文献类型：会议论文

英文题名：A Personalized Learning Strategy Recommendation Approach for Programming Learning

作者：Gu, Peipei[1];Ma, Junxia[1];Chen, Wei[2];Deng, Lujuan[1];Jiang, Lan[3]

第一作者：Gu, Peipei

通讯作者：Ma, JX[1]

机构：[1]Zhengzhou Univ Light Ind, Software Engn Coll, Zhengzhou 450000, Henan, Peoples R China;[2]Chinese Acad Agr Sci, Agr Informat Inst, Beijing 100081, Peoples R China;[3]Xinxiang Univ, Coll Comp & Informat Engn, Xinxiang 453000, Peoples R China

第一机构：Zhengzhou Univ Light Ind, Software Engn Coll, Zhengzhou 450000, Henan, Peoples R China

通讯机构：[1]corresponding author), Zhengzhou Univ Light Ind, Software Engn Coll, Zhengzhou 450000, Henan, Peoples R China.

会议论文集：22nd International Conference on Database Systems for Advanced Applications (DASFAA)

会议日期：MAR 27-30, 2017

会议地点：Suzhou, PEOPLES R CHINA

语种：英文

外文关键词：Intelligent tutoring system; Learning strategy recommendation system; Learning strategy; Learning strategy model

摘要：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.