- Title
- Boosting the opportunities of open learning (MOOCs) through learning theories
- Creator
- Fasihuddin, Heba A.; Skinner, Geoff D.; Athauda, Rukshan I.
- Relation
- GSTF Journal on Computing Vol. 3, Issue 3
- Publisher Link
- http://dx.doi.org/10.5176/2251-3043_3.3.280
- Publisher
- Global Science and Technology Forum (GSTF)
- Resource Type
- journal article
- Date
- 2013
- Description
- The recent evolution of computing technology has led to dramatic developments and changes in online learning. Open learning is a new form of online learning that allows learning materials to be freely available on the Internet and accessible to anyone who is interested. Different initiatives, which are based on the open learning concept, have been initiated by various prestigious institutions. Although all of these initiatives provide courses with free access to content, each has its own approach in terms of teaching, assessment and even their own goals of defining an open learning environment. Massive Open Online Courses is the term for courses provided in these open environments. These courses attract a large number of learners, however their success and efficacy in terms of the learning process has yet to be determined. The authors found that there is no clear model for open learning environments and therein lies our research objective. Many aspects still need to be considered and addressed in order to achieve a reliable and sustainable model. These aspects can be addressed with consideration to the principles of cognitive science so that better learning models can be obtained. This paper presents some learning theories that can be considered and applied to enhance open learning environments. The use of knowledge maps, as an approach to implement schema theory, was selected to present and organize the learning concepts. In addition, the Felder-Silverman learning styles theory was selected to personalize the learning environment and provide learning materials based on every learner’s needs and preferences.
- Subject
- adaptive learning; cloud computing; knowledge maps; learning styles; MOOCs; open learning
- Identifier
- http://hdl.handle.net/1959.13/1318796
- Identifier
- uon:23690
- Identifier
- ISSN:2010-2283
- Language
- eng
- Full Text
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