Computational Psychometrics: Analyzing Educational Behavior in Learners Using Machine Learning
Abstract
The rise of digital learning platforms has enabled the collection of vast learner data, offering insights into educational behavior. This paper presents a computational psychometrics approach that applies machine learning techniques to analyze student engagement, learning patterns, and academic performance. We introduce a predictive model that classifies learners based on behavioral indicators and compares its performance with existing methodologies. The results demonstrate the effectiveness of AI-driven psychometric analysis in improving personalized learning and educational outcomes.
References
Davuluri, M. (2024). AI in Healthcare Fraud Detection: Ensuring Integrity in Medical Billing. International Machine learning journal and Computer Engineering, 7(7).
Davuluri, M. (2024). AI in Geriatric Care: Supporting an Aging Population. International Numeric Journal of Machine Learning and Robots, 8(8).
Davuluri, M. (2023). AI for Healthcare Workflow Optimization: Reducing Burnout and Enhancing Efficiency. International Numeric Journal of Machine Learning and Robots, 7(7).
Davuluri, M. (2023). AI in Surgical Assistance: Enhancing Precision and Outcomes. International Machine learning journal and Computer Engineering, 6(6).
Davuluri, M. (2022). AI in Mental Health: Transforming Diagnosis and Therapy. International Machine learning journal and Computer Engineering, 5(5).
Davuluri, M. (2021). AI for Chronic Disease Management: Improving Long-Term Patient Outcomes. International Journal of Machine Learning and Artificial Intelligence, 2(2).
Davuluri, M. (2021). AI in Personalized Oncology: Revolutionizing Cancer Care. International Machine learning journal and Computer Engineering, 4(4).
Davuluri, M. (2020). AI-Driven Drug Discovery: Accelerating the Path to New Treatments. International Journal of Machine Learning and Artificial Intelligence, 1(1).
Davuluri, M. (2020). AI in Pediatric Healthcare: Transforming Care for Younger Patients. International Numeric Journal of Machine Learning and Robots, 4(4).
Davuluri, M. (2018). AI in Preventive Healthcare: From Risk Assessment to Lifestyle Interventions. International Numeric Journal of Machine Learning and Robots, 2(2).
Davuluri, M. (2017). AI-Enhanced Telemedicine: Bridging the Gap in Global Healthcare Access. International Numeric Journal of Machine Learning and Robots, 1(1).
Kolla, V. R. K. (2020). Forecasting the Future of Crypto currency: A Machine Learning Approach for Price Prediction. International Research Journal of Mathematics, Engineering and IT, 7(12).
Kolla, V. R. K. (2018). Forecasting the Future: A Deep Learning Approach for Accurate Weather Prediction. International Journal in IT & Engineering (IJITE).
Kolla, V. R. K. (2016). Analyzing the Pulse of Twitter: Sentiment Analysis using Natural Language Processing Techniques. International Journal of Creative Research Thoughts.
Kolla, V. R. K. (2015). Heart Disease Diagnosis Using Machine Learning Techniques In Python: A Comparative Study of Classification Algorithms For Predictive Modeling. International Journal of Electronics and Communication Engineering & Technology.
Kolla, V. R. K. (2020). Paws And Reflect: A Comparative Study of Deep Learning Techniques For Cat Vs Dog Image Classification. International Journal of Computer Engineering and Technology.
Kolla, V. R. K. (2016). Forecasting Laptop Prices: A Comparative Study of Machine Learning Algorithms for Predictive Modeling. International Journal of Information Technology & Management Information System.
Kolla, V. R. K. (2021). Cyber security operations centre ML framework for the needs of the users. International Journal of Machine Learning for Sustainable Development, 3(3), 11-20.
Kolla, V. R. K. (2021). Prediction in Stock Market using AI. Transactions on Latest Trends in Health Sector, 13(13).
Kolla, V. R. K. (2020). India’s Experience with ICT in the Health Sector. Transactions on Latest Trends in Health Sector, 12(12).
Deekshith, A. (2020). AI-Enhanced Data Science: Techniques for Improved Data Visualization and Interpretation. International Journal of Creative Research In Computer Technology and Design, 2(2).
Deekshith, A. (2021). Data engineering for AI: Optimizing data quality and accessibility for machine learning models. International Journal of Management Education for Sustainable Development, 4(4), 1-33.
Deekshith, A. (2022). Cross-Disciplinary Approaches: The Role of Data Science in Developing AI-Driven Solutions for Business Intelligence. International Machine learning journal and Computer Engineering, 5(5).
Deekshith, A. (2023). Scalable Machine Learning: Techniques for Managing Data Volume and Velocity in AI Applications. International Scientific Journal for Research, 5(5).
DEEKSHITH, A. (2018). Seeding the Future: Exploring Innovation and Absorptive Capacity in Healthcare 4.0 and HealthTech. Transactions on Latest Trends in IoT, 1(1), 90-99.
DEEKSHITH, A. (2017). Evaluating the Impact of Wearable Health Devices on Lifestyle Modifications. International Transactions in Artificial Intelligence, 1(1).
DEEKSHITH, A. (2016). Revolutionizing Business Operations with Artificial Intelligence, Machine Learning, and Cybersecurity. International Journal of Sustainable Development in computer Science Engineering, 2(2).
DEEKSHITH, A. (2015). Exploring the Foundations, Applications, and Future Prospects of Artificial Intelligence. International Journal of Sustainable Development in computer Science Engineering, 1(1).
DEEKSHITH, A. (2014). Neural Networks and Fuzzy Systems: A Synergistic Approach. Transactions on Latest Trends in Health Sector, 6(6).
Deekshith, A. (2023). Transfer Learning for Multilingual Speech Recognition in Low-Resource Languages. International Transactions in Machine Learning, 5(5).
Boppiniti, S. T. (2023). Data Ethics in AI: Addressing Challenges in Machine Learning and Data Governance for Responsible Data Science. International Scientific Journal for Research, 5(5).
BOPPINITI, S. T. (2018). Human-Centric Design for IoT-Enabled Urban Health Solutions: Beyond Data Collection. International Transactions in Artificial Intelligence, 2(2).
BOPPINITI, S. T. (2018). Unraveling the Complexities of Healthcare Data Governance: Strategies, Challenges, and Future Directions. Transactions on Latest Trends in IoT, 1(1), 73-89.
BOPPINITI, S. T. (2017). Privacy-Preserving Techniques for IoT-Enabled Urban Health Monitoring: A Comparative Analysis. International Transactions in Artificial Intelligence, 1(1).
BOPPINITI, S. T. (2016). Core Standards and Applications of Big Data Analytics. International Journal of Sustainable Development in computer Science Engineering, 2(2).
BOPPINITI, S. T. (2015). Revolutionizing Industries with Machine Learning: A Global Insight. International Journal of Sustainable Development in computer Science Engineering, 1(1).
BOPPINITI, S. T. (2014). Emerging Paradigms in Robotics: Fundamentals and Future Applications. Transactions on Latest Trends in Health Sector, 6(6).
Boppiniti, S. T. (2023). AI-Powered Disease Outbreak Prediction Using Environmental and Social Data. International Transactions in Machine Learning, 5(5).
Boppiniti, S. T. (2021). AI-Based Cybersecurity for Threat Detection in Real-Time Networks. International Journal of Machine Learning for Sustainable Development, 3(2).
BOPPINITI, S. T. (2019). Revolutionizing Healthcare Data Management: A Novel Master Data Architecture for the Digital Era. Transactions on Latest Trends in IoT, 2(2).
Boppiniti, S. T. (2017). Revolutionizing Diagnostics: The Role of AI in Early Disease Detection. International Numeric Journal of Machine Learning and Robots, 1(1).
Boppiniti, S. T. (2018). AI-Powered Predictive Analytics for Personalized Healthcare. International Numeric Journal of Machine Learning and Robots, 2(2).
Boppiniti, S. T. (2018). AI-Driven Drug Discovery: Accelerating the Path to New Therapeutics. International Machine learning journal and Computer Engineering, 1(1).
Boppiniti, S. T. (2019). Natural Language Processing in Healthcare: Enhancing Clinical Decision Support Systems. International Numeric Journal of Machine Learning and Robots, 3(3).
Raghunath, V., Kunkulagunta, M., & Nadella, G. S. (2020). Optimizing SAP Data Processing with Machine Learning Algorithms in Cloud Environments. International Transactions in Artificial Intelligence, 4(4).
Raghunath, V., Kunkulagunta, M., & Nadella, G. S. (2020). Artificial Intelligence in Business Analytics: Cloud-Based Strategies for Data Processing and Integration. International Journal of Sustainable Development in Computing Science, 2(4).
Raghunath, V., Kunkulagunta, M., & Nadella, G. S. (2020). Scalable Data Processing Pipelines: The Role of AI and Cloud Computing. International Scientific Journal for Research, 2(2).
Raghunath, V., Kunkulagunta, M., & Nadella, G. S. (2021). Leveraging Cloud Computing for Efficient Data Processing in SAP Enterprise Solutions. International Journal of Machine Learning for Sustainable Development, 3(4).
Raghunath, V., Kunkulagunta, M., & Nadella, G. S. (2021). Machine Learning in SAP Workflows: A Study of Predictive Analytics and Automation. Transactions on Latest Trends in Artificial Intelligence, 2(2).
Raghunath, V., Kunkulagunta, M., & Nadella, G. S. (2021). Machine Learning Models for Optimizing SAP-Based Data Processing in Cloud Environments. International Journal of Sustainable Development in Computing Science, 3(3).
Published
Issue
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
