A novel CALM algorithm in student profiling
Computer Applications in Engineering Education, 2018, 26(4): 841-851.
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.
CALM algorithm; career prediction; student profiling; subject selection