Users in software world play key role in determining whether a software, including e-Learning system, has a long time of use or not. Past literatures have highlighted the importance of incorporating emotional requirement into software systems. It is important to consider what users need related to software. One of the critical component of a software systems that directly interacts with users is the interface. Users interface design (UID) could induce critical emotional experience and impression to users the first time they execute a software system. Kansei Engineering is adopted as a methodology to analyze users emotional experience towards the software UID. This research implemented a combination approach of Kansei Engineering and Analytic Hierarchy Process in order to analyze students’ emotional experience as users of e-Learning in higher learning institution, and then determines which of an open source e-Learning system that suits their positive emotional experience. This paper reports an attempt to discover the relationship between UID and users’ emotional experience in e-Learning systems. The research found that there were two critical students’ emotional factors, which are “clear” and “pleasant”. These two factors had a big impact in the selection of an e-Learning system, with factor of clear has larger impact. The research result then suggests the preferred e-Learning system for students based on those that evoked positive emotional experience to students. The result will benefit higher learning institution in promoting e-Learning, to extend the outreach potential of e-Learning among students.
L. Kun, Z. Yiying, H. Yeshen, Z. Yilin, T. Wei, and L. Xiaoxia, “Online Behaviour Analysis-Based Student Profile for Intelligent E-Learning”. Journal of Electrical and Computer Engineering. Article ID 9720396, 2017.
D. Rebecca and A. Elizabeth, “An Evaluation of Formative In-Class versus E-Learning Activities to Benefit Student Learning Outcomes in Biomedical Sciences”, Journal of Biomedical Education Article ID 9127978, Article ID 9127978, 2017.
A. Hadiana, A. M. Lokman A. M. “Kansei Evaluation in Open Source E-Learning System”, Jurnal Teknologi 78:12-3: 135-139, 2016.
H. Sihombing, M. Y. Yuhazri, S. H. Yahaya, and F. Syaifoelida, “The Kansei Design Characteristics towards Learning Style”, Journal of Engineering Article ID 584656, 2013.
F. Redzuan, A. M. Lokman, Z. A. Othman, and S. Abdullah, “Kansei Design Model for E-Learning: A Preliminary Finding”, Proceeding of the 10th European Conference on e-Learning (ECEL-2011). Brighton, 2011.
M. Nagamachi, and A. M. Lokman, Innovations of Kansei Engineering Industrial Innovation Series. Adedeji B. Badiru (Eds.), Taylor & Francis Group. Florida, 2011, pp. 85-88.
M. Nagamachi, and A. M. Lokman, Kansei Innovation: Practical Design Applications for Product and Service Development, Taylor & Francis Group, 2015, pp. 123-125.
D. A. Norman, Emotional Design: why we love (or hate) everyday things, New York: Basic Books, 2004, pp. 120-122.
K. G. D. Tharangie, C. M. A. Irfan, C. A. Marasinghe, and K. Yamada, “Kansei engineering assessing system to enhance the usability in E-learning web interfaces: Colour basis”, Proceeding 16th International Conference on Computers in Education( ICCE). Workshop on Testing and Assessment. Taipei, 2008.
A. Hadiana, B. Permana, and D. Tjahjadi. “Kansei Approach in Development of Application Interface Design Based on User’s Emotional Feeling”, European Journal of Engineering Research and Science, vol. 4, no. 10, pp. 121-126, October 2019.
S. Dehaene, The cognitive neuroscience of consciousness. Cambridge. MIT Press, 2001.
C. H. Chen, L. P. Khoo, and W. Yan, “An investigation into affective design using sorting technique and Kohonen self-organising map”, Advanced Engineering Software 37:334-349, 2006.
Y. Chen, “Research on Optimized Design of Kansei Engineering-based Web Interface”, International Conference on Computational and Information Science, 2013.
H. T. Chaminda, A. Basnayake, A. Madurapperuma, and M. Osano, “An interactive E-Learning system using Kansei engineering”, International Conference on Biometrics and Kansei Engineering. 157-162, 2009.
T. C. Sandanayake, and A. P. Madurapperuma, “Conceptual model for E-Learning systems using Kansei Engineering techniques”, International Conference on Biometrics and Kansei Engineering. 148-152, 2009.
F. Redzuan, A. M. Lokman, and Z. A. Othman, “Kansei semantic space for emotion in online learning”, 3rd International Conference on User Science and Engineering (i-USER). Shah Alam, 2014.
N. Sato, M. Anse, and T. Tabe, “A method for constructing a movie-selection support system based on Kansei Engineering”, The 12th International Conference on Human-Computer Interaction (HCII). Beijing, 2007.
T. L. Saaty, “Decision-making with the AHP: Why is the principal Eigevector Necessary. European Journal of Operational Research. 145:85-91, 2003.