Analysis of Educational Data Mining Techniques

2018

Educational systems need innovative ways to improve quality of education to achieve the best results and decrease the failure rate. Educational Data Mining (EDM) has boomed in the educational systems recently as it enables to analyze and predict student performance so that measures can be taken in advance. Due to lack of prediction accuracy, improper attribute analysis, and insufficient datasets, the educational systems are facing difficulties and challenges exist to effectively benefit from EDM. In order to improve the prediction process, a thorough study of literature and selection of the best prediction technique is very important. The main objective of this paper is to present a comparative study of various recently used data mining techniques, classification algorithms, their impact on datasets as well as the prediction attribute’s result in a clear and concise way. The paper also identifies the best attributes that will help in predicting the student performance in an efficie...

2018

The Electronic (E)-Learning attracts the attention of researchers in the recent years. This for different reasons, such as easing the board studying and guarantee the education for busy people. Different methods and algorithm have been adopted in e-learning systems to offer more flexible services for students. In addition, the recent smart systems consider the prediction strategies for expecting the logical results of different categories in e-learning. The researcher goes further with decision making for students, presented as a recommendation for each type of classification. Moreover, the e-learning systems use the classification and clustering methods for classifying the investigated dataset. In this paper, a comprehensive study of the recent e-learning decision making and prediction is presented. It offers a wide information regarding the subject of decision making and prediction in e-learning that can improve them efficiently. Discussion and recommendations have been included in this paper.

UHD Journal of Science and Technology, 2019

In this period of computerization, schooling has additionally remodeled itself and is not restrained to old lecture technique. The everyday quest is on to discover better approaches to make it more successful and productive for students. These days, masses of data are gathered in educational databases, however it stays unutilized. To be able to get required advantages from such major information, effective tools are required. Data mining is a developing capable tool for examination and expectation. It is effectively applied in the field of fraud detection, marketing, promoting, forecast and loan assessment. However, it is in incipient stage in the area of education. In this paper, data mining techniques have been applied to construct a classification model to predict the performance of students.

International Journal of Computer Science and Information Technologies, 2014

Data mining is about explaining the past and predicting the future by means of data analysis. Educational Data Mining is a promising discipline which has an imperative impact on predicting students’ academic performance. Thousands of students take admissions in Universities and colleges every year, at the time of admissions they collect the students’ data. In the same way while the Teachers join in the institution they collect their personal and professional data. Understand the importance of data is essential from a business point of view. Data collected at the time of admission can be used for classifying and predicting students’ behavior and performance as well as teachers’ performance. Therefore, in this paper, we are examining the role of Data mining in an Educational Field. By using SDAR, we have identified possible grade values i.e., Excellent, Good, Average and Poor or Fail. We have used K-means clustering algorithm to find the best cluster center for attributes like attendance, Sessional marks and assignment marks etc. We have also discussed a Rule-Based Classification (RBC) method; it extracts a set of rules that shows relationships between attributes of the data set and the class label. In this paper we have also addressed the evaluation of Teachers’ performance by using data mining techniques at University and College level.

— Data Mining has wide applicability due to wide ease of use of large amount of data and requirement of storage as per the need. Data mining techniques are widely useful in educational data mining for analysis of student data. In educational area data mining different data mining techniques like classification, clustering, association rule mining, decision tree method have been used to analyze student's learning manners, their mindset, forecasting their result, group them, and for finding out different patterns. Educational data mining helps for improving student's performance, for managing the student database and for managing the institute. This paper focuses on differe nt data mining techniques that are useful for predicting student performance.

Int. J. Next Gener. Comput., 2020

Educational Data Mining (EDM) is a process in which data mining is applied on students’ data obtained from any educational institution. The importance of data mining is increasing in this field as it can help both in the improvement of education system and in the growth of students by making predictions. Many techniques are used for doing classification and predictions regarding different aspects of education. In this paper, the data mining techniques that are used in education have been discussed with their applications.

IJARCCE, 2017

Making use of Data mining (DM) in education is a rising interdisciplinary research field often referred as educational data mining (EDM). The principal objective of any educational institute is to provide excellent education to its students. One method to gain perfect level of quality in higher education is discovering knowledge that evaluates teachers' and students' performance and tries to predict areas of improvements and strengths. To satisfy this objective, EDM plays a vital role. The proposed work offers an effective approach for evaluation and prediction of teachers' and students' performance in institutions of learning using data mining technologies. The proposed system also acknowledges improvement areas of student as well as teachers' and is able to recommend respective training to them.

Technoarete Transactions on Application of Information and Communication Technology(ICT) in Education

This research study has aimed to analyze the importance of educational data mining on the performance and efficiency level of teachers and students. Presently, in the competitive world, several organizations are utilizing educational data mining to enhance the performance of the educational institute to stay competitive among the competitiveness in the universities. The implication of data mining has supported the students to enhance their efficiency level through enhancing their knowledge base. On the other hand, the implication of educational data mining has also supported the teachers to track the performance of the students. As a result, they support the teachers to provide effective training and development classes to the students who are facing difficulties in the understanding of a subject. However, in this research study, the researcher has utilized a secondary qualitative method of data collection to collect the data regarding the research topic. In addition, the secondary ...

Abstract: Educational Data Mining (EDM) is an rising ground search data in educational background by relating different Data Mining (DM) techniques/tools. It gives basic knowledge of teaching and learning method for useful education development. Educational data mining (also referred to as “EDM”) is clear as the area of scientific query centered around the growth of methods for making discoveries within the single kinds of data that come from educational background, and using those technique to better identify students and the background which they be trained in. This boost in rapidity and feasibility has had the advantage of making imitation much more possible. This paper addresses the purpose of data mining in educational society to pull out useful information from the vast data sets and providing logical tool to analysis and use this information for decision making processes by taking real life examples. Keywords: Educational Data Mining (EDM); Classification; Knowledge Discovery in Database (KDD); ID3 Algorithm. Higher education,, Data mining, Knowledge discover, Classification, Association rule, Prediction. Title: A Review on Role of Data Mining Techniques in Enhancing Educational Data to Analyze Student’s Performance Author: Dr N. Preethi, Deepak Goswami International Journal of Computer Science and Information Technology Research ISSN 2348-1196 (print), ISSN 2348-120X (online) Research Publish Journals

International Journal for Research in Applied Science and Engineering Technology IJRASET, 2020

The paper represents the data mining techniques used for predicting student's performance. In today's world the education field is growing, developing widely and becoming one of the most crucial industries. The data available in the educational field can be studied using educational data mining so that the unseen knowledge can be obtained from it. In this paper, various Data Mining approaches like Association mining and classification are used to predict the students' performance in examination in advance, so that necessary measures can be taken to improvise on their performance to score better marks. The results obtained after the implementation may be useful for instructor as well as students. This work will help in taking appropriate decision to improve student's performance.