Learning Object Recommendations based on Quality and Item Response Theory

被引:5
作者
Baldiris, Silvia [1 ]
Fabregat, Raman [1 ]
Graf, Sabine [2 ,3 ]
Tabares, Valentina [4 ]
Duque, Nestor [4 ]
Avila, Cecilia [1 ]
机构
[1] Univ Girona, Inst Informat & Aplicat, Girona, Spain
[2] Univ Girona, Inst Informat & Aplicat, Girona, Spain
[3] Athabasca Univ, Sch Comp & Informat Syst, Athabasca, AB, Canada
[4] Univ Nacl Colombia, Manizales, Colombia
来源
2014 14TH IEEE INTERNATIONAL CONFERENCE ON ADVANCED LEARNING TECHNOLOGIES (ICALT) | 2014年
关键词
Item response theory; learning objects; recommendations;
D O I
10.1109/ICALT.2014.238
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Nowadays, teachers and students continue to face the problem to find high quality learning objects for learning and teaching. The purpose of this paper is to introduce an innovative approach, which considers Item Response Theory (IRT) for recommending to students or teachers Learning Objects (LOs) of high quality in the context of the Learning Objects Economy, which is a marketplace for sharing and reuse of LOs. Recommendations provide to teachers or students the needed support for finding high quality learning objects taking advantage of the previous quality evaluations carry out by peers. An evaluation of our approach was carried out in a real scenario which allowed us to verify the applicability of the process for generating good recommendations.
引用
收藏
页码:34 / +
页数:2
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