Abstract--This paper presents an ontology-based methodology for automatic decomposition of Learning Objects (LOs) into reusable content units, and discusses their dynamic assembly into personalized learning paths within the domain of technology-assisted self-directed learning. PerLE, a learnercentered, adaptive, tutored Personal Learning Environment (PLE), was developed to substantiate our dynamic syllabus approach applicable to authoring tutored adaptive e-courses. PerLE allows the decomposition of LOs into smaller learning units, which can be dynamically assembled into new LO sequences and repurposed for different learning objectives. While focusing on ontologies in the context of user modeling and personalization, we particularly describe the concept of creating dynamically assembled e-course sequences. We describe how PerLE was designed to better respond to psychological issues of self-directed learning through the strategic approach of user profiling, grounded in the FelderSilverman Learning Style Model (FSLSM). We discuss the system’s conceptual learning architecture rooted in socioconstructivist and connectivist learning theories, and highlight the concept of use of RLOs with reference to the L.U.I.S.A. architecture and its functionalities as a recommender system. In this context, we describe our techno-pedagogical methodology which supports the proposed dynamic syllabus and dynamic assembly approach. Against this psychopedagogical backdrop, we question the platform concept and propose the OPUS 3 (OP 3) AI assisted e-Tutoring framework to better support the authoring of tutored adaptive e-courses, as shown in the use case.Index Terms Adaptive Learning, Behavior Recording, Student Profile and Learning Style, RLO Dynamic Assembly

Authoring Tutored, Adaptive e-Courses in a Personal Learning Environment: a Dynamic Syllabus and Dynamic Assembly Approach

Altimari F;PLASTINA, Anna Franca;CRONIN, Michael;SERVIDIO, Rocco Carmine;CARIA, Maria;
2012-01-01

Abstract

Abstract--This paper presents an ontology-based methodology for automatic decomposition of Learning Objects (LOs) into reusable content units, and discusses their dynamic assembly into personalized learning paths within the domain of technology-assisted self-directed learning. PerLE, a learnercentered, adaptive, tutored Personal Learning Environment (PLE), was developed to substantiate our dynamic syllabus approach applicable to authoring tutored adaptive e-courses. PerLE allows the decomposition of LOs into smaller learning units, which can be dynamically assembled into new LO sequences and repurposed for different learning objectives. While focusing on ontologies in the context of user modeling and personalization, we particularly describe the concept of creating dynamically assembled e-course sequences. We describe how PerLE was designed to better respond to psychological issues of self-directed learning through the strategic approach of user profiling, grounded in the FelderSilverman Learning Style Model (FSLSM). We discuss the system’s conceptual learning architecture rooted in socioconstructivist and connectivist learning theories, and highlight the concept of use of RLOs with reference to the L.U.I.S.A. architecture and its functionalities as a recommender system. In this context, we describe our techno-pedagogical methodology which supports the proposed dynamic syllabus and dynamic assembly approach. Against this psychopedagogical backdrop, we question the platform concept and propose the OPUS 3 (OP 3) AI assisted e-Tutoring framework to better support the authoring of tutored adaptive e-courses, as shown in the use case.Index Terms Adaptive Learning, Behavior Recording, Student Profile and Learning Style, RLO Dynamic Assembly
2012
978-988-19251-6-9
Adaptive Learning, Behavior Recording, Student Profile and Learning Style, RLO Dynamic Assembly
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/166558
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? 2
social impact