Recommending in Inclusive Lifelong Learning Scenarios: Identifying and Managing Runtime Situations

Authors:
Olga C. Santos
Affiliations:
-
Venue:
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 03
Year:
2008

Citing 6
Cited 1

Building a Recommender Agent for e-Learning Systems

ICCE '02 Proceedings of the International Conference on Computers in Education
The software empiricist

ACM SIGMETRICS Performance Evaluation Review
A multiagent knowledge-based recommender approach with truth maintenance

Proceedings of the 2007 ACM conference on Recommender systems
Personal recommender systems for learners in lifelong learning networks: the requirements, techniques and model

International Journal of Learning Technology
A recommender system to provide adaptive and inclusive standard-based support along the elearning life cycle

Proceedings of the 2008 ACM conference on Recommender systems
Users' Experience with a Recommender System in an Open Source Standard-Based Learning Management System

USAB '08 Proceedings of the 4th Symposium of the Workgroup Human-Computer Interaction and Usability Engineering of the Austrian Computer Society on HCI and Usability for Education and Work

Users' Experience with a Recommender System in an Open Source Standard-Based Learning Management System

USAB '08 Proceedings of the 4th Symposium of the Workgroup Human-Computer Interaction and Usability Engineering of the Austrian Computer Society on HCI and Usability for Education and Work

Quantified Score

Hi-index	0.00

Visualization

Abstract

Supporting learners in inclusive lifelong learning scenarios requires a dynamic support that takes into account their learning needs and preferences. This research is focused on an open standard-based recommender system, covering the full life cycle of eLearning. The recommending system I am developing is supported by a multi-agent architecture and its ultimate goal is to improve the learning efficiency and the learners’ satisfaction during the execution of the course tasks.