ARCHIVES

1. Efendi, R., Lesmana, L. S., Putra, F., Yandani, E. & Wulandari, R. A. (2021). Design and Implementation of Computer Based Test (CBT) in
Vocational Education; Journal of Physics: Conference Series; 1764 (1):45-62;
2. Thalor, M. A. (2021). A Descriptive Answer Evaluation System Using Cosine Similarity Technique 2021 International Conference on
Communication information and Computing Technology (ICCICT), Conference Proceedings, IEEE XPlore
3. Usman, K. O. and Olaleye, S. B. (2022). Effect of Computer Based Test (CBT) Examination on Learning Outcome of Colleges of Education
Students in Nigeria; Mathematics and Computer Science; 7(3): 53-58
4. Paul, D. V. (2021). Answer Evaluation of Short Descriptive Questions. Developing a Keyword Extractor and Document Classifier: Emerging
Research and Opportunities, IG-Global
5. Pradeep, R. K. B., Thyagaraju, G. S., Sahana, K. B. and Prasad, S. (2025). A Comprehensive Review on Descriptive Answer Script Evaluation
Techniques, International Journal of Innovative Research in Computer Science and Technology (IJIRCST), 13(6):2347-5552DOI:
https://doi.org/10.55524/ijircst.2025.13.6.1
6. Nandini, V. and Maheswari, P. U. (2020). Automatic assessment of descriptive answers in online examination system using semantic relational
features, The Journal of Supercomputing, Springer; 76(3):4430-4448
7. Konade, S., Hirgude, Y., Kulkarni, A. Jadhav, A. & Sonar, L. (2024). Implementation of an automated answer evaluation system," in Proc.
IEEE International Conference on Computing, Power and Communication Technologies (IC2PCT), 5(1):457–462.
8. Zhao, S. (2022). Evaluation of English Subjective Questions Based on Deep Neural Networks; Scientific Programming, Hindawi
9. Chu, Y., Li, H., Yang, K., Shomer, H., Liu, H., CopurGencturk, Y. & Tang, J. (2024). "A LLM-powered automatic grading framework with
human-level guidelines optimization," arXiv:2410.02165;
10. Saha, S. K. and Rao, D. R. C. (2019). Development of a practical system for computerized evaluation of descriptive answers of middle school
level students, Interactive Learning Environment, 30(2):215-228
11. Tayal, P., Shetty, P. P., Harshita, R. and Sreenath. M. V. (2023). Evaluation of handwritten descriptive responses using machine learning – A
survey, in Proc. 2nd International Conference on Futuristic Technologies (INCOFT), Nov. 2023, pp. 1–5.
12. Zhou, N. (2024). Evaluating human and machine assessment: Introducing a hybrid approach for enhanced educational evaluation, Lect. Notes
Educ. Psychol. Publ. Med., 58(1):118–124
13. Meena, K. and Lawrance, R. (2016). Semantic Similarity based Assessment of Descriptive Type Answers; 2016 International Conference on
Computing Technologies and Intelligent Data Engineering (ICCTIDE'16)
14. Ejiim, S. (2017). An Overview of Computer Based Tests; Nigerian Journal of Computing Engineering and Technology; 5(2):47-59
15. Liu, J., Xu, Y. and Zhu, Y. (2019). Automated Essay Scoring based on Two-Stage Learning; arXiv:1901.07744v2 pp. 1-7
16. Kumar, Y., Aggarwal, S., Mahata, D., Shah, R. R., Kumaraguru, P., Zimmermann, R. (2019). Get IT scored using AutoSAS - an automated
system for scoring short answers; AAAI'19/IAAI'19/EAAI'19: Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence and
Thirty-First Innovative Applications of Artificial Intelligence Conference and Ninth AAAI Symposium on Educational Advances in Artificial
Intelligence; 1194:9662 – 9669
17. George, S. K. A., N. and Varghese, S. M. (2021). "Descriptive answer script grading system using CNN-BiLSTM network," International
Journal of Innovative Research in Computer Science and Technology, 9(5):139–144;
18. Khalkho, V. S., Malik. S. K , Rama, S. (2021). Automated Subjective Answer Evaluation; International Journal of Engineering and Computer
Science (IJECS), 11(5):117-124
19. Phalke, A. S., Bamnote, G. R. & Ahmad, S. (2021). Evaluating Descriptive Answer Assessment System with Machine Learning; International
Journal of Creative Research Thoughts, 9(7):657-669
20. Wangwiwattana, C. & Tongvivat, Y. (2023). "Automating academic assessment: A large language model approach," In 2023 7th International
Conference on Information Technology (InCIT), pp. 330–334.
21. Matos, A. R. (2023). Semantic similarity based automated answer script evaluation system using machine learning pipeline and natural language
processing; Advances in Intelligent Systems and Computing, pp. 495–509.
22. Manikandan, R., Yakshith, R. N., Sai, G., Vignavi, G., Reddy, S. K. & Reddy, N. S. D. (2024). Evaluating subjective answers using RNN and
NLP, In Challenges in Information, Communication and Computing Technology, 1(1):681–686.
23. Metan, J., Kumar, D. & Kumar H. (2024). "An automated approach to subjective answer evaluation using ML and NLP," in Proc. 2nd Int. Conf.
Advances in Information Technology (ICAIT), 1(1):1–7.
24. Singh, V. S., Verma, V., Srivastava, G. & Kumar, S. (2024). Exam assessor tool: An automated system for efficient answer sheet evaluation;
Asian Journal of Research in Computer Science, 17(6):36-57
25. Ashoka, S. B., Deep, K., Goutham, G., Ganihar, S. M. M., Udayaprasad, P. K., Lakshmikantha, G. C. & Dayananda, P. (2025). Efficient
automated evaluation of answer scripts using LLMs, NLP, and deep learning, In Data Science & Exploration in Artificial Intelligence, pp. 484–
491.
26. Bhanawat, V. (2019, June 28). The Architecture of Word2Vec; Medium