Evaluating students' emotional response in video-based learning using Kansei Engineering

Recent studies have shown that multimedia learning materials are able to evoke positive emotions in students which in turn facilitates the learning process. Hence, in enabling the development of such learning materials, the knowledge of how design elements influence emotion should be continued in order for emotion to be engineered into video-based e-learning materials which is the main objective of this research. The research was conducted on postgraduate's students from one of the local universities using the Kansei Engineering approach by using 10 video specimens obtained from YouTube, 55 Kansei Emotion Words (KW), and 32 evaluation subjects. This research expedited evaluation experiments in order to assess students' emotional response to video-based e-learning materials. A multivariate analysis was performed to average the evaluation results acquired from subjects to identify the semantic space for video-based e-learning material for higher education and investigate design elements associated in order to be used as a guide in designing video-based e-learning material that embed targeted emotion in its design. The findings in this research reveal the five pillars of the Kansei semantic space of emotions for video-based e-learning materials. Based on the Factor Analysis, it reveals three main pillars; professional-motivated, fun, joking-humorous and two additional pillars; deceptive and puzzled whereas based on the Partial Least Square Analysis (PLS), the design elements of video-based e-learning materials are able to evoke specific emotions based on five pillars identified.