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A novel CALM algorithm in student profiling
Author(s) -
Jha Sunil Kr.,
Shorko Stefan
Publication year - 2018
Publication title -
computer applications in engineering education
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.478
H-Index - 29
eISSN - 1099-0542
pISSN - 1061-3773
DOI - 10.1002/cae.21926
Subject(s) - profiling (computer programming) , memorization , computer science , perception , artificial intelligence , associative property , personality , logical analysis , machine learning , mathematics education , psychology , social psychology , mathematics , mathematical statistics , statistics , neuroscience , pure mathematics , operating system
Computational intelligence plays a significant role in the improvement of the learning process. Student profile provides an overview of personality and establishes a connection between the abilities and learning preferences. The objective of the present study is to develop an algorithmic approach to student profiling in the selection of subjects and profession. A calculative associative logical memorable (CALM) algorithm is proposed which integrates calculative thinking, association, logical perception, and memorizing features. The developed CALM approach is also validated by including the environmental and social constraints. The validation outcomes claim that the CALM is able to design a noble student profiling framework which leads to further improvement in the quality of the learning process.