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Damien S. Fleur; Max Marshall; Miguel Pieters; Natasa Brouwer; Gerrit Oomens; Angelos Konstantinidis; Koos Winnips; Sylvia Moes; Wouter van den Bos; Bert Bredeweg; Erwin A. van Vliet – Journal of Learning Analytics, 2023
Personalized feedback is important for the learning process, but it is time consuming and particularly problematic in large-scale courses. While automatic feedback may help for self-regulated learning, not all forms of feedback are effective. Social comparison offers powerful feedback but is often loosely designed. We propose that intertwining…
Descriptors: Feedback (Response), Peer Influence, Learning Analytics, Undergraduate Students
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Ohadugha, Rosemary Ogechi; Chukwuemeka, Emeka Joshua; Babatunde, Abdullateef Eyitayo – Contemporary Educational Technology, 2020
The study examined the Impact of Peer-Mediated Learning on achievement and motivation in computer science among senior secondary school students in Minna metropolis, Niger state. The study adopted a randomized pre-test, post-test control group design. Two hypotheses were formulated to guide the study. Purposive sampling technique was used to…
Descriptors: Peer Teaching, Peer Influence, Instructional Effectiveness, Academic Achievement
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Johnson, Genevieve Marie – Educational Psychology, 2016
First-year university students (n = 199) completed an online questionnaire that queried their purchase of paper books and eBooks for university study and personal interest. The questionnaire also required students to rate their learning characteristics including reading strategies, study self-regulation, learning control beliefs and achievement…
Descriptors: College Freshmen, Questionnaires, Printed Materials, Electronic Publishing
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Johnson, Marcus Lee; Taasoobshirazi, Gita; Clark, Lauren; Howell, Leah; Breen, Mishele – Journal of Continuing Higher Education, 2016
We surveyed 139 (88 traditional, 51 nontraditional) students on various motivational measures of self-determination, attribution, and expectancy-value to (a) investigate motivational differences by student status and (b) identify the motivational variables that best predict academic achievement by student status. Results of a multivariate analysis…
Descriptors: Student Motivation, College Students, Nontraditional Students, Self Determination
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Du, Jianxia; Xu, Jianzhong; Fan, Xitao – Technology, Pedagogy and Education, 2015
This study examined predictive models for students' help seeking in the context of online collaborative groupwork. Results from multilevel analysis revealed that most of the variance in help seeking was at the individual student level, and multiple variables at the individual level were predictive of help-seeking behaviour. Help seeking was…
Descriptors: Help Seeking, Cooperative Learning, Electronic Learning, Group Activities