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Ex-Ante and Ex-Post Feature Evaluation of Online Courses Using the Kano Model

机译:使用卡诺模型对在线课程进行事前和事后特征评估

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Evaluating the effectiveness of online courses and what makes or breaks e-learning pose several challenges. Assessing educational data is generally a multivariate problem of high dimensionality. The implementation is often costly, the experimentation setup is complex, and supervision needs technical expertise. This research proposes an ex-ante and ex-post comparison of online course features using the Kano method from customer satisfaction analysis. Undergraduate students were asked to fill out questionnaires before and after taking a fully functional online course to compare their perceived importance of e-learning features. Attitudes towards 12 features, including ease of use, multimedia inclusion, account settings, and other specific features were gathered. The questionnaire also included feedback on overall experience, general positive and negative elements, and a free-form field for comments and suggestions regarding online courses. The results of this experiment suggest a shift in how students perceive the importance of features associated with online courses after successful completion.
机译:评估在线课程的有效性以及电子学习的成败带来了一些挑战。评估教育数据通常是一个高维度的多变量问题。实施通常成本高昂,实验设置复杂,监管需要专业技术。本研究利用顾客满意度分析中的卡诺方法,对在线课程的特点进行事前和事后比较。本科生被要求在参加一门功能齐全的在线课程之前和之后填写问卷,以比较他们对电子学习功能重要性的感知。收集了对12项功能的态度,包括易用性、多媒体包容性、帐户设置和其他特定功能。问卷还包括对总体经验的反馈、一般的积极和消极因素,以及一个自由形式的在线课程评论和建议字段。该实验的结果表明,学生在成功完成在线课程后,对与在线课程相关的特征的重要性的认知发生了变化。

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