چکیده:
The present research was conducted with the aim of providing a conceptual framework for the use of big data in higher education. The type of research is applied and has utilized a descriptive-analytical method. The examination of big data concepts began in 2001, when this concept first gained attention in the field of commerce in many countries, and after that, since 2011, it has specifically entered the field of higher education. The research findings show that given the volume of data produced by each of the higher education actors in three sectors—institutional activities, academic programs, and teaching—the need to understand the connection between data is felt more than ever for planning and policymaking. Among the most important of these findings are the production and recording of unstructured data in higher education, the lack of an integrated structure for managing structured data with structural diversity, the importance of the social dimension versus its technical dimension, and the remarkable application of big data in internet education. Finally, in this study, considering the structure and management of the higher education system in Iran, a model at three levels—university, province, and region—is proposed for integrating data produced in the sectors of education, research, curriculum, instructors, educational content, and educational data.
خلاصه ماشینی:
The emergence and expansion of big data as a knowledge system has been able to influence higher education, just like other fields; because from this perspective, big data is changing the goals of knowledge, social theories, and also transforming decision-making theories (Boyd & Crawford 2, 2012).
Prior to this, research in the field of learning analytics was limited only to testing individual indicators of students and their classroom performance, but with the emergence of the big data concept, new opportunities and challenges arose in higher education.
In the realm of higher education, big data implicitly refers to a wide range of administrative and operational data collection processes aimed at evaluating the performance and progress of educational institutions to predict future situations and identify existing potentials in the areas of university planning, research, teaching, and learning.
Thus, big data, by increasing the understanding of students' lived experiences at the university and improving academic planning, guides the management and decision-making system in higher education toward an evidence-based decision-making system that can be responsive to the course of global transformations.
Based on what was said regarding higher education actors and the analysis of data obtained in various sectors, big data can provide the necessary tools for prediction to higher education institutions so that, with its help, simultaneously with the improvement of 1 learning processes, they can also ensure the quality of academic programs (Drigas & Leliopoulos, 2014).
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