Aspect-based sentiment analysis model for evaluating teachers’ performance from students’ feedback
Evaluating teachers' performance is a fundamental pillar of educational enhancement, guiding the evolution of pedagogical practices and fostering enriched learning environments. This study pioneers an innovative approach by harnessing sentiment analysis within an aspect-based framework to decip...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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AIUB Office of Research and Publication
2023
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| Subjects: | |
| Online Access: | https://umpir.ump.edu.my/id/eprint/44335/ |
| _version_ | 1848827326079434752 |
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| author | Bhowmik, Abhijit Noorhuzaimi, Mohd Noor Miah, Md Saef Ullah Karmekar, Debajyoti |
| author_facet | Bhowmik, Abhijit Noorhuzaimi, Mohd Noor Miah, Md Saef Ullah Karmekar, Debajyoti |
| author_sort | Bhowmik, Abhijit |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | Evaluating teachers' performance is a fundamental pillar of educational enhancement, guiding the evolution of pedagogical practices and fostering enriched learning environments. This study pioneers an innovative approach by harnessing sentiment analysis within an aspect-based framework to decipher the intricate emotional nuances embedded within students' feedback. By categorizing sentiments as positive, negative, and neutral, we delve into the diverse perceptions of teaching aspects, offering a multifaceted portrait of educators' contributions. Through meticulous data collection, preprocessing, and a deep learning sentiment analysis model, we dissected student comments into distinct teaching aspects. The subsequent sentiment analysis unearthed positive, negative, and neutral sentiments. Positive sentiments highlighted strengths and effective communication, while negative sentiments illuminated areas for growth. Neutral sentiments provided contextual equilibrium, forming a holistic tapestry of teachers' performance. The proposed model achieved 86\% F1 score for classifying sentiments into three classes. |
| first_indexed | 2025-11-15T03:58:56Z |
| format | Article |
| id | ump-44335 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T03:58:56Z |
| publishDate | 2023 |
| publisher | AIUB Office of Research and Publication |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-443352025-08-27T06:54:46Z https://umpir.ump.edu.my/id/eprint/44335/ Aspect-based sentiment analysis model for evaluating teachers’ performance from students’ feedback Bhowmik, Abhijit Noorhuzaimi, Mohd Noor Miah, Md Saef Ullah Karmekar, Debajyoti T Technology (General) Evaluating teachers' performance is a fundamental pillar of educational enhancement, guiding the evolution of pedagogical practices and fostering enriched learning environments. This study pioneers an innovative approach by harnessing sentiment analysis within an aspect-based framework to decipher the intricate emotional nuances embedded within students' feedback. By categorizing sentiments as positive, negative, and neutral, we delve into the diverse perceptions of teaching aspects, offering a multifaceted portrait of educators' contributions. Through meticulous data collection, preprocessing, and a deep learning sentiment analysis model, we dissected student comments into distinct teaching aspects. The subsequent sentiment analysis unearthed positive, negative, and neutral sentiments. Positive sentiments highlighted strengths and effective communication, while negative sentiments illuminated areas for growth. Neutral sentiments provided contextual equilibrium, forming a holistic tapestry of teachers' performance. The proposed model achieved 86\% F1 score for classifying sentiments into three classes. AIUB Office of Research and Publication 2023 Article PeerReviewed pdf en cc_by_nc_nd_4 https://umpir.ump.edu.my/id/eprint/44335/1/Aspect-based%20sentiment%20analysis%20model%20for%20evaluating%20teachers%E2%80%99.pdf Bhowmik, Abhijit and Noorhuzaimi, Mohd Noor and Miah, Md Saef Ullah and Karmekar, Debajyoti (2023) Aspect-based sentiment analysis model for evaluating teachers’ performance from students’ feedback. AIUB Journal of Science and Engineering, 22 (3). pp. 287-294. ISSN 1608-3679. (Published) https://doi.org/10.53799/ajse.v22i3.921 https://doi.org/10.53799/ajse.v22i3.921 https://doi.org/10.53799/ajse.v22i3.921 |
| spellingShingle | T Technology (General) Bhowmik, Abhijit Noorhuzaimi, Mohd Noor Miah, Md Saef Ullah Karmekar, Debajyoti Aspect-based sentiment analysis model for evaluating teachers’ performance from students’ feedback |
| title | Aspect-based sentiment analysis model for evaluating teachers’ performance from students’ feedback |
| title_full | Aspect-based sentiment analysis model for evaluating teachers’ performance from students’ feedback |
| title_fullStr | Aspect-based sentiment analysis model for evaluating teachers’ performance from students’ feedback |
| title_full_unstemmed | Aspect-based sentiment analysis model for evaluating teachers’ performance from students’ feedback |
| title_short | Aspect-based sentiment analysis model for evaluating teachers’ performance from students’ feedback |
| title_sort | aspect-based sentiment analysis model for evaluating teachers’ performance from students’ feedback |
| topic | T Technology (General) |
| url | https://umpir.ump.edu.my/id/eprint/44335/ https://umpir.ump.edu.my/id/eprint/44335/ https://umpir.ump.edu.my/id/eprint/44335/ |