Abstract

With the growing importance of e-learning and increased competition among e learning providers, website designers must cater to users’ needs more accurately. Interfaces need to provide the features users demand to experience an optimal learning environment. This empirical research investigates whether the function of specific e learning features are either basic, performance related, indifferent, or attractive. The Kano model is applied to examine the impact of 73 e learning features on satisfaction. 1,034 completed questionnaires from an online survey distributed to economics and business students are the basis for the assignment to the Kano factors. Results show that among others, basic features include learning statistics, sample exams, and video-taped lectures. Educational videos are seen as an attractive factor. In terms of different groups of learners, findings confirm that Bachelor students are more demanding than Master and Doctoral students. Additionally, importance ratings allow recommendations for an implementation sequence for the features examined.

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(Dis-) Satisfiers for e-Learning User Interfaces

With the growing importance of e-learning and increased competition among e learning providers, website designers must cater to users’ needs more accurately. Interfaces need to provide the features users demand to experience an optimal learning environment. This empirical research investigates whether the function of specific e learning features are either basic, performance related, indifferent, or attractive. The Kano model is applied to examine the impact of 73 e learning features on satisfaction. 1,034 completed questionnaires from an online survey distributed to economics and business students are the basis for the assignment to the Kano factors. Results show that among others, basic features include learning statistics, sample exams, and video-taped lectures. Educational videos are seen as an attractive factor. In terms of different groups of learners, findings confirm that Bachelor students are more demanding than Master and Doctoral students. Additionally, importance ratings allow recommendations for an implementation sequence for the features examined.