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Analysis reveals AI-driven question generation enhances adaptive learning with personalized student models.
The main point of the thesis is the generation of questions from text using automation. Different methods of artificial intelligence and natural language processing are explained, along with the potential for adaptive learning in environments where questions are generated automatically. The student model is a compilation of ongoing data about the student that determines which skill to work on next. The report may contain details regarding the student's proficiency in certain skills, as well as their level of enjoyment and motivation. During fact practicing, the student model is utilized to predict how likely it is that a student knows a specific fact. The paragraphs below outline the most frequently used student models for factual knowledge.
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Yuldashev Nodirbek Abdumannob o‘g‘li (2025) studied this question.
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