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  • 标题:Deep and Surface Processing of Instructor's Feedback in an Online Course
  • 本地全文:下载
  • 作者:Kun Huang ; Xun Ge ; Victor Law
  • 期刊名称:Educational Technology and Society
  • 印刷版ISSN:1176-3647
  • 电子版ISSN:1436-4522
  • 出版年度:2017
  • 卷号:20
  • 期号:4
  • 页码:247-260
  • 出版社:IFETS - Attn Kinshuck
  • 摘要:This 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.
  • 关键词:Approaches to learning; Deep learning; Epistemic beliefs; Feedback; Need for closure; Problem solving
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