Tags:Bloom Taxonomy, Fuzzy Inference System, MATLAB and Soft computing
Abstract:
Covid-19: a pandemic situation in the world gives a turning point to the education system and it becomes e-education. E-learning is an emerging trend in the digital era and empowerment of this trend is necessary. Traditional education systems trying to adopt this new method of teaching and learning. But only teaching and learning are not sufficient in the education system. We have to focus on learners and the environmental impact on them. The traditional education system is unable to resolve all the issues that arise due to obstacles such as understanding ability, thinking, mood, concentration, etc. Proposed research work focusing on designing, developing, and modeling of soft computing decision-making model for solving real-life problems and learners capability in the education system. This research work uses Fuzzy Inference System (FIS) which is one of the applications in MATLAB software, for analyzing learner's results from the obtained scores and other factors related to the environment. It also predicts the learner which is helpful in e-learning.
A Softcomputing Approach for Predicting and Categorising Learner’s Performance Using Fuzzy Model