A competency—driven advisor system for multi-actor learning environments | Zendy

Olga Mariño | Zendy; Gilbert Paquette | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

A competency—driven advisor system for multi-actor learning environments

Author(s) -

Olga Mariño,

Gilbert Paquette

Publication year - 2010

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2010.08.013

Subject(s) - computer science , human–computer interaction , artificial intelligence , knowledge management

Advising plays a central role in technology-enhanced learning (TEL). Based on a diagnosis of the activity of a learner and on relevant knowledge of this learner, an advisor system compiles and delivers some useful advices or explanations. Since 1994, we have been working on advisor systems. This paper presents the latest work on a multi-agent system that gives advice on tasks and resources based on competency-driven user models and on ontology-based multi-actor learnflows

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research