Wheelspinning frequency and reason in Robotutor
DOI:
https://doi.org/10.54691/bcpssh.v19i.1630Keywords:
Wheelspinning, Correction percentage, Six aspects, NumbersAbstract
20 March 2022. This paper describes wheelspinning happened in Robotutor team. Wheelspinning, which is a state that a student cannot make any effort although this student has worked hard. Since wheelspinning happens frequently on university student due to higher level of education, the theme is to analyze whether there is the same phenomenon on children and what is the reason for wheelspinning. The analytical tools are Rstudio and Excel. The main method for analyzing is the classification. The main table is split by columns, having “CHILD_ID”, “MATRIXNAME”, “ACTIVITIES”, “TOTALPROBLEMS”, “ACTIVITY_DURATION”, “FIRST_ATTEMPT_ PERCENTAGE_CORRECT”. After the analysis, the result shows that wheelspinning happens frequently on children, proved by a low percentage correct of all activities. Also, an initial reason of a low percentage correct is considered as children’s low interest of activities due to plenty of “BACKBUTTON” and short-time acitvities]. However, representing abstract definitions by numbers might be inaccurate], which is one of the limitations. Meanwhile, insisting for revision of definition representation is included in the future work.
Downloads
References
Beck, J.E., Gong, Y. (2013). Wheel-Spinning: Students Who Fail to Master a Skill. In: Lane, H.C., Yacef, K., Mostow, J., Pavlik, P. (eds) Artificial Intelligence in Education. AIED 2013. Lecture Notes in Computer Science (), vol 7926. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39112-5_44
Matsuda, N., Chandrasekaran, S., & Stamper, J. C. (2016). How quickly can wheel spinning be detected?. In Edm (pp. 607-608).
Beck, J., Rodrigo, M., & Mercedes, T. (2014, June). Understanding wheel spinning in the context of affective factors. In International conference on intelligent tutoring systems (pp. 162-167). Springer, Cham.
Zhang, C., Huang, Y., Wang, J., Lu, D., Fang, W., Stamper, J., ... & Aleven, V. (2019). Early Detection of Wheel Spinning: Comparison across Tutors, Models, Features, and Operationalizations. International Educational Data Mining Society.
Gong, Y., & Beck, J. E. (2015, March). Towards detecting wheel-spinning: Future failure in mastery learning. In Proceedings of the second (2015) ACM conference on learning@ scale (pp. 67-74).
Botelho, A. F., Varatharaj, A., Patikorn, T., Doherty, D., Adjei, S. A., & Beck, J. E. (2019). Developing early detectors of student attrition and wheel spinning using deep learning. IEEE Transactions on Learning Technologies, 12(2), 158-170.
Owen, V. E., Roy, M. H., Thai, K. P., Burnett, V., Jacobs, D., Keylor, E., & Baker, R. S. (2019). Detecting Wheel-Spinning and Productive Persistence in Educational Games. International educational data mining society.
Kai, S., Almeda, M. V., Baker, R. S., Heffernan, C., & Heffernan, N. (2018). Decision tree modeling of wheel-spinning and productive persistence in skill builders. Journal of Educational Data Mining, 10(1), 36-71.
Mu, T., Jetten, A., & Brunskill, E. (2020). Towards Suggesting Actionable Interventions for Wheel-Spinning Students. International Educational Data Mining Society.
Wan, H., & Beck, J. B. (2015). Considering the Influence of Prerequisite Performance on Wheel Spinning. International Educational Data Mining Society.
Downloads
Published
Issue
Section
How to Cite
