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.

Question generation, adaptive practice, knowledge representation

N. Yuldashev “The role and utilizing of automated question generation into web based online examination systems”, in the Journal of Engineering and Technology (JET) ISSN(P): 2250-2394; ISSN(E): Applied Vol. 13, Issue 2, Dec 2023, 157-164 © TJPRC Pvt. Ltd.

M. Agarwal, R. Shah, and P. Mannem, “Automatic question generation using

discourse cues”, in Proceedings of the 6th Workshop on Innovative Use of NLP for Building Educational Applications, Stroudsburg, PA, USA: Association for Computational Linguistics, 2011, pp. 1–9, isbn: 9781937284039.

N. Bach and S. Badaskar, “A review of relation extraction”, Literature review

for Language and Statistics II, 2007.

J. C. Brown, G. A. Frishkoff, and M. Eskenazi, “Automatic question generation for vocabulary assessment”, in Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing, Association for Computational Linguistics, 2005, pp. 819–826.

S. Bird, E. Klein, and E. Loper, Natural language processing with Python. O’Reilly Media, Inc., 2009.

R. Brachman and H. Levesque, Knowledge representation and reasoning. Elsevier, 2004.

K. Bollacker, C. Evans, P. Paritosh, T. Sturge, and J. Taylor, “Freebase: a collaboratively created graph database for structuring human knowledge”, in Proceedings of the 2008 ACM SIGMOD international conference on Management of data, ACM, 2008, pp. 1247–1250.