Bhowmik, Abhijit and Noorhuzaimi, Mohd Noor and Mazid-Ul-Haque, Md. and Miah, Md Saef Ullah and Karmaker, Debajyoti (2024) Evaluating Teachers’ Performance through Aspect-Based Sentiment Analysis. In: 9th IEEE International Conference for Convergence in Technology, I2CT 2024 , 5 - 7 April 2024 , Pune, India. pp. 1-6. (200137). ISBN 979-8-3503-9447-4
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Abstract
This research demonstrates a novel approach for evaluating teacher performance by conducting aspect-based sentiment analysis (ABSA) on student feedback. A large dataset of over 2 million student comments about teachers is analyzed using cutting-edge natural language processing and customized deep learning techniques. The methodology involves identifying positive, negative and neutral aspects of teaching using a BiLSTM model. Rigorous preprocessing, domain adaptation, and performance metrics ensure a robust and objective evaluation. The granular, nuanced insights obtained through this aspect-level sentiment analysis enable educational institutions to provide targeted and unbiased feedback to teachers on their strengths and areas needing improvement. Moreover, this work lays the foundation for detecting potentially fraudulent reviews in academic settings – a crucial capability for safeguarding assessment integrity. The detailed aspect-based analysis methodology presented here significantly advances subjective and holistic evaluation practices. This research has far-reaching implications for enriching teacher development while upholding the credibility of performance assessments through sentiment analysis innovations.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Additional Information: | Indexed by Scopus |
| Uncontrolled Keywords: | Aspect based sentiment analysis; Deep learning; Feature extraction; Fraud review in academic settings detection; Fraud reviews; Teacher Performance evaluation |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > T Technology (General) |
| Faculty/Division: | Institute of Postgraduate Studies Faculty of Computing |
| Depositing User: | Miss Amelia Binti Hasan |
| Date Deposited: | 30 Jun 2024 14:43 |
| Last Modified: | 30 Jun 2024 14:43 |
| URI: | http://umpir.ump.edu.my/id/eprint/41745 |
| Download Statistic: | View Download Statistics |
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