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

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.