Flipped Data Science Classrooms with Peer Instruction and Just-In-Time Teaching: Students’ Perceptions and Learning Experiences

Haoran XIE, Gary CHENG, Fu Lee WANG*, Xinyi HUANG, Chit Ming James CHONG

*Corresponding author for this work

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Researchpeer-review


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.
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, Revised Selected Papers
EditorsCarina S. González-González, Manuel Area-Moreira, Baltasar Fernández-Manjón, Frederick Li, Francisco José García-Peñalvo, Filippo Sciarrone, Marc Spaniol, Alicia García-Holgado, Matthias Hemmje, Tianyong Hao
PublisherSpringer, Cham
Number of pages8
ISBN (Electronic)9783031330230
ISBN (Print)9783031330223
Publication statusPublished - 26 May 2023

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Bibliographical note

Funding Information:
The research reported in this paper has been supported by the Teaching Development Grant (102489) from Lingnan University.

Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.


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


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