ROLE OF ALGORITHMIC THINKING IN IMPROVING MATHEMATICS ACHIEVEMENT: A MACHINE LEARNING PERSPECTIVE

Abstract

This study examines the role of algorithmic thinking in improving mathematics-related computational performance among professionals engaged in software engineering and computational problem-solving, with a particular focus on machine learning environments. The research used a cross-sectional survey with a quantitative approach, with data gathered from 193 participants in Karachi and Hyderabad, Pakistan. A questionnaire with a five-point Likert scale was administered, and the data were analyzed using Structural Equation Modeling (SEM) in SmartPLS. The findings suggest that algorithmic thinking plays a crucial role in improving computational performance through structured thinking, sequencing, and problem-solving processes. Machine learning tools also enhance this relationship by offering these environments. The results underscore the need for cognitive-technology integration in the workplace. This research adds to the body of knowledge on artificial intelligence and computational thinking by showing how algorithmic thinking enhances performance in software and machine learning-based software systems.