Big Data-Driven Algorithm for Teaching Quality Assessment in Universities: Research and Practice

As higher education continues to evolve, assessing the quality of teaching and learning has become crucial not only for educational quality, but also for improving instruction. It is part of a gradual process of making higher education cater to the masses rather than to the elite few, an obvious natural evolution of higher education. In the elitist phase, universities were per se “good” or “excellent” based on their uncommon, elite status, meaning that they did not need to demonstrate their value through competition with, or measurement against, other institutions. However, higher education is increasingly becoming inclusive, reflecting the diversity in both academic and demographic aspects of the student body, and its significance in social and economic development. Universities are now under pressure to demonstrate their efforts and outcomes across multiple dimensions. This study presents a novel big data-based algorithm for evaluating teaching and learning quality in higher education. It is a holistic, multi-faceted approach that measures the quality of teaching by synthesizing different types of raw data followed by data cleaning and pre-processing, evaluation protocol development, and algorithm modeling. This approach provides some flexibility in interpretation and practice metrics. The Government intends to promote educational innovation, allowing institutions to preserve autonomy by selecting pedagogical methods that would have to be implemented to serve students’ needs best. Based on experimental and practical applications, the proposed evaluation model has several superiorities in accuracy and real-time performance. It gives an overall image of teaching performance and student learning outcomes. The deployment of this system in a university demonstrates the feasibility and real-life application of this approach. This research provides new perspectives and tools for measuring good teaching in higher education, as well as the promise and potential of big data in education.