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Enhancing Teacher Assessment Literacy Using a Blended Deep Learning Approach

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Blended Learning. Enhancing Learning Success (ICBL 2018)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10949))

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Abstract

Assessment literacy refers to educators’ understanding of the principles and practices of sound assessment. It has been considered as a critical professional requirement in educational system since it to a great extent affects students’ learning. However, research has shown that both pre-service and in-service teachers are weak in assessment literacy and lack confidence to implement effective assessment. The main reasons of unsatisfactory assessment literacy among teachers are the limited pre-service assessment education and a lack of research on the pedagogies on assessment education. To enrich effective practice of assessment literacy education, a blended deep learning approach for educating teacher assessment literacy was applied in this study. The strategy combined a face-to-face component for content-based teaching and an online learning component for process-based teaching. The online learning component with the focus on peer assessment engaged participants in a deep learning of assessment. Participants expressed that they had obtained an in-depth understanding on assessment literacy and particularly on peer assessment. They had developed better confidence and are willing to implement peer assessment in their future teaching. This study provides a case of using a blended learning approach on assessment education for reference.

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Author information

Authors and Affiliations

  1. The Education University of Hong Kong, Tai Po, NT, Hong Kong

    Wing Shui Ng & Haoran Xie

  2. The Open University of Hong Kong, Ho Man Tin, Kowloon, Hong Kong

    Fu Lee Wang

Authors
  1. Wing Shui Ng
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  2. Haoran Xie
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  3. Fu Lee Wang
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Corresponding author

Correspondence to Wing Shui Ng .

Editor information

Editors and Affiliations

  1. The Open University of Hong Kong, Hong Kong, China

    Simon K.S. Cheung

  2. City University of Hong Kong, Hong Kong, China

    Lam-for Kwok

  3. Kansai University, Osaka, Japan

    Kenichi Kubota

  4. The Open University of Hong Kong, Hong Kong, Hong Kong

    Lap-Kei Lee

  5. Kwansei Gakuin University, Osaka, Japan

    Jumpei Tokito

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Ng, W.S., Xie, H., Wang, F.L. (2018). Enhancing Teacher Assessment Literacy Using a Blended Deep Learning Approach. In: Cheung, S., Kwok, Lf., Kubota, K., Lee, LK., Tokito, J. (eds) Blended Learning. Enhancing Learning Success. ICBL 2018. Lecture Notes in Computer Science(), vol 10949. Springer, Cham. https://doi.org/10.1007/978-3-319-94505-7_16

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  • DOI: https://doi.org/10.1007/978-3-319-94505-7_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-94504-0

  • Online ISBN: 978-3-319-94505-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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