Analyzing the Emotional State of Students Using Generative Artificial Intelligence

This paper aims to find out how Generative AI models like GPT-3, when integrated with traditional teaching methods can enhance academic performance as well as the emotional well-being of students. Most of the digital education systems and tools only focus on curriculum delivery and fail to address the emotional states of students and their individual learning capabilities, this leads to the downfall of their academic progress and will yield poor learning outcomes. To address this issue, we have developed a system that analyzes the emotional states of students and then further categorizes them according to their learning pace (fast, medium, or slow). Our system works by first analyzing the survey responses collected from students using a scoring system that is predefined. Then it generates a personalized lesson plan tailored for each student according to the insights gained from the responses. With the integration of OpenAI's GPT-3 for the Lesson plan generation we ensure the content generated will be tailored specifically for each student's needs. Furthermore, it has been observed that using learning strategies that use AI-driven technology can create a more supportive and flexible educational environment which results in the student having better comprehension, motivation and increases academic success.