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View all- An W(2022)Based on the Application of Deep Learning in College Education EvaluationMobile Information Systems10.1155/2022/29595962022Online publication date: 1-Jan-2022
Classification of Heuristics for Components of e-Learning
Article No.: 43, Pages 1 - 11
Abstract
The popularity of e-learning has cumulated in a wealth of research in this field, however, there is limited research related to the technological aspects of what makes e-learning components (content and interactive features) successful. Existing criteria that are available are primarily based on criteria used for evaluating new, untested systems such as web systems. It is often the case that these criteria are inappropriate for deciding on what learning components to use in an e-learning environment and ultimately for evaluating the successful use of components in an e-learning environment.
The purpose of this paper was to investigate and classify heuristics for e-learning environments with the primary focus on the different components of e-learning. A case study approach was used in an Enterprise Resource Planning (ERP) course at a South African university. The ERP e-Learning Environment (ERPeL) was designed using the guidelines and criteria proposed. Specific components incorporated into the ERPeL were badges, a leader board, live chats and a mobile learning (m-learning) application (app). Opinions of the ERPeL and its components were collected using a mixed methods approach. Useful feedback was received from the students using the proposed criteria. An analysis of the results was then used to improve the design of these components in subsequent Design-Based Research (DBR) cycles.
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September 2015
423 pages
ISBN:9781450336833
DOI:10.1145/2815782
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View all- An W(2022)Based on the Application of Deep Learning in College Education EvaluationMobile Information Systems10.1155/2022/29595962022Online publication date: 1-Jan-2022
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