The contribution of intelligence, learning strategies, and personal development to engineering students' academic performance

Abstract

Previous studies have addressed the question whether intellectual ability (as measured by the Raven's Progressivp Matrices Tests) is related to academic performance in engineering (Rushton & Skuy, 2000; Rushton, Skuy & Fridjhon, 2002; Rushton, Skuy & Fridjhon, 2003). The question arose of whether nonintellective (personality and attitudinal factors) playa larger role at this level, than intelligence, in determining academic performance in engineering university students. Accordingly, data were yielded for 93 percent (N=100) of the second year Chemical Engineering class in terms of their performance on various measures. These included two measures of intellectual ability, namely the Ravens Advanced Progressive Matrices (RAPM) and the Organiser (of The Learning Propensity Assessment Device), together with a measure of learning strategies and attitudes (Learning and Study Strategies Inventory), locus of control (Locus of Control Inventory) and self-esteem (Coopersmith Self-Esteem Inventory). The students' academic results comprised the December 2002 and June 2003 examination results. The current research results demonstrated that while neither the RAPM nor the Organiser yielded any significant correlations with academic results, certain of the non-intellective measures did, and were able to differentiate between high and low academic performers. Motivation, Autonomy and Freedom from Anxiety were found to be significantly related to academic performance, and contributed 26 percent of the variance. This indicates that these factors play a role in academic achievement, and that exploration of personality and motivational factors constitutes a potentially fruitful avenue of research. However, it also seems that 74 percent of variance was unaccounted for, and therefore future studies should explore other factors, not included in this study, in relation to engineering students' academic performance. Furthermore, it emerged that it is unrealistic to attempt to predict academic performance at midyear (June results). KEY WORDS: Intelligence, learning strategies, locus of control, self-esteem, engineering students, second year, and academic performance.