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A Conceptual Framework for Evolving, Recommender Online Learning Systems
Author(s) -
Peiris K. Dharini Amitha,
Gallupe R. Brent
Publication year - 2012
Publication title -
decision sciences journal of innovative education
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.52
H-Index - 19
eISSN - 1540-4609
pISSN - 1540-4595
DOI - 10.1111/j.1540-4609.2012.00347.x
Subject(s) - computer science , recommender system , conceptual framework , knowledge management , constructivist teaching methods , data science , teaching method , mathematics education , world wide web , psychology , sociology , social science
A comprehensive conceptual framework is developed and described for evolving recommender‐driven online learning systems (ROLS). This framework describes how such systems can support students, course authors, course instructors, systems administrators, and policy makers in developing and using these ROLS. The design science information systems research approach was used to develop the framework. The ROLS framework incorporates both the cognitive and situative perspectives of the constructivist paradigm of learning. Research propositions are developed to highlight new research opportunities for these systems. The framework demonstrates how various components of an evolving ROLS can be integrated to provide potential benefits for all users.