Effectiveness of AI-Based Learning Tools in Improving Engineering Mathematics Understanding
G Radhika,
G Sriraja Vijaya Krishna,
K M V Ramana,
M Srivani
Engineering mathematics is fundamental to engineering education, yet many students struggle to
achieve conceptual clarity and problem-solving proficiency through traditional teaching methods
alone. This study investigates the effectiveness of AI-based learning tools in improving engineering
mathematics understanding among undergraduate engineering students. An AI-assisted learning
environment incorporating adaptive practice, intelligent feedback, and personalized learning pathways
was implemented alongside conventional classroom instruction. Student performance was evaluated
using pre-test and post-test assessments, learning outcome metrics, and engagement indicators. The
results show that students using AI-based tools achieved significantly higher post-test scores, improved
conceptual understanding, greater problem-solving accuracy, and reduced error rates compared to
those relying solely on traditional instruction. Increased engagement and sustained learning activity
further highlight the benefits of AI-supported learning. The findings demonstrate that AI-based learning
tools, when integrated with conventional teaching, offer an effective approach to enhancing engineering
mathematics education.
