Journal of Data Acquisition and Processing Vol. 38 (3) 2023 2709 ISSN: 1004-9037 https://sjcjycl.cn/ DOI: 10.5281/zenodo.98549638 EXPLORING THE USE OF EDUCATIONAL DATA MINING AND LEARNING ANALYTICS TO IMPROVE INSTRUCTIONAL PRACTICES AND STUDENT PERFORMANCE Nidhi Agarwal Professor, Faculty of Social Science and Humanities, Lincoln University, Malaysia Yogendra Babu Assistant Professor, Department of Education, Mahatma Gandhi Antarrashtriya Hindi Vishwavidyalaya, Wardha, M.H., India Ram Awadh Assistant Professor, Department of Education, Mahatma Gandhi Antarrashtriya Hindi Vishwavidyalaya, Wardha, M.H., India Vikas Mishra Assistant Professor, Department of Education, Akbarpur Degree College, Akbarpur, Kanpur Dehat, U.P., India Corresponding Author: Dr Nidhi Agarwal, dr.nidhi@lincoln.edu.my, 0000-0002-1590-9888 ABSTRACT Learning analytics (LA) and educational data mining (EDM) are two new fields that use the power of data analysis to better educational practises and student performance. These approaches give teachers access to information about the behaviour, learning patterns, and performance of their students by analysing big datasets gathered from diverse educational resources. Personalising learning experiences, offering early interventions and assistance, informing curriculum and instructional design, utilising predictive analytics for preventative measures, improving assessment and feedback systems, and guiding institutional decision- making are all possible uses for this information. To achieve proper and efficient implementation, ethical issues like prejudice, consent, and data protection must be properly considered. Overall, educational data mining and learning analytics have enormous potential to alter education and give teachers the tools they need to optimise teaching learning Process. Keywords: Learning Analytics, Educational Data Mining, Performance, Instructional Practices. INTRODUCTION In order to improve educational results, learning analytics refers to the gathering, examination, and interpretation of data produced throughout the learning process. To collect and analyse student data, including their interactions with learning management systems, online platforms,