DIGITAL LIBRARY
HOW DO COGNITIVE ABILITY AND STUDY MOTIVATION PREDICT THE ACADEMIC PERFORMANCE OF IT STUDENTS?
University of Tartu (ESTONIA)
About this paper:
Appears in: ICERI2015 Proceedings
Publication year: 2015
Pages: 7167-7176
ISBN: 978-84-608-2657-6
ISSN: 2340-1095
Conference name: 8th International Conference of Education, Research and Innovation
Dates: 18-20 November, 2015
Location: Seville, Spain
Abstract:
About one third of Estonian ICT students drop out during the first critical year of higher education studies. In general, studies have shown that dropout is mostly linked to lower academic performance and the latter is influenced by several characteristics of learners and the learning community (see Kori et al., 2015; Larsen et al., 2013; Tinto, 1975 and 2006-2007). Nowadays the meaning of a learning community and engagement in it is changing because of the expansion of digital communities. This is especially the case in ICT studies where students are more familiar with ICT tehnologies for learning. Therefore ICT students are a promising group to study in order to discover how motivational aspects and cognitive abilities of digitally competent students are combined in predicting academic performance and dropout and what the role of both of them is. The high dropout rate of ICT students might be due to problems they have with academic and social integration (see Tinto, 2006-2007) in the context of their university studies.

Many studies have demonstrated that academic performance is correlated with students’ cognitive abilities. The strongest correlations with academic achievement in the first university year have been found when results of cognitive ability tests have been combined with high school average scores (Bridgeman, McCamley-Jenkins & Ervin, 2000). Performance in college is also predicted by achievement motivation (Robbins et al., 2004; Eccles & Wigfield, 2002). Niitsoo et al. (2014) showed that in the context of ICT studies both prior achievement in mathematics and time spent studying during the semester were significant predictors of students’ academic performance. However, these three factors – academic performance, cognitive ability and study motivation – have not been linked in the context of ICT studies. Therefore, we were interested in how cognitive ability and study motivation could lead to better academic performance.

In this study data was collected from 44 first year students who started their universities studies in ICT related curricula. We asked them to fill in a study motivation questionnaire and cognitive ability test. In addition, data about their academic performance was collected from the university’s study information system. The motivation questionnaire (adapted by Einaste & Mägi, 2011 from Vallerand et al., 1989) measured intrinsic motivation (to know, toward accomplishment, to experience stimulation), extrinsic motivation (identified, introjected, external regulation) and amotivation. The cognitive ability test used was a test developed at the University of Tartu to predict students’ academic performance (Must & Allik, 2001). The version used in the current study focused on three dimensions: linguistic, mathematical and spatial abilities.

Our findings demonstrated that students’ cognitive ability is mainly correlated with intrinsic study motivation. The higher a students’ cognitive ability the stronger his or her intrinsic motivation. The best predictor of academic motivation in ICT studies seems to be students’ mathematical ability. Among the three dimensions of intrinsic motivation the willingness to experience stimulation was the one with the strongest correlation to all dimensions of academic performance. A regression analysis also demonstrated the importance of cognitive abilities and study motivation in predicting academic performance.
Keywords:
Dropout, academic performance, ICT studies, motivation, cognitive ability.