Title: Modelling higher education environment based on knowledge system transfer between instructor and learners using genetic algorithm

Authors: J. Sowmiya; K. Kalaiselvi

Addresses: Vels Institute of Science, Technology and Advanced Studies, Pallavaram, Chennai 117, India. And Formerly: Vels University, India ' Vels Institute of Science, Technology and Advanced Studies, Pallavaram, Chennai 117, India. And Formerly: Vels University, India

Abstract: Performance of a teacher in classroom evaluates via feedback from students, assignment and exam. Traditionally, the performance of teachers in classrooms evaluate by administrators. However, the administrators never evaluate teacher performance by considering factors such as subject, experience, and student's performance, which influence student learning and performance in assignment and exams. In this paper, we evaluate the performance of teachers based on student's assignment and term exam results via genetic algorithm. The Genetic algorithm adjusts the weightage of student's performance in the assignment and terms exam with respect to various factors such as syllabus difficulty level and preparation time for term exams. The study was conducted for BCA course second-year students of total 50 in number. From the proposed teacher evaluation, the relation between teacher knowledge and student performance at the various level are analysed and suggests certain parameter must be considered in the evaluation for exact teacher's performance more accurately.

Keywords: genetic algorithm; teacher performance assessment; teacher knowledge transfer; student performance; knowledge transfer; non-cognitive; regression fit; knowledge mining; assessment; weightage; minimal.

DOI: 10.1504/IJSSE.2021.121458

International Journal of System of Systems Engineering, 2021 Vol.11 No.3/4, pp.268 - 283

Received: 19 Jun 2020
Accepted: 09 Nov 2020
Published online: 14 Mar 2022 *

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