Academic Performance in Professional Programs is Reflection of Non-Cognitive Factors in Students; Predictive Analysis using PLS based Structural Equation Modeling.

Abstract

Students in their under-graduation programs are in an important stage of transition from being a raw student to qualified professional, especially those of who doing professional programs in engineering, management, medicine, legal, finance etc. Industry expects student outcomes in these programs as more holistic one which should meet both cognitive and non-cognitive factors in individuals. The assessment process in such programs not only captures students’ cognitive ability but there are non-cognitive factors that also indirectly influence the academic performance of the students. This paper is a case study to explore how the academic performance of students has a hidden influence on non-cognitive constructs. It is a predictive analysis using PLS-SMART to deduct the predictive nature of those non-cognitive aspects with statistical validations.