scholarly journals Research Topics on Educational Data Mining in MOOCS

2020 ◽  
Vol 8 (7) ◽  
pp. 311-320
Author(s):  
Vanessa Faria de Souza ◽  
Tony Carlos Bignardi dos Santos
Keyword(s):  
Data Mining ◽  
Performance Analysis ◽  
Behavior Analysis ◽  
Educational Data Mining ◽  
Recommendation Systems ◽  
Research Topics ◽  
Systematic Mapping ◽  
Data Mining Techniques ◽  
Forum Analysis

Educational Data Mining Techniques have been widely used in MOOC environments to conduct different educational analyzes. In this context, a systematic mapping was conducted in five databases in order to verify which aspects of studies are inherent to the use of Educational Data Mining in MOOCs. The search comprised the period from 2015 to 2019, and 253 searches were found, out of this total, 133 studies were selected. The results revealed that studies on performance analysis, behavior analysis, forum analysis and implementation of recommendation systems are the most frequent themes.

scholarly journals Performance Analysis and Prediction Student Performance to build effective student Using Data Mining Techniques

2019 ◽  
Vol 3 (2) ◽  
pp. 10
Author(s):  
Ardalan Husin Awlla
Keyword(s):  
Data Mining ◽  
Performance Analysis ◽  
Student Performance ◽  
Fraud Detection ◽  
Classification Model ◽  
Data Mining Techniques ◽  
Incipient Stage ◽  
The Everyday ◽  
Using Data

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.

Nuclear fuel lattice performance analysis by data mining techniques

2015 ◽  
Vol 80 ◽  
pp. 236-247 ◽  
Author(s):  
Juan José Ortiz-Servin ◽  
José Manuel Cadenas ◽  
David A. Pelta ◽  
Alejandro Castillo ◽  
José-Luis Montes-Tadeo
Keyword(s):  
Data Mining ◽  
Performance Analysis ◽  
Nuclear Fuel ◽  
Data Mining Techniques

A Systematic Review About Prediction of Academic Behavior Through Data Mining Techniques

2020 ◽  
Vol 17 (11) ◽  
pp. 5162-5166
Author(s):  
Puninder Kaur ◽  
Amandeep Kaur ◽  
Rajwinder Kaur
Keyword(s):  
Systematic Review ◽  
Data Mining ◽  
Data Analysis ◽  
Educational Data Mining ◽  
Prediction Methods ◽  
Time Data ◽  
Academic Behavior ◽  
Data Mining Techniques ◽  
Real Time Data ◽  
Extract Information

In the IT world, predicting the academic performance of the huge student population poses a big challenge. Educational data mining techniques significantly contribute in providing solution to this problem. There are several prediction methods available for data classification and clustering, to extract information and provide accurate results. In this paper, different prediction methodologies are highlighted for the prediction of real-time data analysis of dynamic academic behavior of the students. The main focus is to provide brief knowledge about all data mining techniques and highlight dissimilarities among various methods in order to provide the best results for the students.

Mining Learners’ Behaviors: An Approach Based on Educational Data Mining Techniques

2020 ◽  
pp. 655-670 ◽  
Author(s):  
Ouafae El Aissaoui ◽  
Yasser El Alami El Madani ◽  
Lahcen Oughdir ◽  
Ahmed Dakkak ◽  
Youssouf El Allioui
Keyword(s):  
Data Mining ◽  
Educational Data Mining ◽  
Data Mining Techniques
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