| Project Details | |
| Project Code | DWA171 |
| Title | Evaluating Student’s Performance Using K-Means Clustering - .Net Project |
| Project Type | ASP.Net Web Application |
| Front End | Microsoft Visual Studio 2010 |
| Back End | Microsoft SQL Server 2008 |
| Project Cost | |
About the Project
Evaluating Student’s Performance Using K-Means Clustering - .Net Project
ABSTRACT
In India ranking of students is mainly done on basis of marks obtained in exams. Most of the Indian universities follow the common pattern of grouping the students in the category of pass with distinction for students scoring 75% and above, first division for students scoring from 60% to 74.9%, second division for students scoring from 50% to 59.9%, third division having the range from 40% to 49.9%.Many Universities set a minimum set of marks that should be maintained in order to continue in the degree program. In some University, the minimum requirement set for the students is 40% while in other cases it may be 33%. Therefore, marks obtained in examination is still remains the most common factor used by the academic planners to evaluate progression in an academic environment. With traditional approach of grouping students based on their average scores, it is difficult to obtain a comprehensive view of the state of the students’ performance and simultaneously discover important details from their time to time performance
In this paper, a simple methodology based on k-means clustering algorithm and deterministic model is being used to evaluate the performance of students in higher institutions. This methodology will assist the academic planners to monitor student’s performance during each semester. Hence this model will play important role for academic planners to determine the reasons for decline in performance of students during particular semester and steps that need to be taken to improve performance from next academic session
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