Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

Predictions Algorithms in Educational Systems based on Student Performance


Affiliations
1 MCA Department, P.E.S's Modern College of Engineering, Pune, India
     

   Subscribe/Renew Journal


Now a student’s performance towards education is influenced through various factor. Proper motivation and guidance towards Students should increase. Factor and proper assessment abilities support for better performance. Thus the different techniques of data mining is used for increase the performances of the candidates. Identifying the performance of candidates most important research area .studies of educational data mining based on distinguish mining algorithms connected with different predictions techniques. Thus learners performance is suffered by distinguish parameters for example considers a learning environment, financial issues etc. the paper study based on environmental factors and institute factors for evaluating student performance.

Keywords

Data Mining, Educational Data Mining, Classification.
User
Subscription Login to verify subscription
Notifications
Font Size

  • A. Dinesh Kumar, V. Radhika .(2016) Mining Educational Data to Predicting Higher Secondary Students Performance”, International Journal of Computational Intelligence and Informatics, Vol. 6: No. 2.
  • Azwa Abdul, Nur Hafieza, FadhilahAhmad .(2013) “ Mining Students’Academic Performance”, Journal of Theoretical and Applied Information Technology”, Vol 53.
  • Birijesh Kumar, Saurabh Pal.(2011)“Mining Educational Data toAnalyze Students’ Performance”, International Journal ofAdvanced Computer Science and Applications Vol 2.
  • Birijesh Kumar Bharadwaj, Saurabh Pal.(2011)” Data Mining: APrediction for performance improvement using classification”,International Journal of Computer Science and InformationSecurity, Vol 9.
  • Bevinda Alisha Pereira, Anusha Pai.(2017)” A Comparative Analysis of Decision Tree Algorithms for Predicting Student’s Performance”, International Journal of Engineering Science and Computing, Vol 7.
  • Mukesh Kumar Prof. A.J. Singh.(2017) “Evaluation of Data Mining Techniques for Predicting Student’s Performance”, Modern Education and Computer Science,vol 8, 25-31.
  • Padma Mishra , Dr. Vaishali B. Sangvikar(2018) “ Educational Data Mining and Learning Analytics in Higher Education”,MQRI Journal of Management and IT Vol. 12, No. 1.
  • Patinon Galvan (2016) ” Educational Evaluation and Prediction of School Performance through Data Mining and Genetic Algorithms”, Future Technologies conference IEEE.
  • Raheela Asif, Saman Hina and Saba (2017) “Predicting Student Academic Performance using Data Mining Method’s”, International Journal of Computer Science and Network Security (IJCSNS), VOL.17.
  • S.Anupama Kumar, Dr. Vijayalskhmi (2011) “Efficiency of DecisionTress in Predicting Student’s Academic Performance”, CCSEA.
  • SajadinSembiring and Zarlis(2011),”Prediction of student performance by an application of data mining techniques”, International Confrence on Management and Artificial Intelligence IPEDR vol.6 2011

Abstract Views: 604

PDF Views: 5




  • Predictions Algorithms in Educational Systems based on Student Performance

Abstract Views: 604  |  PDF Views: 5

Authors

Padma Mishra
MCA Department, P.E.S's Modern College of Engineering, Pune, India
Vaishali B. Sangvikar
MCA Department, P.E.S's Modern College of Engineering, Pune, India

Abstract


Now a student’s performance towards education is influenced through various factor. Proper motivation and guidance towards Students should increase. Factor and proper assessment abilities support for better performance. Thus the different techniques of data mining is used for increase the performances of the candidates. Identifying the performance of candidates most important research area .studies of educational data mining based on distinguish mining algorithms connected with different predictions techniques. Thus learners performance is suffered by distinguish parameters for example considers a learning environment, financial issues etc. the paper study based on environmental factors and institute factors for evaluating student performance.

Keywords


Data Mining, Educational Data Mining, Classification.

References





DOI: https://doi.org/10.25089/%2FMERI%2F2018%2Fv12%2Fi2%2F182837