Developing a Learning Pathway System through Web-Based Mining Technology to Explore Students’ Learning Motivation and Performance

Shu-Chen Cheng, Yu-Ping Cheng and Yueh-Min Huang ()
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Shu-Chen Cheng: Department of Computer Science and Information Engineering, Southern Taiwan University of Science and Technology, Tainan City 710301, Taiwan
Yu-Ping Cheng: Department of Engineering Science, National Cheng Kung University, Tainan City 701, Taiwan
Yueh-Min Huang: Department of Engineering Science, National Cheng Kung University, Tainan City 701, Taiwan

Sustainability, 2023, vol. 15, issue 8, 1-14

Abstract: There are many resources on the Internet. Searching for articles or multimedia videos is usually interspersed with irrelevant information or advertisements, which may cause students to spend a lot of time judging whether the search results are suitable for learning materials. Therefore, this study developed a learning pathway system by analyzing the representative keywords and difficulty of Internet articles in an automated way and then explored the learning performance and motivation of students using this system. In addition, 67 students were recruited into this study for 18 weeks of experimental activities. In the experimental activities, students can use the learning pathway system to search for algorithm-related materials for reading, and they can also continue to use the system proposed in this study for self-learning after class. The results show that the students’ post-test scores are significantly higher than their pre-test scores, indicating that students can use the learning pathway system to improve their academic performance in algorithm courses. In addition, the intrinsic motivation of high-achieving students was improved, while the intrinsic and extrinsic motivation of low-achieving students were both improved. This means that the learning pathway system can provide suitable learning materials for students to learn, allowing students to achieve autonomous learning.

Keywords: learning pathway; web-based mining; association rule; learning motivation; deep learning (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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