Factors Affecting the Academic Performance of Students with Hearing Impairment

Abstract

Around 5 million people in India are with hearing impairment. The higher education opportunities for students with hearing impairment are very limited. Only six institutes in the country provide undergraduate degrees to students with hearing impairment, according to accessible records. Academic achievement in the past, student background characteristics, and eLearning elements are all aspects that influence a student's academic performance. Hearing impairment-related characteristics may also need to be considered for a student with hearing impairment. Identification of these elements may aid teachers in developing individualized teaching plans for students. This paper tries to find the features that affect the performance of students with hearing impairment. The features included are socioeconomic, previous academic scores, and deafness-related factors. The dataset includes data of 224 undergraduate students who have hearing impairment. The preadmission data is used to analyze the performance of students with hearing impairment. The students are classified into different levels – low, medium, and high according to their performance. Different machine learning models are used to classify the students – Logistic Regression, Decision Tree, Support Vector Machine, KNN, Random Forest, and Naïve Bayes. The Random Forest model performed better compared to other models.