The Practice of Differentiated Instruction Based on the Large Language Models in the Introduction to Computer Security Course

Differentiated instruction has always been a goal pursued in university education, aiming to meet the personalized learning needs of diverse students. However, due to the large number of students and limited teaching resources, traditional instruction methods often struggle to achieve true differentiation. With the development of large language models (LLMs) technology, its application in the field of education offers new possibilities for implementing differentiated instruction. This paper proposes a differentiated instruction model based on LLMs, which encompasses the utilization of prompt engineering with LLMs to craft survey forms and to aid in comprehending and enhancing educational content, as well as reinforcing the accuracy of concepts through objective assessments. A detailed introduction to the practical implementation of this model through the example of the "Introduction to Computer Security" course is provided. Through an analysis of course teaching outcomes, it demonstrates that the introduction of LLMs can enhance students' learning experiences and improve teaching effectiveness, while also having a positive impact on cultivating students' independent learning abilities and innovative thinking.