Flipped data science classrooms with peer instruction and just-in-time teaching: Students’ perceptions and learning experiences

Haoran XIE, Xinyi HUANG, Kwok Shing CHENG, Fu Lee WANG, James Chit Ming CHONG

Research output: Chapter in Book/Report/Conference proceedingChapters

Abstract

This paper focused on students’ learning experiences in a flipped data science class integrated with peer instruction and just-in-time teaching. University students in Hong Kong participated in the research during the pandemic. Students’ perceptions of the flipped learning mode were investigated by a 5-point Likert scale questionnaire. According to the results, most students felt they enjoyed learning with the flipped mode since it allowed them to learn flexibly and independently. The course materials (i.e., instructional videos, lecture notes, and in-class exercises) were well-designed, and students perceived the materials were useful and user-friendly. As suggested by the students, more time should be given to the pre-class learning activities. Based on the suggestions, the researchers provide practical implications on improving teaching in the flipped science class. This study demonstrates how to flip a data science class and proves its value on students’ learning, providing implications for using flipped learning during the pandemic period. Copyright © 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG.

Original languageEnglish
Title of host publicationLearning technologies and systems: 21st International Conference on Web-Based Learning, ICWL 2022, and 7th International Symposium on Emerging Technologies for Education, SETE 2022, Tenerife, Spain, November 21–23, 2022, revised selected papers
EditorsCarina S. GONZÁLEZ-GONZÁLEZ, Baltasar FERNÁNDEZ-MANJÓN, Frederick LI, Francisco José GARCÍA-PEÑALVO, Filippo SCIARRONE, Marc SPANIOL, Alicia GARCÍA-HOLGADO, Manuel AREA-MOREIRA, Matthias HEMMJE, Tianyong HAO
Place of PublicationCham
PublisherSpringer
Pages395-402
ISBN (Electronic)9783031330230
ISBN (Print)9783031330223
DOIs
Publication statusPublished - 2023

Citation

Xie, H., Huang, X., Cheng, G., Wang, F. L., & Chong, J. C. M. (2023). Flipped data science classrooms with peer instruction and just-in-time teaching: Students’ perceptions and learning experiences. In C. S. González-González, B. Fernández-Manjón, F. Li, F. J. García-Peñalvo, F. Sciarrone, M. Spaniol, A. García-Holgado, M. Area-Moreira, M. Hemmje, & T. Hao (Eds.), Learning technologies and systems: 21st International Conference on Web-Based Learning, ICWL 2022, and 7th International Symposium on Emerging Technologies for Education, SETE 2022, Tenerife, Spain, November 21–23, 2022, revised selected papers (pp. 395-402). Springer. https://doi.org/10.1007/978-3-031-33023-0_37

Keywords

  • Flipped Learning
  • Peer Instruction
  • Just-in-time teaching

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