A Comparative Analysis of Speed: AI-Driven Tool vs. Pen-and-Paper Method in Matrix Multiplication

Abstract The use of artificial intelligence (AI) in mathematical research is revolutionizing problem-solving approaches. However, the comparison of AI-based math tools with the traditional pen-and-paper problem-solving approach in terms of effectiveness remains underexplored. This study investigates the speed differences between AI-driven tools and the manual pen-and-paper problem-solving method when addressing complex matrix multiplication. Two groups of college students were formed: one group used the AI tool Wolfram Alpha, while the other employed the traditional manual calculation method. A set of benchmark matrix multiplication problems was chosen to assess computational challenges. Quantitative data on the speed of solutions were collected and analyzed. Preliminary findings indicate that AI-assisted methods significantly reduce computation time and excel in handling calculation-heavy tasks. The results suggest that AI’s computational capabilities offer a considerable advantage in terms of speed, showcasing its potential as a faster and more efficient tool for mathematical problem-solving. Keywords: Artificial Intelligence, Matrix Multiplication, Wolfram Alpha.