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dc.contributor.authorAhmed, MD Sajib
dc.contributor.authorAhmed, Khawza Iftekhar Uddin
dc.contributor.authorIslam, Mohammad Tohidul
dc.contributor.authorSarwar, Miya and Hasan
dc.date.accessioned2016-10-04T10:02:30Z
dc.date.available2016-10-04T10:02:30Z
dc.date.issued2016-09-01
dc.identifier.isbn978-984-34-0780-1
dc.identifier.urihttps://ar.iub.edu.bd/handle/11348/256
dc.description.abstractUnited International University (UIU) has been offering graduate degrees for more than 10 years. During this time period, we are regularly coming up with students who are suffering miserably in their academic career. In academic context, these students fall into the state of probation. A probationary state is when a student’s CGPA falls below 2.00. Every new recruit is generating a larger batch of probationary students. Observation indicates that students suffer not only due to factors relating to teachers’ quality and teaching practices; a lot of other issues like social surroundings, previous academic efforts, his/her real intention and other factors affect his/her performance. In this study, we would analyze some parameters of a group of students based on their historical data. Data were collected from their current and previous academic performances and survey questionnaires related to their habits and social involvements. Some data on teaching practices and delivery quality would be considered here. The analysis on data would help us to develop a model for prediction of students’ future academic result. This prediction will help students to design their academic career more carefully and help develop a better sustainable nation.en_US
dc.language.isoen_USen_US
dc.publisherCenter for Pedagogy (CP) Established under the Sub-project Titled “Pedagogical Development at Undergraduate and Master’s Level” (CP3357), Independent Univeristy, Bangladesh (IUB)en_US
dc.subjectData analyticsen_US
dc.subjectData miningen_US
dc.subjectDecision treeen_US
dc.subjectRegression methoden_US
dc.titleData Analytics to Improve Students’ Academic Performanceen_US
dc.typeArticleen_US


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