Peer assessment of peer assessment plan: A deep learning approach of teacher assessment literacy

Wing Shui NG*, Haoran XIE, Fu Lee WANG, Tingting LI

*Corresponding author for this work

Research output: Journal PublicationsJournal Article (refereed)

Abstract

The rationales of using assessment to enhance learning have been highly recognised. However, the issue of assessment literacy deficiency and insecurity about effective assessment implementation among pre-service and in-service teachers has been documented, which inevitably weakens the effectiveness of using assessment to improve learning. In this study, a deep learning approach with a core component of peer assessment of peer assessment plan was implemented to enhance the assessment literacy of a group of pre-service teachers. The design was informed by the taxonomy of learning in the cognitive domain and affective domain. Results show that they were able to prepare peer assessment plans in good quality. After conducting the activity of peer assessment on peer assessment plan, they demonstrated a deep level of attitude change and explicitly expressed their willingness to implement peer assessment in their future teaching. The deep learning approach to a great extent enhanced teachers' assessment literacy.

Original languageEnglish
Pages (from-to)450-466
Number of pages17
JournalInternational Journal of Innovation and Learning
Volume27
Issue number4
DOIs
Publication statusE-pub ahead of print - 22 Apr 2020
Externally publishedYes

Keywords

  • Assessment education
  • Assessment for learning
  • Assessment literacy
  • Blended learning
  • Deep learning
  • Peer assessment
  • Peer feedback
  • Pre-service teacher
  • Taxonomy of learning
  • Teacher training

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