Emotional responses in augmented reality based M-learning applications using Kansei engineering for secondary school students

Abstract

Design that evoked emotions are one of the main concerning issues in developing mobile applications for online learning in general and for augmented reality (AR) based mobile learning applications in specific. Emotional design could attract users by creating different feelings while using AR-based mobile learning applications. Suitable emotions related to design could motivate students towards fascinating learning experiences. The aim of this research is to evaluate the emotional responses of the students based on different designs in AR-based mobile learning applications using Kansei engineering technique. In this research, about thirty-two students from secondary school were involved in an experiment to identify the Kansei (emotion) words for AR-based mobile applications. The data gathered were analysed using factor analysis (FA), principal component analysis (PCA), and partial least square (PLS) analysis. The results revealed four important pillars of emotions or known as Kansei semantic space such as challenging-thinking, motivated, humorous, preoccupied and also touched as an additional pillar. Based on the PLS analysis of design elements of AR-based mobile learning applications suggested specific design and emotions based on the pillars. In conclusion, this research is motivated to give affective formulae that would guide the design of AR-based mobile learning materials in the future.