A Personalized Learning Strategy Recommendation Approach for Programming Learning

• Published in: Database Systems for Advanced Applications pp. 267 - 274
• Main Authors: Gu, Peipei, Ma, Junxia, Chen, Wei, Deng, Lujuan, Jiang, Lan
• Format: Book Chapter
• Language: English
• Published: Cham Springer International Publishing
• Series: Lecture Notes in Computer Science
• Subjects: Intelligent tutoring system; Learning strategy; Learning strategy model; Learning strategy recommendation system
• ISBN: 3319557041; 9783319557045
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-319-55705-2_21

Nowadays, it has been a significant problem to recommend learning strategy for different learners in programming learning projects. This paper discusses a personalized learning strategy recommendation approach to aid programming learning. In this paper, an improved design method of model learner strategies and programming learning strategy recommendation approach are presented. A reward factor is adopted to help to construct a learning strategy recommendation mechanism adaptively. The programming learning strategy recommendation system (ZZULI-PLS) is proposed based on those models to help learners learning in programming according to the actual progresses of learners. Usability tests are conducted to validate the recommendation efficiency in ZZULI-PLS system.