Adaptive Learning Resources Sequencing in Educational Hypermedia Systems

Autor/inn/en	Karampiperis, Pythagoras; Sampson, Demetrios
Titel	Adaptive Learning Resources Sequencing in Educational Hypermedia Systems
Quelle	In: Educational Technology & Society, 8 (2005) 4, S.128-147 (20 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1436-4522
Schlagwörter	Methods; Educational Resources; Models; Individualized Instruction; Higher Education; Intelligent Tutoring Systems; Educational Technology; Computer Assisted Instruction; Computer System Design; Instructional Design; Computer Software; Computer Science Education; Programming; Computer Simulation; Hypermedia; Electronic Learning + Suchen Sie Ihr Suchwort? Method; Methode; Bildungsmittel; Analogiemodell; Individualisierender Unterricht; Hochschulbildung; Hochschulsystem; Hochschulwesen; Intelligentes Tutorsystem; Unterrichtsmedien; Computer based training; Computerunterstützter Unterricht; Lesson concept; Lessonplan; Unterrichtsentwurf; Computer science lessons; Informatikunterricht; Programmierung; Computergrafik; Computersimulation
Abstract	Adaptive learning resources selection and sequencing is recognized as among the most interesting research questions in adaptive educational hypermedia systems (AEHS). In order to adaptively select and sequence learning resources in AEHS, the definition of adaptation rules contained in the Adaptation Model, is required. Although, some efforts have been reported in literature aiming to support the Adaptation Model design by providing AEHS designers direct guidance or semi-automatic mechanisms for making the design process less demanding, still it requires significant effort to overcome the problems of inconsistency, confluence and insufficiency, introduced by the use of rules. Due to the problems of inconsistency and insufficiency of the defined rule sets in the Adaptation Model, conceptual "holes" can be generated in the produced learning resource sequences (or learning paths). In this paper, we address the design problem of the Adaptation Model in AEHS proposing an alternative sequencing method that, instead of generating the learning path by populating a concept sequence with available learning resources based on pre-defined adaptation rules, it first generates all possible learning paths that match the learning goal in hand, and then, adaptively selects the desired one, based on the use of a decision model that estimates the suitability of learning resources for a targeted learner. In our simulations we compare the learning paths generated by the proposed methodology with ideal ones produced by a simulated perfect rule-based AEHS. The simulation results provide evidence that the proposed methodology can generate almost accurate learning paths avoiding the need for defining complex rule sets in the Adaptation Model of AEHS. (Contains 10 figures and 5 tables.) (As Provided).
Anmerkungen	International Forum of Educational Technology & Society. Athabasca University, School of Computing & Information Systems, 1 University Drive, Athabasca, AB T9S 3A3, Canada. Tel: 780-675-6812; Fax: 780-675-6973; Web site: http://www.ifets.info
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10