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Investigating secondary school students' academic emotions in data science learning
Citation
Zhu, G., Teo, C. L., Yuan, G., Ker, C. L., Ong, A., & Lee, A. V. Y. (2024). Investigating secondary school students' academic emotions in data science learning. In A. Kashihara, B. Jiang, M. M. Rodrigo, & J. O. Sugay (Eds.), Proceedings of the 32nd International Conference on Computers in Education (Volume 1). Asia Pacific Society of Computers in Education. https://doi.org/10.58459/icce.2024.4839
Author
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Ker, Chin-Lee
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Ong, Aloysius Kian-Keong
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Abstract
Cultivating students' data science knowledge and skills is pressing and challenging, given its interdisciplinary nature, students' limited prior knowledge, and teachers' insufficient training. In data science learning, students may experience various academic emotions. Understanding what emotions students experience, how these emotions are associated with their perceived learning, and under what conditions they experience intensive emotions is critical to informing the design of data science programs and better supporting students. This study collected 839 emotion survey responses from 67 secondary school students in two cycles of a two-day out-of-school data science program. The program engaged students in collaborative inquiries on authentic problems through data science practices with the support of teachers, researchers and facilitators. We found that frustration, interest, surprise and happiness positively predicted students' perceived learning, whereas anxiety negatively predicted perceived learning. Students experienced peaks of positive emotions after an expert's enthusiastic introduction talk to data science in the first cycle and after one-to-one face-to-face consultations with data science experts in the second cycle. However, sharing their progress and challenges with the data science expert in the first cycle and preparing for presentations in both cycles made them experience intense negative emotions such as anxiety, frustration, and confusion. These findings provide implications for designing data science programs to elicit students' positive learning experiences and reduce intensive negative emotions.
Date Issued
2024
ISBN
9786269689040 (online)
Publisher
Asia-Pacific Society for Computers in Education
Project
RP 10/22 ZGX
Grant ID
NIE-SUG 4-22 ZGX
Funding Agency
National Institute of Education, Singapore
Ministry of Education, Singapore