Academic journal article Educational Technology & Society

A Markov-Based Recommendation Model for Exploring the Transfer of Learning on the Web

Academic journal article Educational Technology & Society

A Markov-Based Recommendation Model for Exploring the Transfer of Learning on the Web

Article excerpt

Introduction

Recent advances in network bandwidth availability have increased use of Web-based education. In Web-based educational settings, information and communication technology (ICT) provides access to various resources, such as audio recordings, videos, images, and text. ICT has therefore had a dramatic impact on both learning processes and outcomes. For learners, the need for large amounts of information is increasing. However, not every learner can effectively organize and choose between these learning resources. A good learning management system (LMS) should provide learners with guidance that will assist them to make the best choices in their management of the available resources. Therefore, the selection of learning contents and recommended learning sequences have been recognized as two of the most interesting research topics in Web-based learning systems (Chen et al., 2005; Tseng et al., 2007).

Sharable Content Object Reference Model (SCORM) a model of web-based learning content and sequence standards, was proposed in 1997 at the 4th International forum on research and technology advances in digital libraries. This model was not innovative, but combined many existing international standards, such as the Content Packaging, Simple Sequencing (IMS, 2003), and LOM (IEEE LTSC, 2002). According to SCORM, learning contents, such as multimedia, images, slides or others learning objects, can be packaged and organized based on the SCORM standards to form a learning sequence. Notably, the SCORM-based learning sequence (ADL, 2004) offered a way to string several learning objects together and design instructions easily. In spite of the digital content learning sequence specifications instituted by SCORM, the pedagogical meaning of a learning sequence also needs to be recognized in e-Learning environments.

Generally speaking, the goals of education are not only the transfer of skills and knowledge in one context, but also the transfer and application of those skills and knowledge to other contexts. "Transfer of learning", which refers to the expansion and generalization of learning outcomes, is one major criterion of learning efficacy. The theory of transfer of learning was introduced by Thorndike and Woodworth (Thorndike & Woodworth, 1901). They explored similarities in the features of transfer of learning in different contexts. The theory asserted that effective transfer of learning depends on identical elements shared between the learning task and the transfer task. Several studies (De Corte, 2003; Haskell, 2001; Richman-Hirsch, 2001) have noted that transfer of learning is fundamental to learning because it generally aspires to impact on contexts quite different from the context of learning (Perkins & Salomon, 1992). In Web-based learning settings, however, there are two limitations that obstruct the transfer of learning. First, there is no guide to assist learners to conduct cross-subject transfer of learning in a Web-based learning environment. Second, while considerable attention has been paid in the past to research issues related to Web-based course design (Chan et al., 2006; Chen et al., 2005; Kabassi & Virvou, 2003; Zhu, 2007), the designer seldom takes the transfer of learning into consideration during the process of course design. Therefore, learning transfer is a significant issue for educators to take into consideration during the course-designing process for Web-based learning environments.

As noted before, transfer of learning is the process whereby skills learned in one situation or under one set of conditions are demonstrated in a different situation or under a different set of condition (Borich & Tombari, 1995). However, since transfer effects are not concrete, how to achieve and evaluate transfer of online learning is a challenging issue. In this study, we argue that transfer of online learning can be effectively achieved from group-learning sequences. …

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