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Evaluating learning management systems Adoption of hexagonal e‐learning assessment model in higher education

Evaluating learning management systems Adoption of hexagonal e‐learning assessment model in... Purpose – The purpose of this paper is to demonstrate the importance of undertaking a systemic view of learning management systems (LMSs) evaluation addressing the conceptualization and measurement of e‐learning systems success in higher education. Design/methodology/approach – The paper adopts a quantitative case perspective and derives a conceptual model for e‐learning assessment (Hexagonal e‐learning assessment model – HELAM). The model is empirically tested for validity and reliability in the university setting. Findings – Qualitative and quantitative findings have been presented, which will be valuable for academics and practitioners doing research in e‐learning evaluation. The findings support the flexibility and relevance of HELAM as an e‐learning assessment model. It highlights a number of success measures which are grouped under six dimensions. Research limitations/implications – Further research efforts should explore new dimensions or test the causal relationships among proposed dimensions within the boundary of e‐learning. In that, the paper is limited contextually where attention should be made not to generalize the findings beyond the empirical findings within the case analysis. Practical implications – The paper supports a practitioner perspective through a consideration of a holistic approach to e‐learning assessment. E‐learning system developers may find the findings useful when designing and implementing the LMS. Originality/value – The paper is original as the conceptual model has been derived through both theoretical constructs and empirical analysis. It provides an innovative approach to e‐learning assessment. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Transforming Government: People, Process and Policy Emerald Publishing

Evaluating learning management systems Adoption of hexagonal e‐learning assessment model in higher education

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Publisher
Emerald Publishing
Copyright
Copyright © 2009 Emerald Group Publishing Limited. All rights reserved.
ISSN
1750-6166
DOI
10.1108/17506160910960522
Publisher site
See Article on Publisher Site

Abstract

Purpose – The purpose of this paper is to demonstrate the importance of undertaking a systemic view of learning management systems (LMSs) evaluation addressing the conceptualization and measurement of e‐learning systems success in higher education. Design/methodology/approach – The paper adopts a quantitative case perspective and derives a conceptual model for e‐learning assessment (Hexagonal e‐learning assessment model – HELAM). The model is empirically tested for validity and reliability in the university setting. Findings – Qualitative and quantitative findings have been presented, which will be valuable for academics and practitioners doing research in e‐learning evaluation. The findings support the flexibility and relevance of HELAM as an e‐learning assessment model. It highlights a number of success measures which are grouped under six dimensions. Research limitations/implications – Further research efforts should explore new dimensions or test the causal relationships among proposed dimensions within the boundary of e‐learning. In that, the paper is limited contextually where attention should be made not to generalize the findings beyond the empirical findings within the case analysis. Practical implications – The paper supports a practitioner perspective through a consideration of a holistic approach to e‐learning assessment. E‐learning system developers may find the findings useful when designing and implementing the LMS. Originality/value – The paper is original as the conceptual model has been derived through both theoretical constructs and empirical analysis. It provides an innovative approach to e‐learning assessment.

Journal

Transforming Government: People, Process and PolicyEmerald Publishing

Published: May 29, 2009

Keywords: E‐learning; Information systems; Statistical analysis

References