Group formation based on reading annotation data: system innovation and classroom practice-Reference-Cited by-同舟云学术

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Group formation based on reading annotation data: system innovation and classroom practice

Published:2023-04-24 Issue: Volume: Page:
ISSN:2197-9987
Container-title:Journal of Computers in Education
language:en
Short-container-title:J. Comput. Educ.

Author:

Liang Changhao^ORCID,Toyokawa Yuko^ORCID,Majumdar Rwitajit^ORCID,Horikoshi Izumi^ORCID,Ogata Hiroaki^ORCID

Funder

Japan Society for the Promotion of Science

New Energy and Industrial Technology Development Organization

Japan Society for Aeronautical and Space Sciences

Japan Science and Technology Agency

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Education

Link

https://link.springer.com/content/pdf/10.1007/s40692-023-00274-y.pdf

Reference68 articles.

1. Abou-Khalil, V. & Ogata, H. (2021). Homogeneous student engagement: A strategy for group formation during online learning. In International Conference on Collaboration Technologies and Social Computing (pp. 85–92). Springer.

2. Acarol, K. (2019). A study on the effectiveness of flipped learning model. Kara Harp Okulu Bilim Dergisi, 29(2), 267–295.

3. Ali, A. M., & Razali, A. B. (2019). A review of studies on cognitive and metacognitive reading strategies in teaching reading comprehension for ESL/EFL learners. English Language Teaching, 12(6), 94–111.

4. Arisman, R., & Haryanti, I. S. (2019). Using small group discussion to improve students’ reading achievement on narrative text. English Community Journal, 3(1), 325–334.

5. Ball, E., Franks, H., Jenkins, J., McGrath, M., & Leigh, J. (2009). Annotation is a valuable tool to enhance learning and assessment in student essays. Nurse Education Today, 29(3), 284–291.

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1. Co-designing Data-Driven Educational Technology and Practice: Reflections from the Japanese Context;Technology, Knowledge and Learning;2024-07-03

2. Enabling Mixed Genetic Algorithm for Automatic Group Formation System;Lecture Notes in Computer Science;2024

3. Challenges and opportunities of AI in inclusive education: a case study of data-enhanced active reading in Japan;Smart Learning Environments;2023-12-18

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