JACIII Vol.21 No.5 pp. 907-916
doi: 10.20965/jaciii.2017.p0907


Supporting the Exploration of the Learning Goals for a Continuous Learner Toward Creative Learning

Takato Okudo*, Tomohiro Yamaguchi*, Akinori Murata**, Takato Tatsumi**, Fumito Uwano**, and Keiki Takadama**

*National Institute of Technology, Nara College
22 Yata-cho, Yamatokoriyama, Nara, Japan

**The University of Electro-Communications
1-5-1 Chofugaoka, Chofu, Tokyo 182-8585, Japan

April 16, 2017
July 21, 2017
September 20, 2017
learning support system, sub-reward, continuous learning, learning goal space, creative learning

This paper proposes a learning goal space that visualizes the distribution of the obtained solutions to support the exploration of the learning goals for a learner. Subsequently, we examine the method for assisting a learner to present the novelty of the obtained solution. We conduct a learning experiment using a continuous learning task to identify various solutions. To assign the subjects space to explore the learning goals, several parameters related to the success of the task are not instructed to the subjects. In the comparative experiment, three types of learning feedbacks provided to the subjects are compared. These are presenting the learning goal space with obtained solutions mapped on it, directly presenting the novelty of the obtained solutions mapped on it, and presenting some value that is slightly related to the obtained solution. In the experiments, the subjects to whom the learning goal space or novelty of the obtained solution is shown, continue to identify solutions according to their learning goals until the final stage in the experiment is attained. Therefore, in a continuous learning task, our supporting method of directly or indirectly presenting the novelty of the obtained solution through the learning goal space is effective.

  1. [1] M. A. Boden, “The creative mind: Myths and mechanisms,” Abingdon, 2003.
  2. [2] C. B. Frey and M. A. Osborne, “The future of employment: how susceptible are jobs to computerization?,” Oxford Martin School Working Paper, No.7, pp. 1-72, 2013.
  3. [3] J. Smita and M. Trey, “Facilitating Continuous Learning: A Review of Research and Practice on Individual Learning Capabilities and Organizational Learning Environments,” Proc. of Selected Research and Development Papers at the Annual Convention of the Association of Educational Communications and Technology,,2012 [accessed Mar. 23, 2017].
  4. [4] T. Yamaguchi, K. Takemori, Y. Tamai, and K. Takadama, “Analyzing human’s continuous learning processes with the reflection sub task,” J. of Communication and Computer, Vol.12, No.1, pp. 20-27, 2015.
  5. [5] T. Yamaguchi, Y. Tamai, and K. Takadama, “Analyzing human’s continuous learning ability with the reflection cost,” Proc. of 41st Annual Conf. of the IEEE Industrial Electronics Society (IECON2015), pp. 2920-2925, 2015.
  6. [6] J. P. Guilford, “Creativity Research: Past, Present and Future,” Frontiers of creativity research: beyond the basics, pp. 34-64, 1987, [accessed Mar. 23, 2017].
  7. [7] R. A. Finke, T. B. Ward, and S. M. Smith, “CREATIVE COGNITION: Theory, Research, and Applications,” The MIT Press, 1992.
  8. [8] T. Okudo, T. Yamaguchi, and T. Takadama, “Designing the learning goal space for human toward acquiring a creative learning skill,” Proc. of the 19th Int. Conf. on Human-Computer Interaction (HCII2017), 2017.
  9. [9] J. Lehman, “Evolution through the Search for Novelty,” University of Central Florida, Ph.D. Computer Science, 2012.
  10. [10] A. K. Jain, M. N. Murty, and P. J. Flynn, “Data clustering: a review,” ACM Comput. Surv., Vol.31, No.3, pp. 264-323, 1999.

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Last updated on Oct. 20, 2017