Learning Motivation Assessment for High School Computer Science: Developing a Questionnaire for an Algorithm Learning Tool

ID: 49436 Type: Full Paper: Systems & Resources
  1. Aimee Theresa Avancena and Akinori Nishihara, Tokyo Institute of Technology, Japan

Tuesday, June 28 3:15-3:45 PM Location: Grand Ballroom AB

No presider for this session.

Abstract: This paper presents the development of a questionnaire that was used to assess the effects of an algorithm learning tool on the motivation for learning computer science among high school students. The questionnaire was also designed to determine certain motivation components for learning introductory computer science topics, particularly, algorithms. It was conducted among the students of a specialized science and technology high school in Japan for whom the algorithm learning tool was designed. Based on the students’ response to the questionnaire, there was an increase in their motivation level after using the learning tool. Using exploratory factor analysis, four motivation components were extracted and using confirmatory factor analysis, the construct validity of the revised questionnaire was proven. The relationship of the derived motivation components with the algorithm test performance of the students was also examined.


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