Virtual Agent Design Factors for the 21st Century Learners: A Kansei Approach

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 739)

Abstract

In recent years, Virtual Learning has gained wide popularity among the Higher Education Institutions (HEIs) to promote holistic education. Reviews have proven that Virtual Learning has proliferated over the years and it has created a dynamic learning culture among the 21st Century learners. These young learners from the digital age have different learning styles and vernaculars as they are much more diverse. It is also noted that it is challenging to keep these learners engaged in learning due to those differences. Therefore, it is vital to identify a learning tool that caters to these young learners from a diverse background and simultaneously optimize their learning satisfaction. To address these momentous issues, this research study aims to identify the design factors or specifications of a Virtual Agent (VA) deployed in the Virtual Learning Environment (VLE) to maximize learner’s satisfaction. In this exploratory study, the researchers have adapted Kansei Engineering (KE) approach that uses the quantitative analysis to identify the design factors of Virtual Agent. The respondents are undergraduate students from a HEI in Malaysia (N=107). The findings suggest that KE modus operandi had successfully paved the way for an effective design of VA that has high aesthetic value and identified attractiveness and expertness as key factors in VA design.

Keywords

Kansei Engineering Virtual Agent Virtual Learning Environment 21st Century Learners 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Barak, M.: Science teacher education in the twenty-first century: a pedagogical framework for technology-integrated social constructivism. Research in Science Education, 1-21 (2016).Google Scholar
  2. 2.
    Bickmore, T. W., & Picard, R. W.: Establishing and maintaining long-term human-computer relationships. ACM Transactions on Computer-Human Interaction (TOCHI), 12(2), 293-327 (2005).Google Scholar
  3. 3.
    Choi, J. I., & Hannafin, M.: Situated cognition and learning environments: Roles, structures, and implications for design. Educational technology research and development, 43(2), 53-69 (1995).Google Scholar
  4. 4.
    Cobb, P., & Jackson, K.: Towards an Empirically Grounded Theory of Action for Improving the Quality of Mathematics Teaching at Scale. Mathematics Teacher Education and Development, 13(1), 6-33 (2011).Google Scholar
  5. 5.
    Doumanis, I.: Evaluating humanoid embodied conversational agents in mobile guide applications (Doctoral dissertation, Middlesex University) (2013).Google Scholar
  6. 6.
    Grapragasem, S., Krishnan, A., & Mansor, A. N.: Current trends in Malaysian higher education and the effect on education policy and practice: An overview. International Journal of Higher Education, 3(1), p85. (2014).Google Scholar
  7. 7.
    Harada, A.: On the Definition of Kansei. In Modelling the Evaluation Structure of Kansei Conference. Volume 2, pp. 22 (1998).Google Scholar
  8. 8.
    Khan, R., & De Angeli, A.: Mapping the demographics of virtual humans. In Proceedings of the 21st British HCI Group Annual Conference on People and Computers: HCI… but not as we know it-Volume 2 (pp. 149-152). British Computer Society (2007, September).Google Scholar
  9. 9.
    Kim, Y., & Baylor, A. L.: Research-based design of pedagogical agent roles: a review, progress, and recommendations. International Journal of Artificial Intelligence in Education, 26(1), 160-169 (2016).Google Scholar
  10. 10.
    Krathwohl, D. R.: Methods of educational and social science research: An integrated approach. Longman/Addison Wesley Longman. (1993).Google Scholar
  11. 11.
    Levy, P.: Beyond kansei engineering: The emancipation of kansei design. International Journal of Design, 7(2) (2013).Google Scholar
  12. 12.
    Lokman, A. M.: Design & emotion: The kansei engineering methodology. Malaysian Journal of Computing, 1(1), 1-11 (2010).Google Scholar
  13. 13.
    Lokman, A. M., & Nagamachi, M.: Validation of kansei engineering adoption in e-commerce web design. Kansei Engineering International Journal, 9(1), 21-27 (2009).Google Scholar
  14. 14.
    Lokman, A. M., Awang, A. A., Zaili, R. A. M., & Fathir, M. F. M.: Designing Racial Unity through Films: The Kansei Engineering Approach. Advanced Science Letters, 22(5-6), 1368-1372 (2016).Google Scholar
  15. 15.
    Miksatko, J., Kipp, K. H., & Kipp, M.: The persona zero-effect: Evaluating virtual character benefits on a learning task with repeated interactions. In International Conference on Intelligent Virtual Agents (pp. 475-481). Springer Berlin Heidelberg. (2010, September).Google Scholar
  16. 16.
    Moreno, R., & Flowerday, T.: Students’ choice of animated pedagogical agents in science learning: A test of the similarity-attraction hypothesis on gender and ethnicity. Contemporary educational psychology, 31(2), 186-207 (2006).Google Scholar
  17. 17.
    Nagamachi, M. (1999). Kansei Engineering: A New Consumer-Oriented Technology For Product Development. In W. Karwowski and W. S. Marras (Eds.), The Occupational Ergonomics Handbook, CRC Press, Chap. 102, pp.1835-1848.Google Scholar
  18. 18.
    Nagamachi, M. (2010). Methods of Kansei/Affective engineering and specific cases of kansei products. Kansei/Affective Engineering, 13-30.Google Scholar
  19. 19.
    Nagamachi, M. (2016). Home applications of Kansei engineering in Japan: An overview. Gerontechnology, 15(4), 209-215.Google Scholar
  20. 20.
    Nagamachi, M., & Lokman, A. M. (2015). Kansei Innovation: Practical Design Applications for Product and Service Development (Vol. 32). CRC Press.Google Scholar
  21. 21.
    Page, T. (2014). Product attachment and replacement: implications for sustainable design. International Journal of Sustainable Design, 2(3), 265-282.Google Scholar
  22. 22.
    Ramachandiran, C. R., Mahmud, M. M., & Jomhari, N. (2016). The Effectiveness of Morfo as A Communication Enhancement Tool In 21st Century Learning. Journal of Media Critiques [JMC], 2(8).Google Scholar
  23. 23.
    See Yin Lim, J., Agostinho, S., Harper, B., & Chicharo, J. (2014). The engagement of social media technologies by undergraduate informatics students for academic purpose in Malaysia. Journal of Information, Communication and Ethics in Society, 12(3), 177-194.Google Scholar
  24. 24.
    Taharim, N. F., Lokman, A. M., Isa, W. A. R. W. M., & Noor, N. L. M. (2015). Investigating feasibility of mobile learning (M-learning) for history lesson. In International Colloquium of Art and Design Education Research (i-CADER 2014) (pp. 541-550). Springer Singapore.Google Scholar
  25. 25.
    Thorsteinsson, G. (2013). Developing an Understanding of the Pedagogy of Using a Virtual Reality Learning Environment (VRLE) to Support Innovation Education. The Routledge International Handbook of Innovation Education. Edited by LV Shavinina. Oxford: Routledge. ISBN-10, 415682215, 456-470.Google Scholar
  26. 26.
    Veletsianos, G., & Russell, G. S. (2014). Pedagogical agents. In Handbook of research on educational communications and technology (pp. 759-769). Springer New York.Google Scholar
  27. 27.
    Xu, D., Huang, W. W., Wang, H., & Heales, J. (2014). Enhancing e-learning effectiveness using an intelligent agent-supported personalized virtual learning environment: An empirical investigation. Information & Management, 51(4), 430-440.Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.School of ComputingAsia Pacific UniversityKuala LumpurMalaysia
  2. 2.Software Engineering Department, Faculty of Computer Science and Information TechnologyUniversity of MalayaKuala LumpurMalaysia

Personalised recommendations