Computational thinking skills in mathematics: A study of social arithmetic

Computational Thinking (CT) has emerged as a fundamental skill in mathematical problem-solving, fostering logical reasoning and structured approaches to tackling complex problems. Despite its significance, the integration of CT in mathematics education, particularly in secondary school curricula, remains insufficiently explored, leading to a gap in understanding students' proficiency in CT skills. This study aims to investigate the CT abilities of seventh-grade students in solving social arithmetic problems based on four key CT indicators: decomposition, pattern recognition, abstraction, and algorithmic thinking. Data were collected through a set of problem-solving tasks designed to assess each indicator comprehensively. The findings reveal that 25% of students demonstrate high CT proficiency (score >78.12), 52% exhibit medium proficiency (score between 17.78 and 78.12), and 23% fall into the low category (score <17.78). The mean scores for each CT indicator are as follows: decomposition (53), pattern recognition (46), abstraction (40), and algorithmic thinking (53), with abstraction emerging as the weakest area. These results indicate that the majority of students possess only a moderate level of CT competence, particularly struggling with abstraction, which involves identifying critical information and disregarding extraneous details. The study underscores the necessity of developing instructional strategies that enhance students' CT skills, particularly in pattern recognition and abstraction, to foster deeper mathematical understanding and problem-solving capabilities. The findings contribute