Students' Persistence and Academic Success in a First-Year Professional Bachelor Program: The Influence of Students' Learning Strategies and Academic Motivation

Abstract

The present study explores whether students' learning strategies and academic motivation predict persistence and academic success in the first year of higher education. Freshmen students in a professional bachelor program in teacher education were questioned on their learning strategy use and motivation at the start and at the end of the academic year. Students' learning strategies were assessed using the inventory of learning styles-SV. Motivation was measured using scales from the self-regulation questionnaire and the academic motivation scale. Gender and students' prior education were incorporated as control variables. Logistic regression analyses and general linear modelling were applied to predict persistence and academic success, respectively. In each case a stepwise approach in data analysis was used. Results on persistence indicate that lack of regulation and amotivation at the start of the year are significant predictors. For academic success, results showed that relating and structuring, lack of regulation, and lack of motivation at the end of the year are meaningful predictors. Overall, our study demonstrates that learning strategies and motivation have a moderate explanatory value regarding academic success and persistence, and that these effects remain even after controlling for the influence of background variables.

Academic success is about self-efficacy rather than frequency of use of the learning management system

“…In contrast, those who are extrinsically motivated usually have lower levels of SE (Friedal et al, 2007), with studies reporting mixed findings regarding the relationship between academic achievement, SE, and extrinsic motivation (Bong, 2005;Harackiewicz, Barron, Tauer, Carter, & Elliot, 2000). High amotivation has also been associated with lower SE (Turner, Chandler, & Heffer, 2009), poorer academic success (Vanthournout, Gijbels, Coertjens, Donche, & Van Petegem, 2012), and feeling that a behaviour is beyond one's control (Legault et al, 2006).…”

The role of students' motivation and participation in predicting performance in a MOOC

“…Although initially MOOCs students are highly motivated, only a very small number persist until the end of the course (e.g., Clow, 2013;MOOCs@Edinburgh Group, 2013). Previous studies show that lack of persistence in online environments is associated with low levels of motivation (Hart, 2012;Vallerand, Fortier, & Guay, 1997;Vanthournout, Gijbels, Coertjens, Donche, & Van Petegem, 2012). However, not much is known about how this relationship functions in an environment where students are initially highly motivated, such as MOOCs.…”

Early Detection of At-Risk Undergraduate Students through Academic Performance Predictors

“…The results showed that the meaning-directed learning style had a low positive association with academic performance, whereas the undirected learning style had a low negative association with academic performance (Boyle, Duffy, & Dunleavy, 2003). Other studies, for example Vanthournout et al (2012) and Komarraju et al (2012) have suggested that learning styles may influence academic performance. This research attempts to determine the extent to which learning styles influence academic performance in the current setup.…”