Exploring aspects of algorithmic thinking of informatics education students in solving linear equation systems

Algorithmic thinking contributes significantly to education, particularly in problem-solving within mathematics and information technology. This study aims to explore the characteristics of algorithmic thinking among informatics education students when solving mathematical tasks. The focus is on three main components of algorithmic thinking: decomposition, abstraction, and algorithmization. Employing a qualitative case study approach, data were collected through tests and semi-structured interviews. The findings indicate that students engage in algorithmic thinking activities across these three aspects during mathematical problem-solving. Decomposition activities involve identifying relevant information and dividing tasks into sub-tasks. Abstraction activities include recognition, building with, and integrating prior knowledge. Algorithmization activities encompass planning, composing, and applying systematic steps. These aspects are interconnected, forming a cognitive process rather than functioning independently. The study's novelty lies in categorizing activities associated with each aspect of algorithmic thinking. It contributes to the theoretical understanding that algorithmic thinking is a relevant cognitive activity that facilitates mathematical problem-solving.