Assessm ent of Performance of Students u sing Conditional Statistical Technique
Educational data mining (EDM) is gaining importance in every field. Due to the competency in every branch of engineering, the institutions are concentrating mainly on improving the performance of students. Efforts are also put towards knowing the reasons for low performance and identifying the facto...
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| Veröffentlicht in: | International journal of innovative technology and exploring engineering 2020-03, Vol.9 (5), p.1025-1031 |
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| Sprache: | eng |
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| container_end_page | 1031 |
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| container_issue | 5 |
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| container_title | International journal of innovative technology and exploring engineering |
| container_volume | 9 |
| creator | H, Dr. HemaMalini B. V., Dr. Suma L, Dr. Suresh M., Mr. Shankar M. |
| description | Educational data mining (EDM) is gaining importance in every field. Due to the competency in every branch of engineering, the institutions are concentrating mainly on improving the performance of students. Efforts are also put towards knowing the reasons for low performance and identifying the factors affecting the student’s performance. Researchers are working on preparing predictive models for improving student performance. The present study is considering the educational data of 1186 students. The data is classified as demographic and study related variables. An effort is made to predict the student performance, using a statistical technique – Chi Square test. The attributes affecting and not affecting the performance of students are assessed. The results are plotted using Pie Chart and histograms. The association between demographic and education variables with semester results is tabulated. |
| doi_str_mv | 10.35940/ijitee.C8389.039520 |
| format | Article |
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| title | Assessm ent of Performance of Students u sing Conditional Statistical Technique |
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