Analysis of Student Performance using Data Mining
We are thankful to Almighty Allah for his blessings for the successful completion of our thesis. Ourheartiestgratitude,profoundindebtednessanddeeprespectgotooursupervisor, Dr. Syed Akhter Hossain, Professor and Head of the Department, Department of Computer Science and Engineering, Daffodil Internat...
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| Format: | Thèse |
| Langue: | anglais |
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Department of Computer Science and Engineering, Military Institute of Science and Technology
2015
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| Accès en ligne: | http://hdl.handle.net/123456789/147 |
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| _version_ | 1868227005731831808 |
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| author | Yeasmin, Suraiya Jinnah, Rubayat Islam, Atoshi |
| author_browse | Islam, Atoshi Jinnah, Rubayat Yeasmin, Suraiya |
| author_facet | Yeasmin, Suraiya Jinnah, Rubayat Islam, Atoshi |
| author_sort | Yeasmin, Suraiya |
| collection | DSpace |
| description | We are thankful to Almighty Allah for his blessings for the successful completion of our thesis. Ourheartiestgratitude,profoundindebtednessanddeeprespectgotooursupervisor, Dr. Syed Akhter Hossain, Professor and Head of the Department, Department of Computer Science and Engineering, Daffodil International University(DIU), Dhaka, Bangladesh, for his constant supervision, affectionate guidance and great encouragement and motivation. His keen interest on the topic and valuable advices throughout the study was of great help in completing thesis.
We are especially grateful to the Department of Computer Science and Engineering (CSE) of Military Institute of Science and Technology (MIST) for providing their all out support during the thesis work.
Finally, we would like to thank our families and our course mates for their appreciable assistance, patience and suggestions during the course of our thesis. |
| format | Thesis |
| id | oai:localhost:123456789-147 |
| institution | My University |
| language | English |
| publishDate | 2015 |
| publishDateRange | 2015 |
| publishDateSort | 2015 |
| publisher | Department of Computer Science and Engineering, Military Institute of Science and Technology |
| publisherStr | Department of Computer Science and Engineering, Military Institute of Science and Technology |
| record_format | dspace |
| spelling | oai:localhost:123456789-1472015-08-04T08:22:29Z Analysis of Student Performance using Data Mining Yeasmin, Suraiya Jinnah, Rubayat Islam, Atoshi Performance, Data Mining, WEKA develop We are thankful to Almighty Allah for his blessings for the successful completion of our thesis. Ourheartiestgratitude,profoundindebtednessanddeeprespectgotooursupervisor, Dr. Syed Akhter Hossain, Professor and Head of the Department, Department of Computer Science and Engineering, Daffodil International University(DIU), Dhaka, Bangladesh, for his constant supervision, affectionate guidance and great encouragement and motivation. His keen interest on the topic and valuable advices throughout the study was of great help in completing thesis. We are especially grateful to the Department of Computer Science and Engineering (CSE) of Military Institute of Science and Technology (MIST) for providing their all out support during the thesis work. Finally, we would like to thank our families and our course mates for their appreciable assistance, patience and suggestions during the course of our thesis. The aim of this thesis paper is to analyze student performance using data mining. Data mining is the process of prediction, extracting data. Prediction regarding student performance can help a student to take decision. It can help not only the current students but also the future students, to take decision. In this way they can avoid poor performance which will help to enhance their performance. This is also a guideline to take decision. To understand student performance, a survey was conducted by Military InstituteofScience Technology(MIST)withthesupportfromtheCSEdepartmentand the peer learners of different classes. The data collected from survey was normalized, validatedandrevalidated. Afterthoroughinvestigationonthesurveydata,basedonstatisticalanalysistechniques,differntobservationswererecordedintheformofgraphical illlustrationinordertofindtherelations. Theexperimentalanalysisofthedatathrough result form the survey was satisfactory whicn led towards further study. In order to proceedfurtherthroughdataminingbasedontheunderstandingofthesurvey,datawas collected form the central databse of MIST where the main aim was to relate CGPA and student performance. We investigated different properties of the data; collected and developed a classification hypothesis in order to apply data mining algorithms. In this reasearch a machine learning tool called WEKA develop by the university of New Zealand was used for testing different algorithms on the data. It is to be noted successful appliaction of data minig algorithms in weka requires careful analysis of the source data and develops very specific classes using a very specialized format called ARFF (Attribute related file format) format, which defines attributes a targeted class based on data observations. The experimental results are validated against test data and intersting co-relations are observed. In the future further regorous study to match between demographic data and academic data will lead to much determining factors in order to predict the student performance. Department of Computer Science and Engineering, Military Institute of Science and Technology 2015-07-05T04:23:28Z 2015-07-05T04:23:28Z 2014-12 Thesis http://hdl.handle.net/123456789/147 en B.Sc. in Computer Science and Engineering Thesis; application/pdf Department of Computer Science and Engineering, Military Institute of Science and Technology |
| spellingShingle | Performance, Data Mining, WEKA develop Yeasmin, Suraiya Jinnah, Rubayat Islam, Atoshi Analysis of Student Performance using Data Mining |
| title | Analysis of Student Performance using Data Mining |
| title_full | Analysis of Student Performance using Data Mining |
| title_fullStr | Analysis of Student Performance using Data Mining |
| title_full_unstemmed | Analysis of Student Performance using Data Mining |
| title_short | Analysis of Student Performance using Data Mining |
| title_sort | analysis of student performance using data mining |
| topic | Performance, Data Mining, WEKA develop |
| url | http://hdl.handle.net/123456789/147 |
| work_keys_str_mv | AT yeasminsuraiya analysisofstudentperformanceusingdatamining AT jinnahrubayat analysisofstudentperformanceusingdatamining AT islamatoshi analysisofstudentperformanceusingdatamining |