Genetic Algorithm Application for Improving the Performance of Teaching Learning Process Through Collaborative Learning

Collaborative learning proves to be one of the greatest academia continuous improvement tools. Previous study indicated different methods depending upon different traits of the learners are found to be effective in group formation; however the students mark utilization in group formation is not explicitly used. Thus, this paper proposed a student’s group formation with intra and intergroup knowledge transfer as a focused approach supported with mathematical model which is optimized using a strong optimization tool real coded genetic algorithm (RCGA). Mathematical model is supported with hypothetical example. The first-generation solutions after implementing the real coded genetic algorithm shows significant improvement in fitness function. Also, an improvement of 5% in the average fitness value over that of initial population observed. The fitness function will keep on improving in subsequent generations which proved the robustness of the proposed model.