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Student-Centric Explainable-AI Framework for Campus Placement Prediction

Pramila S. Patil, Isha R. Marathe, Sakshi S. Kamble

Abstract


Placement drives are an important opportunity for the students. Yet many students find it difficult to understand their preparation level. Most of the existing models provide only result like placed or not, without giving an explanation. To address this gap ,this paper introduce an explainable AI-based system which predict the placement readiness score along with the impact of every factor on performance, and also give the actions for improvement. It also provides the student with a list of companies that he or she would be eligible for.

This system uses different machine learning algorithms, to find a best fit model for predicting the placement. Student-related technical attributes and non-technical attributes are used as input features. The best performing model Random forest is selected of accuracy score 89.5 % .To increase the transparency, the system combines the shape, explainable AI technique to analyse the contribution of each feature.


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References


Senthilkumar, K. R., Vijayarajkumar, P. T., Sivasankari, & Balamani. (2023). Campus placement prediction using machine learning techniques. Handbook of Research in Big Data Analytics, Artificial Intelligence and Machine Learning.

Ruparel, M., & Swaminarayan, P. (2025). Enhanced student placement prediction using machine learning: A comparative evaluation of algorithms. International Journal of Engineering Trends and Technology.

Bhagat, S., Dhavale, S., Hegde, N., Jadhav, G., & Patil, P. (2024). Campus placement prediction using machine learning. Journal of Emerging Technologies and Innovative Research (JETIR).

Clemente, C. J., & Kwak, M. (2022). Utilizing data science and analytics in predicting campus placement. Issues in Information Systems.

Rao, A. V. S. S., Sreeram, K. N., Sahithi, D. J. S. L., Abhinav, K., Rayudu, R. S., & Dyuthi, M. L. (2025). Campus placement prediction using machine learning. Journal of Computer Science.

Indoori, A., Patwari, S., & Prathima, T. (n.d.). Analysis of campus placement data: A case study. Grenze International Journal of Engineering and Technology.

Khandale, S., & Bhoite, S. (2019). Campus placement analyzer: Using supervised machine learning algorithms. International Journal of Computer Applications Technology and Research.

Shahane, P. (2022). Campus placements prediction & analysis using machine learning. In Proceedings of the 2022 International Conference on Emerging Smart Computing and Informatics (ESCI). AISSMS Institute of Information Technology, Pune, India.

Maurya, L. S., Hussain, M. S., & Singh, S. (2021). Developing classifiers through machine learning algorithms for student placement prediction based on academic performance. Applied Artificial Intelligence, 35(6), 403–420.

Dutta, S., & Bandyopadhyay, S. K. (2020). Forecasting of campus placement for students using ensemble voting classifier. Asian Journal of Research in Computer Science.


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