.org/10.14742/ajet.3142
Tucker, R. 2015. What will the NBN really cost? The Conversation, 1 December. Available at https://theconversation.com/what-will-the-nbn-really-cost-51562 [Accessed 19 July 2019].
Umbach, PD and Wawrzynski, MR. 2005. Faculty do matter: The role of college faculty in student learning and engagement. Research in Higher Education, 46(2): 153–184. DOI: https://doi.org/10.1007/s11162-004-1598-1
Vekiri, I. 2010. Socioeconomic differences in elementary students’ ICT beliefs and out-of-school experiences. Computers & Education, 54(4): 941–950. DOI: https://doi.org/10.1016/j.compedu.2009.09.029
Warschauer, M and Xu, Y. 2018. Technology and Equity in Education. In: Voogt, J, Knezek, G, Christensen, R and Lai, K-W (eds.), Second Handbook of Information Technology in Primary and Secondary Education, 1063–1079. Cham: Springer International Publishing. DOI: https://doi.org/10.1007/978-3-319-71054-9_76
Whipp, JL and Lorentz, RA. 2009. Cognitive and social help giving in online teaching: An exploratory study. Educational Technology Research and Development, 57(2): 169–192. DOI: https://doi.org/10.1007/s11423-008-9104-7
Willis, L-D, Povey, J, Hodges, J and Carroll, A. 2018. PES – Parent engagement in schools. Brisbane, QLD, Australia: The University of Queensland, Institute for Social Science Research. Available at https://issr.uq.edu.au/parent-engagement-schools [Accessed 8 January 2019].
Wimpenny, K and Savin-Baden, M. 2013. Alienation, agency and authenticity: A synthesis of the literature on student engagement. Teaching in Higher Education, 18(3): 311–326. DOI: https://doi.org/10.1080/13562517.2012.725223
Wong, RSM, Ho, FKW, Wong, WHS, Tung, KTS, Chow, CB, Rao, N, Chan, KL and Ip, P. 2018. Parental Involvement in Primary School Education: Its Relationship with Children’s Academic Performance and Psychosocial Competence through Engaging Children with School. Journal of Child and Family Studies, 27(5): 1544–1555. DOI: https://doi.org/10.1007/s10826-017-1011-2
Xiao, J. 2017. Learner-content interaction in distance education: The weakest link in interaction research. Distance Education, 38(1): 123–135. DOI: https://doi.org/10.1080/01587919.2017.1298982
Yildiz, S. 2009. Social Presence in the Web-Based Classroom: Implications for Intercultural Communication. Journal of Studies in International Education, 13(1): 46–65. DOI: https://doi.org/10.1177/1028315308317654
Zepke, N. 2014. Student engagement research in higher education: Questioning an academic orthodoxy. Teaching in Higher Education, 19(6): 697–708. DOI: https://doi.org/10.1080/13562517.2014.901956
Zepke, N. 2018a. Student engagement in neo-liberal times: What is missing? Higher Education Research & Development, 37(2): 433–446. DOI: https://doi.org/10.1080/07294360.2017.1370440
Zepke, N. 2018b. Learning with peers, active citizenship and student engagement in Enabling Education. Student Success, 9(1): 61–73. DOI: https://doi.org/10.5204/ssj.v9i1.433
Zepke, N and Leach, L. 2010. Improving student engagement: Ten proposals for action. Active Learning in Higher Education, 11(3): 167–177. DOI: https://doi.org/10.1177/1469787410379680
Zhang, A and Aasheim, C. 2011. Academic success factors: An IT student perspective. Journal of Information Technology Education: Research, 10: 309–331. DOI: https://doi.org/10.28945/1518
Zhang, H, Song, W, Shen, S and Huang, R. 2014. The effects of blog-mediated peer feedback on learners’ motivation, collaboration, and course satisfaction in a second language writing course. Australasian Journal of Educational Technology, 30(6): 670–685. DOI: https://doi.org/10.14742/ajet.860
Zhu, E. 2006. Interaction and cognitive engagement: An analysis of four asynchronous online discussions. Instructional Science, 34(6): 451–480. DOI: https://doi.org/10.1007/s11251-006-0004-0
Zweekhorst, MBM and Maas, J. 2015. ICT in higher education: Students perceive increased engagement. Journal of Applied Research in Higher Education, 7(1): 2–18. DOI: https://doi.org/10.1108/JARHE-02-2014-0022