The Use of Computational Thinking Skills, Difficulties, and Strategies of Introductory Programming Students Solving Bebras Tasks

2026-06-01

AI Summary

This study investigates how novice learners without a computer science background employ computational thinking skills when solving computational problems, along with the primary difficulties they encounter and their coping strategies. By analyzing process data from students completing Bebras tasks, the research combines descriptive statistics with established coding schemes to identify computational thinking skills and uses thematic analysis to distill recurring challenges and strategies. The findings reveal, for the first time in a systematic manner, that algorithmic thinking, abstraction, and decomposition are the most frequently used computational thinking skills among non-CS beginners in authentic problem-solving contexts, and that the frequency of skill use is significantly positively correlated with solution accuracy. Moreover, students commonly struggle during task comprehension and planning phases. These results provide empirical foundations and targeted directions for instructional interventions in computational thinking education for non-specialist learners.

Abstract

Computational thinking (CT) is regarded as a fundamental skill set everyone should learn. Identifying when and how CT skills are used is challenging but important to inform interventions supporting their development. Previous research has examined how students and experts apply CT skills when solving introductory computational problems. However, the extent to which higher education students in introductory programming courses do so in depth is underexplored. We address this gap by examining how those students apply CT skills when solving computational problems, the difficulties they encounter, and the strategies they employ. We collected plans and solutions to Bebras tasks (short problems introducing CS concepts and considered effective for eliciting CT skills) in an introductory programming course for non-CS majors. We gathered 241 submissions from 58 students across five tasks, along with post-task comments and reflections on strategies. We analyzed the data using descriptive statistics, applied an existing coding scheme to identify CT skills, and conducted thematic analysis to identify difficulties and strategies. Submissions varied in structure and level of detail. The most prevalent CT skills were algorithmic thinking, abstraction, and decomposition, while evaluation and generalization appeared much less frequently. CT skill presence was positively associated with correct answers. Students faced challenges in four areas, including understanding the tasks and making a plan, and reported various problem-solving strategies. Consolidating and extending prior research on CT skills and problem solving, our findings show that students in introductory programming apply CT skills but can struggle to solve problems systematically and explain their reasoning. Furthermore, Bebras tasks create opportunities for this population to engage CT skills and could be used in future research.

Problem

• computational thinking
• introductory programming
• Bebras tasks
• problem solving
• higher education

Innovation

• computational thinking
• Bebras tasks
• introductory programming
• problem-solving strategies
• non-CS majors