Emotional augmented reality-based mobile learning design elements: A kansei engineering approach

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Abstract

In recent times, various studies have shown that Augmented Reality (AR) will be the next wave of online learning. This is because of the advent of powerful smartphones that has changed user experiences, thereby able to increase the capability of AR. There has been much concentration in previous studies on cognition towards the use of AR in education, in which little consideration has been given to emotions which is also an important aspect in learning. Based on this, the present research aims to identify salient connections between emotions and design elements of AR-based mobile learning material through the application of the Kansei Engineering (KE) approach. In order to achieve this study objective, the use of a human heart in relation to the mobile AR application of the KE approach was adopted in this research as a case study, in which seven specimens of the mobile AR application were evaluated including 55 emotions of Kansei Words (KW). Additionally, the kansei evaluation experiment of this study was carried out by 28 students from one of the public universities, after which the data were analysed using Factor and Principal Component Analysis. The results of this study show the important pillars of emotions or Kansei semantic space of emotions for AR-based mobile learning materials. Based on Factor Analysis, it revealed four main pillars; professional-motivated, confused, wandering-thrilled, challenging and one additional pillar; trustable. Besides that, this research also described design elements of AR-based mobile learning material that might evoke specific emotions based on the identified pillars. Finally, the findings of this research are hoped to be applicable as a guide in design during preparation of AR-based mobile learning materials with affective elements in the future.

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APA

Redzuan, F., Khairuddin, A. N. A., & Daud, N. A. (2019). Emotional augmented reality-based mobile learning design elements: A kansei engineering approach. Indonesian Journal of Electrical Engineering and Computer Science, 14(1), 413–420. https://doi.org/10.11591/ijeecs.v14.i1.pp413-420

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