The effectiveness of statistical learning tasks based on Excel software in developing statistical thinking skills related to the labor market among students of the Applied College

Background/purpose. This study addresses the lack of statistical thinking skills among Applied College students, a key requirement for professional success. Traditional statistics education focuses on procedural and computational methods rather than conceptual understanding, leading to misconceptions and difficulties in data organization, summarization, and interpretation. The research aligns with Umm Al-Qura University's Program Transformation Project, emphasizing workforce readiness by enhancing statistics courses. The study's primary goal was to design and implement Excel-based statistical learning tasks to improve students' statistical thinking skills, particularly in the Banking and Finance diploma program. The study aimed to equip students with essential data-handling skills for professional environments by integrating practical applications. Materials/methods. This study utilized a mixed-methods approach, combining qualitative and quantitative techniques. The qualitative aspect focused on designing Excel-based statistical learning tasks and identifying essential statistical thinking skills, while the quantitative component employed a quasi-experimental design to evaluate task effectiveness. Results. The study demonstrated a significant improvement in statistical thinking skills among the experimental group using Excel-based tasks. It confirmed their effectiveness in developing key skills. It emphasized their importance in the job market, particularly for banking and finance diploma students, highlighting their role in enhancing future professional competencies. Conclusion. The study concluded that Excel-based statistical learning tasks effectively develop students' statistical thinking skills. These skills are essential for success in the job market, particularly for students in banking and finance diploma programs.