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Autor/inn/enHuang, Kun; Ge, Xun; Law, Victor
TitelDeep and Surface Processing of Instructor's Feedback in an Online Course
QuelleIn: Educational Technology & Society, 20 (2017) 4, S.247-260 (14 Seiten)Infoseite zur Zeitschrift
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Spracheenglisch
Dokumenttypgedruckt; online; Zeitschriftenaufsatz
ISSN1436-4522
SchlagwörterCollege Students; Student Evaluation; Feedback (Response); Online Courses; Electronic Learning; Learning Processes; Problem Solving; Student Attitudes; Beliefs; Epistemology; Holistic Approach; Mixed Methods Research; Pretests Posttests
AbstractThis study investigated the characteristics of deep and surface approaches to learning in online students' responses to instructor's qualitative feedback given to a multi-stage, ill-structured design project. Further, the study examined the relationships between approaches to learning and two learner characteristics: epistemic beliefs (EB) and need for closure (NFC). Four emerging themes were identified where the students' approaches to learning spread along a spectrum of deep to surface learning: "number of feedback items addressed," "understanding of feedback," "quality in addressing feedback," and "holistic thinking." In addition, the maturity of EB was likely to be associated with students' understanding of feedback and the systematic and relational thinking demonstrated in their responses to feedback. The relationship was unclear between NFC and deep/surface learning characteristics. The findings provide implications for the design of feedback to scaffold deep learning in ill-structured problem solving. (As Provided).
AnmerkungenInternational Forum of Educational Technology & Society. Available from: National Sun Yat-sen University. Department of Information Management, 70, Lien-Hai Rd, Kaohsiung, 80424, Taiwan. Web site: http://www.ifets.info
Erfasst vonERIC (Education Resources Information Center), Washington, DC
Update2020/1/01
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