MASTERING CHOICES: DECISION-MAKING AND STUDENT ACADEMIC PERFORMANCE
Abstract
This study aims to investigate the correlation between decision-making skills and the academic achievement of second-stage students in computer science departments, specifically in the subject of numerical analysis. The importance of teaching thinking skills and their application in problem-solving has become increasingly recognized in both academic and practical contexts. While possessing knowledge is valuable, it is the ability to effectively use and apply that knowledge that truly contributes to success. Therefore, there is a growing need to incorporate teaching methods that enhance students' decision-making abilities, as this helps them strengthen their judgment, evaluate evidence, and make sound decisions.
The impact of thinking skills and decision-making on academic success has been a topic of controversy among researchers. In the field of mathematics education, it becomes crucial to determine how learners distinguish the right decisions in solving mathematical problems and how this affects their achievement in the subject. The researcher, who works in the Department of Computer Science, noticed that students frequently struggled to apply the concepts of numerical analysis, a prerequisite subject, when programming proposed solutions for mathematical problems. This inability to make appropriate decisions regarding the best solutions adversely affected their academic performance.
To address this issue, the researcher conducted a study to explore the relationship between decision-making skills and the achievement of second-stage students in computer science departments within education faculties. The focus was specifically on the subject of numerical analysis. The study aimed to understand the nature of this correlation and its impact on students' performance in mathematics.
The findings of this research are expected to contribute to the existing knowledge on the importance of decision-making skills in academic settings, particularly in the field of computer science education. The study may also provide insights into the specific challenges faced by students when applying numerical analysis concepts and making decisions regarding programming solutions. Ultimately, the results can inform the development of teaching strategies that promote effective decision-making and enhance students' achievement in mathematics.
