Browsing by Author "MUHAMMAD USMAN"

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    PREDICTING STUDENT FUTURE INTERACTION USING SELF ATTENTION MECHANISM WITH RANDOMIZATION
    (UMT, Lahore, 2021) MUHAMMAD USMAN
    In the modern era, finding quality education and testing the student’s ability on some standards has become a primary challenging task. To attend this problem, there are several methods designed, some are manual and some of them use technology. The latest and technical methods are more useful and reliable. In the pandemic situation, the education system using technology is better than old systems. In the latest methods, a large number of researchers proposed machine-based prediction methods for student study and their future results. In this thesis, an education model is proposed to predict the future results of the student as well as the correct domain or field selection for the student. The KCT (Knowledge Component Theory) based Model is proposed with Satisfying Results. The main goal is to introduce the tracking model based on Deep Knowledge. The EDNet dataset is utilized for the testing of the projected model. The research is based on some phases like data collection, Feature Engineering, and Model Implementation. The main contribution of the researcher is to accurately predict how students will perform in future interactions