ItemConference Paper

Hybrid Semantic Evaluation of Student Answers Using Rule Matching and BERT Embeddings

Title
Hybrid Semantic Evaluation of Student Answers Using Rule Matching and BERT Embeddings
Creator
Beri, Nimisha; Basha, J. Jeelan; Thilagam, M.; Suganthi, J.; Santhiya, C.; Hemaswathi, S.
Description
Accurate evaluation of student answers in online and traditional assessments is critical in education. In recent years, various text similarity-based methods have been proposed. However, there are certain challenges, such as the semantic and structural understanding of text. Thus, this paper uses the BERT model to present a hybrid evaluation framework that combines rule-based similarity techniques with deep semantic knowledge. The rule-based component utilizes predefined linguistic and domain-specific rules to ensure interpretability. At the same time, BERT-based similarity captures the semantic similarity and the paraphrased answers. Experimentation has been carried out on benchmark datasets, with the proposed hybrid model and human experts on manual evaluation. The performance comparison demonstrates that the hybrid model has performed significantly better than the traditional machine learning approaches in terms of accuracy and fairness of scoring. The proposed hybrid model is also compatible with deployment in educational platforms as it provides suitable feedback to learners. 2025 IEEE.
Source
International Conference on Intelligent Communication Networks and Computational Techniques, ICICNCT 2025;
Date
01-01-2025
Publisher
Institute of Electrical and Electronics Engineers Inc.
Subject
AI-based Assessment; BERT; Hybrid model; Natural Language Processing; Text similarity
Coverage
Beri N., School of Education, Lovely Professional University, Phagwara, India; Basha J.J., School of Management Studies, Reva University, Bengaluru, India; Thilagam M., Sri S.Ramasamy Naidu Memorial College, Department of Computer Science, Sattur, India; Suganthi J., Christ Deemed to be university, Department of Computer Science, Bengaluru, India; Santhiya C., Thiagarajar College of Engg., Department of Computer Sci. and Engg, Madurai, India; Hemaswathi S., Kalasalingam Academy of Research and Educ., Department of Information Technology, Tamil Nadu, India
Rights
Restricted Access; Hardcopy may be available in the library
Relation
ISBN: 979-833158623-2;
Format
online
Language
English
Type
Conference paper

Citation

Beri, Nimisha; Basha, J. Jeelan; Thilagam, M.; Suganthi, J.; Santhiya, C.; Hemaswathi, S., “Hybrid Semantic Evaluation of Student Answers Using Rule Matching and BERT Embeddings,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 17, 2026, https://archives.christuniversity.in/items/show/26015.

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