Abstract

Linear algebra is a very important branch of mathematics that provides powerful tools for multiple disciplines and fields to help us understand and solve a variety of complex real-world problems. Therefore, learning and mastering linear algebra is essential for success in science, engineering, and technology. This paper explores strategies to improve the quality of linear algebra teaching through teaching evaluation methods. Both quantitative methods like analyzing student grades and test performance, and qualitative methods like student feedback are used. The data is integrated to identify problems and develop solutions. Strategies include optimizing course content by focusing on key concepts, increasing practical application cases; innovating teaching methods through blended learning and group work; and personalized teaching with flexible learning paths and targeted tutoring. Regular evaluation of teaching effectiveness and continuous adjustment of strategies are emphasized. The aim is to motivate students, deepen understanding, and enhance learning outcomes. This study provides valuable experience for improving STEM education quality through data-driven teaching evaluation and adjustment.