文章基本信息

标题：Adaptive learning module for a conversational agent to support MOOC learners
本地全文：下载
作者：Nuria González-Castro ; Pedro J.Muñoz-Merino ; Carlos Alario-Hoyos 等
期刊名称：Australasian Journal of Educational Technology
印刷版ISSN：1449-3098
电子版ISSN：1449-5554
出版年度：2021
卷号：37
期号：2
页码：24-44
DOI：10.14742/ajet.6646
语种：English
出版社：Australasian Society for Computers in Learning in Tertiary Education
摘要：Massive open online courses (MOOCs) pose a challenge for instructors when trying to provide personalised support to learners, due to large numbers of registered participants. Conversational agents can be of help to support learners when working with MOOCs. This article presents an adaptive learning module for JavaPAL, a conversational agent that complements a MOOC on Java programming, helping learners review the key concepts of the MOOC. This adaptive learning module adapts the difficulty of the questions provided to learners considering their level of knowledge using item response theory (IRT) and also provides recommendations of video fragments e10.14742/ajet.tracted from the MOOC for when learners fail questions. The adaptive learning module for JavaPAL has been evaluated showing good usability and learnability through the system usability scale (SUS), reasonably suitable video fragments recommendations for learners, and useful visualisations generated as part of the IRT-based adaptation of questions for instructors to better understand what is happening in the course, to design e10.14742/ajet.ams, and to redesign the course content.
关键词：conversational agent;adaptive learning;Item Response Theory;MOOC;Java programming;e10.14742/ajet.pert evaluation