Assessing the Effectiveness of Personalized Adaptive Learning in Teaching Mathematics at the College Level

Abstract

Personalized adaptive learning tailors’ education to each student’s unique needs by adjusting materials, tasks, and feedback based on their individual skill levels and progress. This paper details the development and implementation of a personalized adaptive learning platform designed to assess students’ mathematical abilities and offer customized exercises that align with their strengths and areas for improvement. A pilot study conducted with 118 students at Aktobe Higher Polytechnic College (Kazakhstan) demonstrated that this approach led to significant improvements in academic performance, engagement, and motivation compared to traditional teaching methods. By providing individualized learning paths and real-time feedback, the platform enhanced students’ problem-solving abilities and overall understanding of mathematics. This paper also explores the platform’s design, adaptive algorithms, and the measurable impact on student outcomes, highlighting the potential of personalized adaptive learning to transform educational practices and improve learning effectiveness in diverse academic environments.