Abstract
Education is a process of gaining knowledge and is important for all as it plays a vital role in shaping the life of a student. The knowledge that we gain through education is evaluated through examinations that the teachers conduct periodically. Performance in an examination is an indication of a student’s proficiency in a particular subject. Courses of an educational curriculum are defined with learning objectives. Question papers consist of questions belonging to different cognitive levels. Generation of a quality question paper is essential as performance in it can influence the career decisions the students take in their life. It is difficult for the teachers to maintain the same level of complexity across the set of question papers that are generated. In this paper, we present a model where the questions are tagged automatically to their respective cognitive levels. It also helps in creating different sets of question papers containing unique questions and also provides a pictorial representation of the percentage of various cognitive levels present in the question paper. The pictorial representation helps the evaluation panel to have an overview of the distribution of cognitive levels in the question paper.
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Paul, A., Sabu, A., Abdulkader, B., George, P., Sreedevi, S. (2022). Qgen: An Automatic Question Paper Generator. In: Shakya, S., Balas, V.E., Kamolphiwong, S., Du, KL. (eds) Sentimental Analysis and Deep Learning. Advances in Intelligent Systems and Computing, vol 1408. Springer, Singapore. https://doi.org/10.1007/978-981-16-5157-1_43
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DOI: https://doi.org/10.1007/978-981-16-5157-1_43
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