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Research Article Open access CC BY 4.0

Principal Component Analysis of Cognitive Executive Functions: A Predictive Model of Academic Performance of Students in Mathematics in Secondary Schools

Ekemini T. Akpan, Joseph B. Umoh, Godwin D. James

Asian Journal of Education and Social Studies · pp. 222–231 · Published 18 May 2024

10.9734/ajess/2024/v50i61408

Abstract

There is a growing interest from instructional scientists in using parameters of brain executive functions to unfold cognitive disorders, Mathematical Learning Difficulties (MLD), and assessment of learners’ academic performance. Thus, it is imperative to investigates, extracts and classify the major principal components of learners’ cognitive executive functions that predict academic performance of students in Mathematics and science related courses in secondary schools. An ex post facto quasi-experimental design was adopted for the study.  Students’ cognitive profile was measured using a validated and reliable cognitive assessment Battery (CAB) application. There were significant positive correlations between cognitive executive functions and academic performance of students in Mathematics. The major components of the executive functions that accounted for substantial effects on academic performance of students in Mathematics include working memory, conceptual memory, short-term memory, inhibition, updating, focus attention, divided attention, auditory perception, and visual perception. Also, processing speed, shifting, planning, hand-eye coordination and response time accounted for moderate effects on academic performance of students in Mathematics. Consequently, instructors should reinforce learners’ cognitive processes using cognitive retraining programmes, personalized learning, differentiated instructional strategies for exceptional students, and offer therapeutic interventions on the identified cognitive parameters that could reduce extraneous cognitive loads. These could facilitate mental internalization of external perception during instructional delivery and learning.

Academic performance executive functions mathematics principal component analysis

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