Investigating the impact of Flipped Classroom on students' learning experiences: A Self-Determination Theory approach

Sergis, Stylianos; Sampson, Demetrios G.; Pelliccione, Lina

doi:10.1016/j.chb.2017.08.011

Cited by 221 publications

(197 citation statements)

References 17 publications

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“…In the current SDT literature, autonomy support is understood as more than providing options and choices (Schuitema, Peetsma, & Veen, 2016;Sergis, Sampson, & Pelliccione, 2018). A student's sense of autonomy can be supported by explaining the relevance of learning tasks to his or her personal goals and needs when choices are constrained.…”

Section: Perceived Autonomymentioning

confidence: 99%

Why do college students continue to use mobile learning? Learning involvement and self‐determination theory

Yang¹,

Zhou²,

Cheng³

2018

Brit J Educational Tech

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Retaining learners and facilitating their continuance are critical for the mobile learning providers and educators. Drawing on stimulus‐organism‐response framework and self‐determination theory, this study examines factors that affect college students' mobile learning continuance by considering the self‐determination needs and learning involvement. A research model was developed and empirically tested against data collected from 309 college students who are the mobile learning users of an online education platform in China. The results of structural equation modeling analysis showed that perceived learning support, self‐management of learning and peer influence significantly influence affective learning involvement, which in turn positively affect mobile learning continuance intention. In addition, perceived learning support and peer influence also significantly influence cognitive learning involvement, which further determine mobile learning continuance intention. Theoretical and practical implications of these findings are also discussed.

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Section: Perceived Autonomymentioning

confidence: 99%

Why do college students continue to use mobile learning? Learning involvement and self‐determination theory

Yang¹,

Zhou²,

Cheng³

2018

Brit J Educational Tech

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“…Since most of the learning takes place during self-study outside class through the e-tutorials or other learning materials, class time is used to discuss solving advanced problems. Thus, the instructional format is best characterized as a flippedclassroom design (Isaías et al, 2017;Sergis et al, 2018;Williams et al, 2016). Using and achieving good scores in the e-tutorial practice modes is incentivized by providing bonus points for good performance in quizzes that are taken every two weeks and consist of items that are drawn from the same item pools applied in the practising mode.…”

Section: Context Of the Empirical Studiesmentioning

confidence: 99%

“…The availability of trace data derived from the use of technology-enhanced learning, trace data of both process and product types (Azevedo et al, 2013), is a crucial aspect in this progress made in analysing learning behaviours. (2015), analysing goal setting survey data in combination with trace data, or Sergis et al (2018), analysing self-determination based motivational survey data in combination with trace data. A related approach is that of Dispositional Learning Analytics (DLA, Buckingham Shum and Crick, 2012), that proposes an infrastructure that combines learning data (generated in learning activities through technology-enhanced systems) with a broad range of learner data: student dispositions, values, and attitudes measured through self-report surveys.…”

Section: How To Citementioning

confidence: 99%

“…Academic motivations refer to the first and second so-called mini-theories of self-determination theory: the cognitive evaluation theory, concerning intrinsic motivation, and the organismic integration theory, concerning various forms of extrinsic motivation (Deci and Ryan, 2000;Sergis et al, 2018). The second mini-theory implies that different forms of extrinsic motivation together shape a continuum with pure intrinsic and pure extrinsic motivation as the poles, describing different degrees of internalizing extrinsic motivation into mixed states of more or less learner autonomy.…”

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A multi-modal study into students’ timing and learning regulation: time is ticking

Tempelaar

Rienties

Nguyen

2018

ITSE

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How to cite:Tempelaar, Dirk; Rienties, Bart and Nguyen, Quan (2018). A multi-modal study into students' timing and learning regulation: time is ticking. Interactive Technology and Smart Education, 15(4) pp. 298-313.For guidance on citations see FAQs. ' (Schumacher and Ifenthaler, 2018, p. 397). The use of multi-modal data, which is characterised by two or more distinct types of data, offers new insights into long-standing academic debates that have been addressed in the past with empirical studies based on survey data only. The availability of trace data derived from the use of technology-enhanced learning, trace data of both process and product types (Azevedo et al., 2013), is a crucial aspect in this progress made in analysing learning behaviours. (2015), analysing goal setting survey data in combination with trace data, or Sergis et al. (2018), analysing self-determination based motivational survey data in combination with trace data. A related approach is that of Dispositional Learning Analytics (DLA, Buckingham Shum and Crick, 2012), that proposes an infrastructure that combines learning data (generated in learning activities through technology-enhanced systems) with a broad range of learner data: student dispositions, values, and attitudes measured through self-report surveys. Learning dispositions represent individual difference characteristics that impact all learning processes and include affective, behavioural and cognitive facets (Rienties et al., 2017). Students' preferred learning approaches are examples of such dispositions of both cognitive and behavioural type. In a series of studies (Nguyen et al., 2016;Tempelaar et al., 2015Tempelaar et al., , 2017aTempelaar et al., , 2017bTempelaar et al., , 2018 we have analysed bi-modal data derived from a first-year introductory course mathematics and statistics, offered in blended mode, in which several survey instruments were applied, that cover learning dispositions thought to be important in self-regulated learning. Students' preferences for alternative feedback modes, distinguishing between learners who prefer worked-out examples, tutored problem-solving or untutored problem-solving and investigating the role of learning dispositions as an antecedent of these preferences, was one of the aims of these studies. In our current paper, we continue this line of research, whereby we now focus on learning regulation and especially the timing of learning as part of a self-regulated learning process, and investigate the role of antecedents in this regulation, thereby focussing on antecedents that are part of the framework of embodied motivation (Spector and Park, 2018). Self-regulated learning and the timing of learningThere is an abundance of empirical research investigating learning time in self-regulated learning processes. Examples of such studies can be found in the domain of classical educational studies, such as Wolters et al. (2017) who find that students' self-perceptions of time management are associated with self-perceived motivational and strateg...

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“…Other findings suggest that a MOOC-based flipped class is a good solution to promote students' motivation and learning, but the implementation of this teaching strategy is delicate and must be very well planned [12]. Some authors indicate that the use of flipped MOOCs is promising not only in terms of effectiveness but also the motivation of the students and teachers [13] and increased satisfaction [14]. Meanwhile some authors are more skeptical and suggest that flipped learning (FL) effectiveness is yet to be proven [11].…”

Section: Introductionmentioning

confidence: 99%

The Flipped MOOC: Using Gamification and Learning Analytics in MOOC Design—A Conceptual Approach

2018

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Abstract:Recently, research has highlighted the potential of Massive Open Online Courses (MOOCs) for education, as well as their drawbacks, which are well known. Several studies state that the main limitations of the MOOCs are low completion and high dropout rates of participants. However, MOOCs suffer also from the lack of participant engagement, personalization, and despite the fact that several formats and types of MOOCs are reported in the literature, the majority of them contain a considerable amount of content that is mainly presented in a video format. This is in contrast to the results reported in other educational settings, where engagement and active participation are identified as success factors. We present the results of a study that involved educational experts and learning scientists giving new and interesting insights towards the conceptualization of a new design approach, the flipped MOOC, applying the flipped classroom approach to the MOOCs' design and making use of gamification and learning analytics. We found important indications, applicable to the concept of a flipped MOOC, which entails turning MOOCs from mainly content-oriented delivery machines into personalized, interactive, and engaging learning environments. Our findings support the idea that MOOCs can be enriched by the orchestration of a flipped classroom approach in combination with the support of gamification and learning analytics.

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Investigating the impact of Flipped Classroom on students' learning experiences: A Self-Determination Theory approach

Cited by 221 publications

References 17 publications

Why do college students continue to use mobile learning? Learning involvement and self‐determination theory

Why do college students continue to use mobile learning? Learning involvement and self‐determination theory

A multi-modal study into students’ timing and learning regulation: time is ticking

The Flipped MOOC: Using Gamification and Learning Analytics in MOOC Design—A Conceptual Approach

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