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LEVERAGING THE DATA MINING TOOLS AND TECHNIQUES IN ENHANCING THE EFFECTIVENESS OF EDUCATION TECHNOLOGY PLATFORMS AND SMART LEARNING SYSTEMS

Vineet Sehrawat

99-104

Vol. 3, Jan-Jun, 2016

Date of Submission: 2016-03-12 Date of Acceptance: 2016-04-24 Date of Publication: 2016-05-09

Abstract

Educational Data Mining (EDM) is a stage for education and investigating information to get fundamental data and prompt the exceptional example which will help study, test and ability student execution in scholastics. Can apply bright information mining styles to muck the information from the information storage facility to use information mining ways that assist understudies with taking more time for better outgrowth. The model utilized in instructive information mining should be developmental and graphic applied to the information storage facility and should accumulate authentically exact information to upgrade the review's exhibition. Retrogression investigation can likewise foster a model as a review apparatus; it can use with reliant or free factors. Assuming the model is ideal enough for use as a review apparatus, each bunch of information should utilize that model to cost the orderly information. Sometimes instructive information mining is considered the public exhibition of researchers. However, every student has their place of getting the substance, with the goal that the framework should likewise be adaptable enough for everybody; for satisfying this request school system can be intricate, yet whenever it's built additionally, it'll help everybody. This paper describes surprising information mining ways and their appropriate purposes.

References

  1. Sara Fatima, Salma Mahgoub, “Predicting Student's Performance in Education using Data Mining Techniques”, International Journal of Computer Applications (0975 – 8887), Volume 177 – No. 19, November 2019
  2. Sushil Shrestha, Manish Pokharel, “Educational data mining in moodle data”, International Journal of Informatics and Communication Technology (IJ-ICT), Vol.10, No.1, April 2021, ISSN: 2252-8776
  3. Ahmed Saied Rahama Abdallah, 'Using Regression Analysis to Identify the Predictive Ability of the Achievement Test and the Secondary School Rate in the Prediction of the Cumulative Rate ”, International Journal of Computer Applications (0975 – 8887), Volume 177 – No. 17, November 2019
  4. Nouf S. Aldahwan, Nourah I. Alsaeed, “Use of Artificial Intelligent in Learning Management System (LMS): A Systematic Literature Review”, International Journal of Computer Applications (0975 – 8887), Volume 175– No. 13, August 2020
  5. Krishna Parmar, Huma Khan, “A Survey on Analysis the Students Mind in Different Area”, International Journal of Science and Research (IJSR), ISSN: 2319- 7064, Impact Factor (2017): 7.296
  6. Nilesh V. Ingale, Dr. M. Sivakkumar, Dr. Varsha Namdeo, “Survey on Prediction System for Student Academic Performance using Educational Data Mining”, Turkish Journal of Computer and Mathematics Education Vol.12 No.13 (2021), 363-369.
  7. Suleiman Khalifa Arafa Ibrahim, Mahmoud Ali Ahmed, 'Prediction of Students’ Cumulative Grade Point Averages (CGPAs) at Graduation: A Case Study” International Journal of Computer Applications (0975 – 8887), Volume 174 – No. 24, March 202
  8. Nancy Kansal, Vineet Kansal, “An Efficient Data Mining Approach to Improve Students’ Employability Prediction”, International Journal of Computer Applications (0975 – 8887), Volume 178 – No. 47, September 2019.
  9. Sathyendranath Malli, Nagesh H. R.,B. Dinesh Rao, “Approximation to the K-Means Clustering Algorithm using PCA”, International Journal of Computer Applications (0975 – 8887), Volume 175– No. 11, August 2020
  10. Anirudhd Soni, Anansha Gupta, 'Feature Selection for Performance Prediction using Decision Tree”, International Journal of Computer Applications (0975 –8887), Volume 183 – No. 17, July 2021.
  11. Fatima Alshareef, Hosam Alhakami, Tahani Alsubait, Abdullah Baz, 'Educational Data Mining Applications and Techniques”, (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 11, No. 4, 2020.
  12. Hemlata Pate, Dr. Dhanraj Verma, 'Performance Analysis of Feature Selection Techniques for Text Classification”, International Research Journal on Advanced Science Hub (IRJASH), Volume 02 Issue 12S December 2020.
  13. Laura O. Moraes and Carlos Eduardo Pedreira, 'Clustering Introductory Computer Science Exercises Using Topic Modelling Methods”, Accepted Article. Published In IEEE Transactions On Learning Technologies ( 2021 IEEE.
  14. Chaman Verma, Zoltán Illés, Veronika Stoffová, Pradeep Kumar Singh, 'Predicting Attitude of Indian student’s towards ICT and Mobile Technology for Real-Time: Preliminary Results”, DOI 10.1109/ACCESS.2020.3026934, IEEE
  15. Miguel A. Prada, Manuel Domínguez, 'Educational data mining for tutoring support in higher education: A web-based tool case study in engineering degrees”, DOI 10.1109/ACCESS.2020.3040858, IEEE.
  16. Smita Ghorpade, Seema Patil, 'Educational Data Mining: Tools And Techniques Study”, 2020 IJRAR November 2020, Volume 7, Issue 4 E-ISSN 2348-1269, P- ISSN 2349-5138.
  17. Yijun Zhao, Qiangwen Xu, 'Proceedings of The 13th International Conference on Educational Data Mining (EDM 2020)”.
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