Prediction of the change of learners' motivation in programming education for non-computing majors

Hidekuni Tsukamoto, Yasuhiro Takemura, Hideo Nagumo, Akito Monden, Ken Ichi Matsumoto

Research output: Contribution to journalConference article

3 Citations (Scopus)

Abstract

In the past, the authors had been analyzing motivation of the learners in programming education using the ARCS assessment metric. This metric had been used in the application experiment in 13 programming courses, and about 1,700 sets of data was collected. From these data, the learners' model, characteristics of the change of motivation, and ways of improving teaching materials had been clarified. However, these study results were obtained after the terms, when the programming courses were over, and thus did not contribute much to the ongoing programming education. For this reason, in this research, the methods for predicting the change of learners' motivation were studied so that the learners who may need support could be identified. The idea came from the experiment the authors conducted, in which the motivation of learners was analyzed by plotting the motivation scores of each factor in the ARCS model as a 3D graph. As a result, a decreasing tendency of motivation was observed when the distribution of the plot widened. After studying the tendency in detail, it was thought to be due to the influence of the variance of sub-level category scores. In the proposed method, the motivation of each learner is assessed in each lesson using the ARCS assessment metric. If variance of the motivation scores of a learner in a lesson is above a certain threshold value AND if mean of the scores has not decreased from the previous lesson, then the learner is identified as a candidate of learner who needs support at that lesson. In the application experiment, a programming course with 9 lessons was offered and 9 learners attended all the 9 lessons. In the experiment, 7 cases had been identified as the candidates of learners who need support, and out of those 7 cases, a decrease of motivation to less than average was observed in 5 cases.

Original languageEnglish
Article number7044221
JournalProceedings - Frontiers in Education Conference, FIE
Volume2015-February
Issue numberFebruary
DOIs
Publication statusPublished - Feb 17 2015
Externally publishedYes
Event44th Annual Frontiers in Education Conference, FIE 2014 - Madrid, Spain
Duration: Oct 22 2014Oct 25 2014

Keywords

  • ARCS motivation model
  • Motivation
  • Prediction
  • Programming education

ASJC Scopus subject areas

  • Software
  • Education
  • Computer Science Applications

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