| Title: |
PSFAS: Progressive Student Feedback Analysis System for Improved Teaching Learning with Intelligent Processing of Open-Responses |
| Language: |
English |
| Authors: |
Anitha Dhakshina Moorthy (ORCID 0000-0001-6915-3986); D. Kavitha (ORCID 0000-0001-7435-8222); R. Logeshwaran (ORCID 0009-0009-9097-8996); N. V. Vishnu Kumar; Vishnu Karthick |
| Source: |
Journal of Applied Research in Higher Education. 2025 17(6):2307-2329. |
| Availability: |
Emerald Publishing Limited. Howard House, Wagon Lane, Bingley, West Yorkshire, BD16 1WA, UK. Tel: +44-1274-777700; Fax: +44-1274-785201; e-mail: emerald@emeraldinsight.com; Web site: http://www.emerald.com/insight |
| Peer Reviewed: |
Y |
| Page Count: |
23 |
| Publication Date: |
2025 |
| Document Type: |
Journal Articles; Reports - Research |
| Education Level: |
Higher Education; Postsecondary Education |
| Descriptors: |
Feedback (Response); Student Evaluation of Teacher Performance; Teacher Improvement; Teacher Student Relationship; Graduate Students; Business Education; Automation; Artificial Intelligence; Natural Language Processing; Dravidian Languages; English; Translation; Error Correction; Models |
| DOI: |
10.1108/JARHE-04-2024-0157 |
| ISSN: |
2050-7003; 1758-1184 |
| Abstract: |
Purpose: Student open feedback is an essential element to improve the teaching service. Comprehending the feedback collected daily may not be possible especially in a large classroom. There is needed an automated system that processes feedback and helps to recommend focused, precise points to the teacher stating the positives and negatives of a class. Also, the feedback texts are neither going to be grammatically correct nor going to consist only of English. Hence, an automated feedback processing system is essential that processes the mixed-language language text that provides crisp clear insights to the teachers, thus making effective student-teacher interaction. Design/methodology/approach: This research is designed to analyse daily feedback from the students in grammarless English-Tamil mixed feedback and creates a dashboard that displays concise keywords regarding positive and negative aspects of the class. An ML-based system architecture is proposed for processing English-Tamil mixed grammarless feedback texts and validates the same with an experimental prototype and compares the results with other state-of-the-art models. This prototype classifies the text into different categories and provides the concise view with topic modelling techniques. This system is useful in progressive improvement of teaching learning process, subsequently leading to better teaching learning environment. Findings: The proposed web-based architecture is validated with a prototype by comparing the results with other state-of-the-art models. The accuracy of the results is higher (>90%) in the proposed architecture than other models ( |
| Abstractor: |
As Provided |
| Entry Date: |
2026 |
| Accession Number: |
EJ1497382 |
| Database: |
ERIC |