Reflection on QIP: Empowering with Data Tools for Effective Teaching and Course Planning

The six-day Quality Improvement Programme (QIP) titled "Empowering with Data Tools for Effective Teaching and Course Planning," held from 16th to 21st June 2025, was an enriching and transformative experience for the faculty members of the School of Business and Management. This initiative, aimed at equipping faculty with practical data tools, was a much-needed response to the growing demands of data-driven decision-making in education.

The first three days focused on Advanced Excel and SPSS, offering a deep dive into spreadsheet-based analytics and statistical techniques for academic purposes. The sessions on Advanced Excel enhanced our ability to work with large datasets, apply complex formulas, use pivot tables, perform what-if analyses, and visualize data effectively. This learning is especially beneficial in classroom instruction, assessment planning, and curriculum reviews, where efficiency and clarity in data handling are critical.

The SPSS training was instrumental in building competence in handling empirical data, conducting statistical tests, and interpreting outputs in a pedagogically sound manner. For faculty involved in research supervision or curriculum development, the ability to apply techniques like descriptive statistics, correlation, regression, and hypothesis testing using SPSS adds immense value. Moreover, these tools support a more evidence-based approach to curriculum planning, allowing us to analyse student performance trends, feedback patterns, and course effectiveness with precision.

The latter half of the QIP, covering Power BI, introduced us to the world of business intelligence and interactive dashboards. Learning how to transform raw data into meaningful visual insights through Power BI was particularly relevant for faculty teaching business analytics, operations, and marketing courses. The training covered essentials such as data modelling, DAX functions, and creating dynamic reports, enabling us to design dashboards that can support both classroom instruction and institutional reporting.

What stood out throughout the QIP was the application-oriented approach taken by the facilitators. Each session was hands-on, with real-time datasets and guided exercises that mirrored actual classroom or academic management scenarios. The structure encouraged active participation, collaborative learning, and peer-to-peer discussion. It also provided opportunities to reflect on our teaching methodologies and identify how data tools can help bridge gaps in planning, delivery, and evaluation.

This QIP also reinforced the importance of continuous faculty development in the digital age. With institutions increasingly adopting Learning Management Systems (LMS), Outcome-Based Education (OBE), and AI-powered analytics, it is crucial for educators to stay ahead with relevant technological skills. Integrating these tools into our daily academic tasks can significantly improve transparency, efficiency, and learner engagement.

In conclusion, the QIP served as a valuable capacity-building exercise that not only upgraded our technical skills but also broadened our perspective on data-informed teaching. We are now better prepared to design curricula, assess student outcomes, and make informed academic decisions using modern data tools. Going forward, the insights gained will enhance both the academic quality and the strategic planning processes within the School of Business and Management.