Application of association rule mining with concept-effect relationship model for learning diagnosis

Name: Sudarat Saengkeaw

Organization : Chiang Mai Rajabhat University. Faculty of Management Sciences

Email : sudarat_san@cmru.ac.th

keyword: Association rules (Data mining)

LCSH: Educational tests and measurements -- Data processing

LCSH: Competency-based education

LCSH: Computer-assisted instruction

LCSH: Learning -- Evaluation

Abstract: The traditional concept-effect relationship model (CER model) aims at finding students' suggestions to improve personalized learning outcomes. To provide more benefits to the instructor, we apply association rule mining to search for interesting relationships among all students’ in-class testing scores. This approach enables instructors to better understand student learning performance and improve the instructor’s course design. The experimental results on a computer data mining course have demonstrated the feasibility of the approach, and the mining results provide feedback for supporting instructors in the form of strong association rules, which are found to be very useful in practical applications.

King Mongkut's University of Technology North Bangkok. Central Library

Address: BANGKOK

Email: library@kmutnb.ac.th

Created: 2020

Modified: 2026-04-03

Issued: 2026-04-03

บทความ/Article

application/pdf

BibliograpyCitation : In Prince of Songkla University. College of Computing. The 17th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON 2020) (pp.739-742). Pattani : Prince of Songkla University

eng

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