Learners' Deep and surface processing of instructor's feedback in an online course

Kun Huang, Xun Ge, Victor Law

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

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.

Original languageEnglish
Pages (from-to)247-260
Number of pages14
JournalEducational Technology and Society
Volume20
Issue number4
StatePublished - 2017

Keywords

  • Approaches to learning
  • Deep learning
  • Epistemic beliefs
  • Feedback
  • Need for closure
  • Problem solving

ASJC Scopus subject areas

  • Education
  • Sociology and Political Science
  • General Engineering

Fingerprint

Dive into the research topics of 'Learners' Deep and surface processing of instructor's feedback in an online course'. Together they form a unique fingerprint.

Cite this