Enhancing Predictive Analytics in Education Using Computational Psychometrics

Prof. Ram Sharma

Abstract


This study explores the application of computational psychometrics to analyze educational behavior and improve predictive analytics in learning environments. By leveraging machine learning models on large-scale educational datasets, we identify patterns in learner behavior, performance, and engagement. The paper compares the proposed methods with traditional psychometric techniques, presenting quantitative results in tabular form. Findings suggest that computational psychometrics offers a robust approach to personalizing education, predicting outcomes, and informing interventions to enhance learner success.

References


Pillai, S. E. V. S., & Polimetla, K. (2024, February). Analyzing the Impact of Quantum Cryptography on Network Security. In 2024 International Conference on Integrated Circuits and Communication Systems (ICICACS) (pp. 1-6). IEEE.

Pillai, S. E. V. S., & Polimetla, K. (2024, February). Mitigating DDoS Attacks using SDN-based Network Security Measures. In 2024 International Conference on Integrated Circuits and Communication Systems (ICICACS) (pp. 1-7). IEEE.

Whig, P., & krishna Adusumilli, S. B. (2024). Leveraging AI and Machine Learning for Optimizing Supply Chain Management in Healthcare: A Predictive and Prescriptive Approach. International Scientific Journal for Research, 6(6).

Adusumilli, S. B. K. Mitigating Cybersecurity Risks in Embedded Systems A Software-First Approach.

Chintala, S. (2024). Strategies for Enhancing Data Engineering for High Frequency Trading Systems. International IT Journal of Research, ISSN: 3007-6706, 2(3), 1-10.

Dodda, S., Chintala, S., Kanungo, S., Adedoja, T., & Sharma, S. (2024). Exploring AI-driven Innovations in Image Communication Systems for Enhanced Medical Imaging Applications. Journal of Electrical Systems, 20(3s), 949-959.

Adusumilli, S. B. K. (2023). TOWARDS ENERGY-EFFICIENT AIML INFERENCE ON EDGE DEVICES SOFTWARE SOLUTIONS AND CHALLENGES. Journal of Engineering Sciences, 14(11).

Whig, P., & Adusumilli, S. B. K. (2023). Enhancing Healthcare Delivery Through AI-Driven Supply Chain Innovations: A Case Study Perspective. International Transactions in Artificial Intelligence, 7(7).

Chintala, S. Analytical Exploration of Transforming Data Engineering through Generative AI‖. International Journal of Engineering Fields, ISSN, 3078-4425.

Narani, S. R., Ayyalasomayajula, M. M. T., & Chintala, S. (2018). Strategies For Migrating Large, Mission-Critical Database Workloads To The Cloud. Webology (ISSN: 1735-188X), 15(1).

Chintala, S., Jindal, M., Mallreddy, S. R., & Soni, A. (2024). Enhancing Study Space Utilization at UCL: Leveraging IoT Data and Machine Learning. Journal of Electrical Systems, 20(6s), 2282-2291.

Ayyalasomayajula, M. M. T., Chintala, S., & Narani, S. R. INTELLIGENT SYSTEMS AND APPLICATIONS IN ENGINEERING.

Chintala, S., Kunchakuri, N., Kamuni, N., & Dodda, S. (2024, October). Developing an Adaptive Educational Chatbot for Personalized SQL Tutoring. In 2024 International Conference on Computing, Sciences and Communications (ICCSC) (pp. 1-5). IEEE.

Dodda, S., Chintala, S., Kunchakuri, N., & Kamuni, N. (2024, October). Enhancing Microservice Reliability in Cloud Environments Using Machine Learning for Anomaly Detection. In 2024 International Conference on Computing, Sciences and Communications (ICCSC) (pp. 1-5). IEEE.

Chintala, S. (2023). Improving Healthcare Accessibility with AI-Enabled Telemedicine Solutions. International Journal of Research and Review Techniques, 2(1), 75-81.

Adusumilli, S. B. K., Damancharla, H., & Metta, A. R. (2021). AI-Powered Cybersecurity Solutions for Threat Detection and Prevention. International Journal of Creative Research In Computer Technology and Design, 3(3).

Adusumilli, S. B. K., Damancharla, H., & Metta, A. R. (2020). Leveraging AI for Real-Time Sentiment Analysis in Social Media Networks. International Numeric Journal of Machine Learning and Robots, 4(4).

Kamuni, N., Dodda, S., Chintala, S., & Kunchakuri, N. (2024, October). Optimizing Machine Translation: A Benchmarking Suite for Efficiency and Quality Enhancement. In 2024 International Conference on Computing, Sciences and Communications (ICCSC) (pp. 1-7). IEEE.

Adusumilli, S., Damancharla, H., & Metta, A. (2020). Machine Learning Algorithms for Fraud Detection in Financial Transactions. International Journal of Sustainable Development in Computing Science, 2(1). Retrieved from https://www.ijsdcs.com/index.php/ijsdcs/article/view/639

Adusumilli, S., Damancharla, H., & Metta, A. (2021). Deep Learning Techniques for Image Recognition in Autonomous Vehicles. (2021). International Meridian Journal, 3(3). https://meridianjournal.in/index.php/IMJ/article/view/94


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