Study time and academic performance: A conditional relation?

Abstract

Aim: Study results depend on many interacting factors, including students’ and teachers’ personal characteristics, their conceptions, preferences and strategies with respect to learning and teaching, and contextual variables (e.g., Biggs, 2001; Broekkamp & Van Hout-Wolters, 2007). The current study aims to specify the role and place of study time (ST) in this complex set of variables and relationships in a self-regulated learning environment. Although, intuitively, more ST is expected to result in higher performance, research results have been inconsistent (Stinebrickner & Stinebrickner, 2004). In some cases, ST has been shown to predict academic performance beyond a myriad of intellective (e.g., high school GPA, SAT scores) and non-intellective student characteristics (e.g., gender, health; Brint & Cantwell, 2010). In other cases, no significant association was obtained (e.g., Gortner & Zulauf, 2000). This pattern of findings suggests that the role of ST depends on other factors. Aim of the current study is to explore interactions between ST and the quality of learning activities involved. In line with the work of Vermunt (1992) and Masui and De Corte (2005), the focus will be on the affective-motivational, cognitive, and metacognitive processing of course content. Moreover, based on Biggs’ (2001) model of learning, the predictive value of (quantitative and qualitative) features of the learning process for academic performance will be evaluated beyond relevant student characteristics and for different courses. Methodology: In the period 2008-2010, data were gathered from 329 first-year students of the Faculty of Business Economics of Hasselt University (Belgium). Key variables (academic performance, study time, and quality of learning activities) were measured at course level. Each student was assigned to complete measures about one particular course (i.e., Macro-Economics, Micro-Economics, Mathematics, or Financial Accounting). Course grades and student characteristics (gender, prior knowledge,...) were obtained from academic records. Students recorded their ST for a particular course at least weekly for the entire duration of the term by means of a web-based application. Qualitative aspects of the learning activities deployed for the courses concerned were measured by means of a student questionnaire. The affective-motivational learning processes included were self-efficacy, volition, and learning orientation regarding the course. Cognitive processes referred to activities such as structuring, analyzing, and relating course content. Finally, metacognitive processes referred to, for example, the degree to which students monitor and evaluate their comprehension of course content while studying. Findings: Preliminary analyses showed adequate internal consistencies for all questionnaires involved. First, a general model was evaluated (including data from all courses) in order to determine which factors are important overall. Second, the impact of key variables was also evaluated at course level. Interactions between ST and the quality of learning activities were found. Relevance: Theory and research on self-regulated learning primarily includes the quality of learning activities in models of student learning. The current study aims to add to this literature by identifying complex interplays with invested study time.