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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Issue: May 2026
Volume 11 | Issue 5
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 120
Article Submitted : 24204
Article Published : 9239
Total Authors : 24597
Total Reviewer : 847
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| Paper Title: | Scholar Lens: An XGBoost-Based Early Risk Detection System Using Student Learning Data |
| Authors Name: | Anyesha Biswas , Parvathy V Nair |
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IJRTI_207368
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| Published Paper Id: | IJRTI2604246 |
| Published In: | Volume 11 Issue 4, April-2026 |
| DOI: | |
| Abstract: | Early identification of at-risk students is a critical challenge in modern education systems, where traditional evalu ation methods often fail to capture the complexity of individual learning behaviors. This paper presents Scholar Lens, a machine learning-based early intervention model designed to analyze diverse student data and accurately predict academic risk. The system integrates demographic, behavioral, and educational fea tures—including attendance, extracurricular activities, and self study hours—to generate comprehensive student profiles. Using the XGBoost algorithm optimized via Bayesian tuning, the model achieves high predictive performance with interpretable results using SHAP (SHapley Additive exPlanations) values for feature importance analysis. The dataset comprises multiple attributes across various subjects and student habits, enabling a granular risk assessment. Results show the model’s effectiveness in iden tifying students at potential risk, providing actionable insights for educators and policymakers. Scholar Lens aims to enhance decision-making in academic counseling by enabling timely, data driven interventions, ultimately contributing to improved student outcomes and institutional support strategies. |
| Keywords: | Educational data mining, XGBoost, student performance prediction, early intervention, academic risk as sessment, SHAP values, machine learning in education, student behavior analysis, predictive modeling, learning analytics |
| Cite Article: | "Scholar Lens: An XGBoost-Based Early Risk Detection System Using Student Learning Data", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 4, page no.b784-b790, April-2026, Available :http://www.ijrti.org/papers/IJRTI2604246.pdf |
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2604246
Registration ID:207368
Published In: Volume 11 Issue 4, April-2026
DOI (Digital Object Identifier):
Page No: b784-b790 Country: Chennai, Tamil Nadu, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2604246 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2604246 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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