Programming Languages

Development of a Questionnaire on Self-concept, Motivational Beliefs, and Attitude Towards Programming

by Luzia Leifheit, Katerina Tsarava, Korbinian Moeller, Klaus Ostermann, Jessika Golle, Ulrich Trautwein, and Manuel Ninaus

In Workshop in Primary and Secondary Computing Education (WiPSCE). ACM Press, 2019.

This publication is related to the Computational Thinking research project.

Abstract

Academic self-concept, motivational beliefs, and attitudes towards a school subject are relevant for learning and educational achievement. A positive self-concept in science and mathematics is argued to motivate students to persist and advance in studying these subjects. In particular, self-concept, motivational beliefs, and attitudes towards STEM domains were found to be predictive of educational achievement. Recently, programming was suggested to be a key competence in education. To assess self-concept, motivational beliefs, and attitudes towards programming, we developed a new questionnaire based on existing scales for mathematics. The new questionnaire assesses the same aspects for programming on seven subscales, such as self-concept, belief about usefulness, and self-reported persistence when working on programming tasks. We conducted a pilot study in which we used this questionnaire to measure self-concept, motivational beliefs, and attitudes towards programming. The study was set in the context of an extracurricular course on computational thinking (CT) for elementary school students between the ages of seven and ten years. Before the start of the course, we assessed all 31 participating students’ self-concept, motivational beliefs, and attitudes towards programming using the developed questionnaire and their CT skills using the Computational Thinking test (CTt). Our results confirmed the expected associations between the aspects assessed by our questionnaire. However, we did not find significant associations of questionnaire results and CT skills. Consequently, future research involving a larger sample is needed to better understand the association between children’s actual performance and their self-concept, motivational beliefs, and attitudes towards programming.