Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/9966
Title: Cognitive processes in university learning: A developmental framework using structural equation modelling
Contributor(s): Phan, Huy  (author)orcid 
Publication Date: 2011
DOI: 10.1348/2044-8279.002000
Handle Link: https://hdl.handle.net/1959.11/9966
Abstract: Background: Both achievement goals and study processing strategies theories have been shown to contribute to the prediction of students' academic performance. Existing research studies (Fenollar, Roman, & Cuestas, 2007; Liem, Lau, & Nie, 2008; Simons, Dewitte, & Lens, 2004) amalgamating these two theoretical orientations in different causal models have reported their associations with other adaptive strategies and motivational constructs - for example, effort expenditure. Despite this recognition, there have been to date very few studies that explored the relations between achievement goals, study processing strategies, effort, and academic performance over time. Aim of study: The primary focus of our study is to explore the relations between the aforementioned theoretical constructs over a 2-year period. Specifically, we tested an empirical model that conceptualized the relations between performance-approach and mastery goals, deep processing strategies, effort, and academic performance across six time points of data collection. Methodology: Two hundred and eighty-one (161 females, 120 males) university students took part in this study. The participants were administered various Likert-scale inventories and the overall course mark and final examination were used as indexes of academic performance. Results: Structural equation modelling indicated a relatively good fit to the a posteriori model and the hypothesized paths were, in part, supported. The major findings included the predictive effects of performance-approach goals at Time 1 on deep processing strategies at Time 2 and mastery goals at Time 3; the predictive effect of mastery goals at Time 3 on effort at Time 4; the predictive effects of deep processing at Time 2 on mastery goals at Time 3 and Time 4. Furthermore, the placement of deep processing and effort in this structural model also accentuated the performance-approach goals - mastery goals - effort - academic performance relation, and the performance-approach goals - deep processing - mastery goals - effort - academic performance relation. Discussion: Our study has important theoretical and practical implications concerning the conceptualization of the performance-approach and mastery goals relationship, and the use of goal structure and adaptive strategies (e.g., deep processing) to enhance academic learning.
Publication Type: Journal Article
Source of Publication: British Journal of Educational Psychology, 81(3), p. 509-530
Publisher: John Wiley & Sons Ltd
Place of Publication: United Kingdom
ISSN: 2044-8279
0007-0998
Fields of Research (FoR) 2008: 170103 Educational Psychology
139999 Education not elsewhere classified
130103 Higher Education
Socio-Economic Objective (SEO) 2008: 930102 Learner and Learning Processes
930199 Learner and Learning not elsewhere classified
930101 Learner and Learning Achievement
Peer Reviewed: Yes
HERDC Category Description: C1 Refereed Article in a Scholarly Journal
Appears in Collections:Journal Article
School of Education

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