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Framework for User Experience Evaluation in MOOC Platforms

  • Conference paper
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Artificial Intelligence in HCI (HCII 2022)

Abstract

User Experience (UX) from the simplest perspective is defined in how people feel when using a product or service, which is fundamental to the success or failure of any product in the market. On the other hand, Massive Open Online Courses (MOOCs) have become one of the most popular trends in the field of education, reaching great popularity among several universities, which offer MOOCs through prestigious platforms, however, most of them do not meet the expectations and satisfaction of users, and mechanisms have not yet been designed to comprehensively measure the UX in these platforms. Therefore, the objective of this paper is to develop a comprehensive framework for the evaluation of UX in MOOC platforms from a technological point of view, after a systematic review of the literature to identify the most frequently applied and/or important evaluation approaches, which are analyzed and organized according to the following components: technological criteria and MOOC indicators, type of users, UX dimensions and UX factors. Through this approach it is possible to evaluate the UX in individual components, compare it between similar products and measure it over time.

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Correspondence to Germania Rodríguez Morales .

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Appendix

Appendix

Appendix 1.

Components of the proposed framework for UX evaluation in MOOC platforms (FUXE-MOOC).

figure a

Appendix 2.

Description of the UX evaluation approaches that make up FUXE-MOOC.

Table 1. Description of anticipated UX evaluation approaches.
Table 2. Description of task-based UX evaluation approaches.
Table 3. Description of general EUX or UX evaluation approaches.
Table 4. Description of cumulative UX evaluation approaches.

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Poma Gallegos, A., Rodríguez Morales, G., Torres-Carrión, P.V., Cueva Carrión, S. (2022). Framework for User Experience Evaluation in MOOC Platforms. In: Degen, H., Ntoa, S. (eds) Artificial Intelligence in HCI. HCII 2022. Lecture Notes in Computer Science(), vol 13336. Springer, Cham. https://doi.org/10.1007/978-3-031-05643-7_19

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  • DOI: https://doi.org/10.1007/978-3-031-05643-7_19

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