Predictive Analytics for Personalized Education Pathways
Mahadasu Harshitha
2200030411@kluniversity.in
Computer Science and Engineering
Koneru Lakshmaiah Educational Foundation
Mamillapalli Ramkumar
2200031664@kluniversity.in
Computer Science and Engineering
Koneru Lakshmaiah Educational Foundation
Balina Divya Sri
2200030608@kluniversity.in
Computer Science and Engineering
Koneru Lakshmaiah Educational Foundation
Dr. B. Prameela Rani
Assistant Professor
Computer Science and Engineering
Koneru Lakshmaiah Educational Foundation
Myla Lakshmi Narayana
2200030058@kluniversity.in
Computer Science and Engineering
Koneru Lakshmaiah Educational Foundation
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Abstract - This study explores the application of predictive analytics and machine learning in enhancing educational outcomes through personalized learning pathways. The project developed a predictive system designed to analyze students’ academic performance, behavioral trends, and learning preferences to recommend individualized educational routes. A structured development lifecycle was followed, including data collection, preprocessing, model training, evaluation, and system deployment. Machine learning models such as regression and classification algorithms were utilized within a user-centric interface to generate actionable insights for both students and educators. Emphasis was placed on model interpretability, ethical data usage, and system usability. The resulting prototype demonstrated how data-driven methodologies can enable informed academic planning, improved engagement, and proactive student support, affirming the transformative potential of predictive analytics in modern education.
Key Words: predictive analytics, machine learning, education, personalization, data science, student performance.
