Understanding the Usages and Effects of a Recommendation System in a Non-formal Learning Context

被引:0
|
作者
Badier, Anaelle [1 ]
Lefort, Mathieu [1 ]
Lefevre, Marie [1 ]
机构
[1] Univ Lyon, UCBL, CNRS, INSA Lyon,LIRIS,UMR5205, F-69622 Villeurbanne, France
来源
AUGMENTED INTELLIGENCE AND INTELLIGENT TUTORING SYSTEMS, ITS 2023 | 2023年 / 13891卷
关键词
Pedagogical Recommendations; Traces Analysis; Usage and Practice Analysis; Self-Regulated Learning;
D O I
10.1007/978-3-031-32883-1_5
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Learning support faces many challenges in a non-formal context: the pedagogical recommendations delivered aimed at learners with very different objectives and studying methods, and the analyses of learners' behavior toward the recommendations are based almost exclusively on learning traces from the learning platform. In this context, we propose a recommendation system for educational resources in an extracurricular mobile application. Our system is based on a pedagogical score, on the learner history and ensures a renewal of the recommended chapters. By analyzing the usage traces of more than 10,000 learners over 4 months, we show that delivered recommendations are mainly used as a revision tool when learners face difficulties, and that they mostly remain in chapters of their current level grade. Usage traces also reveal that following recommendations has a positive impact on the learning experience.
引用
收藏
页码:54 / 65
页数:12
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