The 3A Interaction Model and Relation-Based Recommender System: Adopting Social Media Paradigms in Designing Personal Learning Environments
We live in a rapidly changing digital world marked by technological advances, and fraught with online information constantly growing thanks to the Internet revolution and the online social applications in particular. Formal learning acquired in traditional academic and professional environments is not by itself sufficient to keep up with our information-based society. Instead, more and more focus is granted to lifelong, self-directed, and self-paced learning, acquired intentionally or spontaneously, in environments that are not purposely dedicated for learning. The concept of online Personal Learning Environments (PLEs) refers to the development of platforms that are able to sustain lifelong learning. PLEs require new design paradigms giving learners the opportunity to conduct autonomous activities depending on their interests, and allowing them to appropriate, repurpose and contribute to online content rather than merely consume pre-packaged learning resources. This thesis presents the 3A interaction model, a flexible design model targeting online personal and collaborative environments in general, and PLEs in particular. The model adopts bottom-up social media paradigms in combining social networking with flexible content and activity management features. The proposed model targets both formal and informal interactions where learning in not necessarily an explicit aim but may be a byproduct. It identifies 3 main constructs, namely actors, activities, and assets that can represent interaction and learning contexts in a flexible way. The applicability of the 3A interaction model to design actual PLEs and to deploy them in different learning modalities is demonstrated through usability studies and use-case scenarios. This thesis also addresses the challenge of dealing with information overload and helping end-users find relatively interesting information in open environments such as PLEs where content is not predefined, but is rather constantly added at run time, and differ in subject matter, quality, as well as intended audience. For that purpose, the 3A personalized, contextual, and relation-based recommender system is proposed, and evaluated on two real datasets.
Keywords: 3A interaction model ; social media ; personal learning environments ; knowledge management ; social interactions ; interaction context ; user-centered design ; information retrieval ; recommender systems ; personalized recommender systems ; personalization ; contextualization ; lifelong learning ; formal learning ; informal learning ; technology-enhanced learning ; computer-supported collaborative work ; computer-supported collaborative learning ; modèle d'interaction 3A ; médias sociaux ; environnement personnel d'apprentissage ; gestion de connaissance ; interactions sociales ; contextes d'interaction ; contexte ; modèles conceptuels centrés sur l'utilisateur ; extraction de données ; système de recommandation en ligne ; personnalisation ; contextualisation ; apprentissage continu ; apprentissage formel ; apprentissage informel ; travail collaboratif assisté par ordinateur ; apprentissage collaboratif assisté par ordinateurThèse École polytechnique fédérale de Lausanne EPFL, n° 4829 (2010)
Programme doctoral Informatique, Communications et Information
Faculté des sciences et techniques de l'ingénieur
Institut de génie mécanique
Record created on 2010-08-19, modified on 2016-12-12