Investigating High School Students' Code Comprehension and Strategy Use Across Block-Based and Text-Based Programming

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Authors: Shan Zhang, Priyadharshini Ganapathy Prasad, Toni V. Earle-Randell, Yang Shi, Suma Bhat, Maya Israel
Cited by: 0
References: 5

Abstract

Understanding how students comprehend code is essential for designing effective instructional support in computer science (CS). While prior studies have often relied on written responses, few have examined students' reasoning processes through think-aloud data. In this study, we analyzed the verbal reasoning of 27 high school students as they completed block-based and text-based code comprehension tasks targeting loops and conditional statements. Using an adapted SOLO taxonomy framework, we found that most students were classified at lower levels, with performance declining as they transitioned from block-based to text-based code. Students' strategy use, informed by prior work on code comprehension, showed that walkthroughs and identifying program structures were the most common approaches. Text-based tasks more often led students to use pattern-recognition strategies, such as interpreting operators or identifying numerical patterns, whereas block-based tasks occasionally prompted them to articulate broader problem-solving approaches. Overall, these findings demonstrate the value of applying the SOLO taxonomy to evaluate students' programming levels and highlight how programming modality impacts both the depth of understanding and the strategies students employ during code comprehension.

Fields of Study & Subjects

Teaching and Learning Programming Science Education and Pedagogy Educational Robotics and Engineering

Publication details

Journal / source
ACM Technical Symposium on Computer Science Education (SIGCSE)
Pages
1603–1604
Publication date
13 February 2026
Language
EN