SENSE: a Student Performance Quantifier using Sentiment Analysis
Johanna Watkins, Marcos Fabielli, Mufti Mahmud
Abstract
Academic feedback is essential in secondary schools to keep a rapport between students, teachers, and parents and guardians. There are three main factors that contribute towards a student's progress: attitude, attendance and aptitude. Monitoring their progress is key to a student's development in school and allows both teachers and parents or guardians to support them to a greater extent. Annual reports are sent to a student's home to summarise their performance over the academic year, following set criterion from the government. One aspect of a student's report is the teacher's written comment, providing more details on a student's attitude towards their learning. However, families whose primary language is not English may struggle to interpret this information. Working in schools has demonstrated the diversity of students and their wide range of backgrounds, including - but not limited to - language barriers. This work proposes a system called SENSE (Student pErformance quaNtifier using SEntiment analysis) for improving the information conveyed in secondary school reports through means of natural language processing. By combining the three key features which contribute towards a student's progress, a numerical representation is produced for an easier interpretation. This reduces the likelihood of a tarnished relationship between home and schools through better means of conveying information and maintains communication between students, teachers and parents or guardians.