Classification and Analysis of College Students’ Skills Using Hybrid AI Models

Abstract

Each individual diversifies in the population with certain characteristics. Thus, diversity is a scientifically proven and widely accepted phenomenon when the human being is a concern. One of the areas where the diversity of human beings is mostly paid attention to is called the learning process, since different forms of responses could be observed. For example, each student perceives, assimilates, and uniquely processes the information when being transmitted to him, which confirms the inherited diversity. In this regard, educational systems are required to deal effectively with students and to apply the principles of personalized learning, which is pertinent to learning processes that meet the individual needs and interests of learners. By doing so, taking into account their unique characteristics, talents, skills, inclinations, and desires are satisfied. This manuscript presents an innovative model to classify college students’ skills. A hybrid artificial intelligence (AI) system that fully automates the process of personalized training is proposed based on individual skills by taking into account the priority of personalized and fully customized learning systems. The process specifically utilizes the Rasch statistical analysis model and an innovative fuzzy Bayesian network. Higher-level reasoning is generated for the automated and personalized learning process in which college students are automatically classified into a certain category based on their skills.