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Advanced E-Learning Quality Improvement Methods in Government Organizations

Shu-Ping Lin, Chen-Lung Yang and Thao-Minh Ho
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Shu-Ping Lin: Chung Hua University, Taiwan
Chen-Lung Yang: Chung Hua University, Taiwan
Thao-Minh Ho: Chung Hua University, Taiwan

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Abstract: Being equipped with advanced information and communication technologies, e-learning systems have gained dramatic demands in recent years. Especially, to government organizations, e-learning plays a critical role to sustainable competitiveness through facilitating staff and authorities’ continuing professional and training development. Consequently, e-learning quality management is perceived to significantly promote users’ learning effects, satisfaction, and use intention. However, despite the increasing growth rate worldwide, failures in e-leaning still exist and little is known about why many users stop using e-learning after early-stage experience. In spite of previous studies’ attempt in pointing out key factors influencing e-learning success, missing from the extant literature is the investigation of e-learning quality failure gaps and appropriate recovery solutions. Therefore, this paper aims to target government organizations to develop an innovative methodology which can solve these research missing gaps of (1) identifying the key failure factors significantly influencing users’ overall satisfaction and use behaviour and (2) seek the optimal improvement solutions. Accordingly, the recovery capability ranking of achieved determinant factors is firstly established; then, Quality Function Deployment (QFD) method is employed to seek optimal recovery solutions. The results prove five top improvement solutions, namely ‘creation of e-learning support management team’, ‘creation of e-learning agency’, ‘instructors’ professionalism enhancement’, ‘reward system for proactive participation’, and ‘information security certification’. The results hope to provide academicians and organizations with innovative reference method and helpful guidelines for advancing e-learning quality in a shorter and more effective manner.

Keywords: e-learning quality improvement; Quality Function Deployment; recovery capability ranking; government organizations (search for similar items in EconPapers)
Date: 2015
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