EconPapers    
Economics at your fingertips  
 

Automated VTU Result Analytics and NBA Reporting Framework Using Academic Performance Evaluation

Pramod Kumar R, Sunil Kumar R M and Basavaraj S Pol

International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2026, vol. 12, issue 4, 214-226

Abstract: Academic institutions affiliated with Visvesvaraya Technological University (VTU) undertake extensive result analysis following the publication of semester examination results. The conventional approach relies heavily on manual processing using spreadsheet and word-processing tools, requiring faculty members to compute subject-wise pass percentages, gender-wise performance, National Service Scheme (NSS) and Physical Education (PE) student outcomes, faculty-wise statistics, and Outcome-Based Education (OBE) attainment metrics. This process is time-consuming, error-prone, and poorly suited to large-scale academic analytics and National Board of Accreditation (NBA) reporting requirements [1], [2], [11]. This paper proposes an Automated VTU Result Analytics and NBA Reporting Framework (AVRANRF) that automates result ingestion, student classification, performance evaluation, and multi-format report generation. The framework imports VTU examination datasets, performs multidimensional academic analysis across gender, NSS, PE, subject, and faculty dimensions, computes quantitative performance indicators, and produces NBA-compatible reports together with visual dashboards. A preliminary evaluation conducted at a VTU-affiliated engineering institution indicates substantial reductions in report-preparation time and improvements in calculation accuracy and report consistency relative to the existing manual workflow. The proposed framework offers a practical, extensible solution for higher-education institutions seeking data-driven academic performance evaluation and accreditation support, while highlighting directions for further validation across larger and more diverse institutional datasets.

Keywords: Educational Data Mining; Academic Performance Evaluation; NBA Accreditation; Outcome-Based Education; Learning Analytics; Automated Report Generation; VTU Result Analytics (search for similar items in EconPapers)
Date: 2026
Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT261242022
References: Add references at CitEc
Citations:

Downloads: (external link)
https://ijsrcseit.com/home/article/view/CSEIT261242022 Article URL (text/html)
https://ijsrcseit.com/home/article/download/CSEIT261242022/CSEIT261242022 Full text (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:jbh:ijsrcs:v12:y2026:i4:id:2127

DOI: 10.32628/CSEIT261242022

Access Statistics for this article

More articles in International Journal of Scientific Research in Computer Science, Engineering and Information Technology from International Journal of Scientific Research in Computer Science, Engineering and Information Technology
Bibliographic data for series maintained by Pankaj Sharma (USA) ().

 
Page updated 2026-09-18
Handle: RePEc:jbh:ijsrcs:v12:y2026:i4:id:2127