@inproceedings{4e56c980a2264cdfbe2e2659ef1fe178,
title = "Learning object recommendations based on quality and item response theory",
abstract = "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.",
keywords = "Item response theory, learning objects, recommendations",
author = "Silvia Baldiris and Ramon Fabregat and Sabine Graf and Valentina Tabares and Nestor Duque and Cecilia Avila",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 14th IEEE International Conference on Advanced Learning Technologies, ICALT 2014 ; Conference date: 07-07-2014 Through 09-07-2014",
year = "2014",
month = sep,
day = "17",
doi = "10.1109/ICALT.2014.238",
language = "English",
series = "Proceedings - IEEE 14th International Conference on Advanced Learning Technologies, ICALT 2014",
pages = "34--36",
editor = "Sampson, {Demetrios G.} and Spector, {Michael J.} and Nian-Shing Chen and Ronghuai Huang and Kinshuk",
booktitle = "Proceedings - IEEE 14th International Conference on Advanced Learning Technologies, ICALT 2014",
}