A review of structural study and analysis of classification, clustering algorithms for proposed model to assess performance of students.

The performance assessment of students is the most important work as this is directly related to the future of the students. This research paper focuses on structural study, analysis and identification of non academic characteristics and data mining techniques, specifically classification and clustering. These are required for designing a model which collectively gives performance assessment in the form of academic and non-academic characteristics. These characteristics need to be classified separately on the basis of different subcategories in each type of characteristics and data collected from the questionnaire from the stakeholders of this model students, teachers and parents. Identifying and using classification and clustering algorithms suitable to the structure of this assessment leads to required output of the research. [ABSTRACT FROM AUTHOR]