The Covid-19 pandemic has resulted in the worst downturn in the global economy since the Great Depression, in the 1930s. To face the challenges of the global economy a person needs to possess basic skills, including education skills. Education plays a vital role in building a competitive economy that will hardly be affected by crisis and will be able to ensure that there are high rates of social development. The student population has become very diverse over the decades making it difficult to teach. Teaching has become very complex to handle because of the increase in a variety of teaching strategies and the diverse student population. This has led to the need for more research to be conducted on how the diverse student population can be accommodated with teaching and learning. Furthermore, the most expensive education is the one that is not completed. There is a need to pay attention to the low completion rates and the importance of examining academic and institutional practices. One of the effective ways that has been used for over a decade to account for student learning and overall performance has been associated with test scores. This has been effective in forming general programme improvement. However, the use of the test scores alone informs a narrow agenda and is insufficient in developing a responsive pedagogy. There is an importance in using data to improve schools. Data can be used to improve the quality of education. One of the ways to use data is through the implementation of data-driven teaching. This study will therefore explore data-driven instruction in detail. It will be a conceptual paper that will explore how data-driven instruction can be used as a means to improve higher education during the fourth industrial revolution era. Data-driven instruction is explored as it is a growing trend used to improve the quality of education. Data-driven instruction can be defined as using student data to enhance instructional practices in the classroom to address the needs and learning styles of individual students. Additionally, data-driven instruction will be explored to discover how it can be used as a systematic and purposeful work to maximise the students’ performance. Furthermore, the study will provide recommendations on how data-driven instruction can be used to give direction to decisions to improve the students’ outcomes.

Author: Ayanda Pamella Deliwe

Published in: London International Conference on Education (LICE-2023)

• Date of Conference: 13-15 November 2023
• DOI: 10.20533/LICE.2023.0022
• ISBN: 978-1-913572-66-2
• Conference Location: St Anne’s College, University of Oxford, Oxford, UK