Evaluating Students’ Emotional Response in Mobile Learning Using Kansei Engineering
Mobile learning is able to provide flexibility and conduciveness in learning, as learning materials are accessible anywhere and anytime using mobile devices. However, there are limited studies on understanding students’ emotion and emotional presence pertaining to online and mobile learning environments. Therefore, the main objective of this research is to identify the design elements for affective mobile learning material design. Kansei Engineering (KE) is being applied as the methodology for this research. In this research 10 specimens of mobile learning materials were installed from the Play Store specifically for the Database course where these specimens were evaluated using 25 Kansei Emotion Words (KW). A total of 31 participants have taken part in the experiment and conducted the experiment to assess students’ emotional response to mobile learning materials. The findings in this research reveal the five pillars of Kansei semantic space of emotions for mobile learning materials. Based on the Factor Analysis (FA), it reveals that the five pillars that consist of fun-motivated, learnable, challenging, preoccupied and engaged. On the other hand, this research also discusses design elements of mobile learning materials that might evoke certain emotions based on the five pillars that can be identified using the Partial Least Square (PLS) Analysis based on the interface design. However, there were some limitations and constraints during the course of the research such as the limitation of participants that were involved in the evaluation experiment, the mobile phone operating system itself and the technology that were used in this research. Therefore, future researchers should be able to deploy the research by including participants from various levels and can also use different mobile operating systems as well as technology in assessing the mobile learning environment.
KeywordsKansei Engineering Emotional Design Mobile Learning Student Emotion
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