Abstract: Educational Data Mining is an emerging discipline, concerned with developing methods for exploring the unique types of data that come from educational settings, and using those methods to better understand students, and the settings which they learn in. EDM refers to the techniques, tools, and research designs utilized to obtain information from educational records, typically online logs, and examination results, and then analyses this information to formulate conclusions. The problem with educational data is it is a data rich and information poor collection. Data Mining is a process of finding potentially useful patterns from huge data sets. It is a multi-disciplinary skill that uses machine learning, statistics, and AI. Data mining process have the ability to discover the hidden knowledge present within the collection of educational data and then identify students’ performance with great accuracy. Also, it is playing a vital role in the process of diagnosis and prediction of problems in students’ education. This proposed paper presented a detailed systematic study of the role of various data mining techniques and algorithms in the field of educational data mining.
Keywords: Educational Data Mining, Data Mining algorithms, Student Performance, Naïve Bayes, Neural Network
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DOI:
10.17148/IJARCCE.2022.11580
