TY - GEN
T1 - Learning Analytics of the Relationships among Knowledge Constructions, Self-regulated Learning, and Learning Performance
AU - Hao, Hao
AU - Geng, Xuewang
AU - Chen, Li
AU - Shimada, Atsushi
AU - Yamada, Masanori
N1 - Funding Information:
ACKNOWLEDGEMENT This research is supported by JSPS KAKENHI JP19H01716, JP 21K 18134, JP21KK0184 and JST AIP Acceleration Research JPMJCRI9U1.
Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - The concept map has a positive effect on the enhancement of self-regulated learning (SRL) and learning performance in terms of cognitive learning tools, according to previous research. However, the relationships between knowledge construction state, learning behaviors, psychological state, and learning performance have not been clearly investigated. Learning analytics (LA) can play an important role in addressing the issue of collecting learning behaviors. This study aims to investigate the relationships between them, using the LA approach. The results indicated that seven knowledge construction types were detected, and knowledge construction type had significant differences in performance, albeit no significant differences in the Tukey post-hoc analyses. Moreover, there is a significant correlation between knowledge map cluster and discussion, some of the factors of SRL (e.g., declarative knowledge, monitoring), and some learning behaviors, such as adding marker, memo, and red marker.
AB - The concept map has a positive effect on the enhancement of self-regulated learning (SRL) and learning performance in terms of cognitive learning tools, according to previous research. However, the relationships between knowledge construction state, learning behaviors, psychological state, and learning performance have not been clearly investigated. Learning analytics (LA) can play an important role in addressing the issue of collecting learning behaviors. This study aims to investigate the relationships between them, using the LA approach. The results indicated that seven knowledge construction types were detected, and knowledge construction type had significant differences in performance, albeit no significant differences in the Tukey post-hoc analyses. Moreover, there is a significant correlation between knowledge map cluster and discussion, some of the factors of SRL (e.g., declarative knowledge, monitoring), and some learning behaviors, such as adding marker, memo, and red marker.
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U2 - 10.1109/TALE52509.2021.9678920
DO - 10.1109/TALE52509.2021.9678920
M3 - Conference contribution
AN - SCOPUS:85125916331
T3 - TALE 2021 - IEEE International Conference on Engineering, Technology and Education, Proceedings
SP - 290
EP - 297
BT - TALE 2021 - IEEE International Conference on Engineering, Technology and Education, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 IEEE International Conference on Engineering, Technology and Education, TALE 2021
Y2 - 5 December 2021 through 8 December 2021
ER -