Computational Thinking Levels among Secondary School Students: A Pilot Descriptive Study by Gender, Age and Computational Thinking Dimensions

Abstract

Computational Thinking (CT) has emerged as an essential 21st-century skill, for problem-solving in a technology-driven world. However, despite its growing educational importance worldwide, empirical evidences on CT proficiency levels in Indian context remains underexplored. The present study was conducted to assess and describe CT levels among secondary school students using a standardized 40 item CT test, across gender, age, and CT dimensions. The study employed a pilot descriptive survey design. The sample consists of 30 Secondary school students, including 13 male students and 17 female students from a CBSE-affiliated PM SRI Demonstration School, Mysore, Karnataka, India with an age group of 13–15 years. The data were collected using a standardized 40 item computational thinking skill test (CTST) and the tool used to assess four dimension such as decomposition, abstraction, algorithmic thinking, and pattern recognition. Percentage analysis revealed that 56.7% of students demonstrated a moderate level of CT, while 43.3% showed a low level. Female students performed slightly higher mean CT scores than the male students and minor variations in CT scores were observed across different age groups. Dimension-wise analysis showed that decomposition recorded comparatively higher scores where algorithmic thinking showed relatively low performance. The findings highlighted the need for CT-based instructional interventions aligned with the NEP 2020 and the CBSE CT and AI Curriculum Framework.