2020
DOI: 10.1007/s40692-020-00158-5
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Learner participation regulation supported by long-term peer moderation and participation feedback during asynchronous discussions

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Cited by 6 publications
(3 citation statements)
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References 49 publications
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“…Xie et al (2019) suggest that the co-regulatory influence of students in leadership roles depends on individual self-regulation; they found encouraging connections between the use of self-regulatory activities, perceived leadership and online postings conduct. In fact, learners who demonstrated high participation levels in asynchronous online forums were also most likely to have a chance to sharpen their leadership skill behaviours (Gaul & Kim, 2020). These findings suggest that leadership skill development increases with participation in ODF.…”
Section: Leadershipmentioning
confidence: 80%
“…Xie et al (2019) suggest that the co-regulatory influence of students in leadership roles depends on individual self-regulation; they found encouraging connections between the use of self-regulatory activities, perceived leadership and online postings conduct. In fact, learners who demonstrated high participation levels in asynchronous online forums were also most likely to have a chance to sharpen their leadership skill behaviours (Gaul & Kim, 2020). These findings suggest that leadership skill development increases with participation in ODF.…”
Section: Leadershipmentioning
confidence: 80%
“…Although asynchronous online discussions stimulate thinking processes and contribute to learning enhancement, ensuring students participate in these activities remains a key challenge for educators (Gaul & Kim, 2020). These have driven researchers to interrogate the dynamics of the discussions, including participation or interaction patterns, to enhance the existing body of knowledge.…”
Section: Participation Styles In Idfsmentioning
confidence: 99%
“…Compared to analytics driven by a single data Ouyang et al International Journal of STEM Education (2022) 9:45 source, MMLA can better enrich the data collections of students' learning processes to help researchers understand the processes and environments of collaborative learning (Chatti et al, 2017;Di Mitri et al, 2021;Samuelsen et al, 2019). Moreover, multiple learning analytical methods are usually used in MMLA to analyze those data from multiple sources, including click stream analysis (e.g., Sun et al, 2021), video analysis (e.g., Khan, 2017), content analysis (e.g., Socratous & Ioannou, 2021), and discourse analysis (e.g., Gaul & Kim, 2020). In addition, collaborative programming is a dynamic process, consisting of a gradual changing process of problem-solving, meaning-making, and knowledge-construction (Lewis, 2012;Sun et al, 2021;Wu et al, 2019).…”
Section: Literature Reviewmentioning
confidence: 99%