Title: Peer assessment of peer assessment plan: a deep learning approach of teacher assessment literacy

Authors: Wing Shui Ng; Haoran Xie; Fu Lee Wang; Tingting Li

Addresses: The Education University of Hong Kong, 10 Lo Ping Road, Tai Po, NT, Hong Kong ' The Education University of Hong Kong, 10 Lo Ping Road, Tai Po, NT, Hong Kong ' The Open University of Hong Kong, 30 Good Shepherd Street, Homantin, Kowloon, Hong Kong ' The Education University of Hong Kong, 10 Lo Ping Road, Tai Po, NT, Hong Kong

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.

Keywords: assessment literacy; peer assessment; peer feedback; assessment for learning; assessment education; deep learning; taxonomy of learning; blended learning; pre-service teacher; teacher training.

DOI: 10.1504/IJIL.2020.107617

International Journal of Innovation and Learning, 2020 Vol.27 No.4, pp.450 - 466

Received: 12 Jan 2019
Accepted: 03 May 2019
Published online: 02 Jun 2020 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article