Generic CO-PO Attainment Calculation Using Python and Microsoft Excel: A Comprehensive Framework for Automated Outcome Assessment

Abstract

Outcome-Based‍‌‍‍‌‍‌‍‍‌ Education (OBE) is a common global benchmark for assessing student learning, especially in the case of engineering programs which have been accredited by NBA and ABET or alike. Measuring Course Outcomes (COs) and Program Outcomes (POs) is the main focus of such a framework, however, the majority of institutions are still using diversified spreadsheets and manual calculations which take too much time, are not consistent and are loaded with errors.

This study is about an adaptable, fully automated CO-PO attainment system which was developed by Python technologies like Flask, Pandas, NumPy and OpenPyXL and structured Excel templates were used for integration. The system covers the entire workflow—data ingestion, validation, weighted direct and indirect attainment computation, and PO/PSO aggregation in a streamlined manner, also enabling institutions to configure thresholds and weightages if they wish.

Through an easy cloud-based interface, the faculty can upload the standardized Excel files and instantly get the reports in a professional layout with the help of visualizations. Real academic datasets were used for the testing and the results showed that the processes which were going for two to three hours have now been completed in less than thirty seconds with no manual errors.

The proposed framework is a step forward in the direction of standardization, transparency, scalability, and audit readiness which, in turn, make it a convenient instrument for the implementation of the continuous quality improvement process in engineering ‍‌‍‍‌‍‌‍‍‌education.