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      Modeling Change in Learning Strategies throughout Higher Education: A Multi-Indicator Latent Growth Perspective

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          Abstract

          The change in learning strategies during higher education is an important topic of research in the Student Approaches to Learning field. Although the studies on this topic are increasingly longitudinal, analyses have continued to rely primarily on traditional statistical methods. The present research is innovative in the way it uses a multi-indicator latent growth analysis in order to more accurately estimate the general and differential development in learning strategy scales. Moreover, the predictive strength of the latent growth models are estimated. The sample consists of one cohort of Flemish University College students, 245 of whom participated in the three measurement waves by filling out the processing and regulation strategies scales of the Inventory of Learning Styles – Short Versions. Independent-samples t-tests revealed that the longitudinal group is a non-random subset of students starting University College. For each scale, a multi-indicator latent growth model is estimated using Mplus 6.1. Results suggest that, on average, during higher education, students persisting in their studies in a non-delayed manner seem to shift towards high-quality learning and away from undirected and surface-oriented learning. Moreover, students from the longitudinal group are found to vary in their initial levels, while, unexpectedly, not in their change over time. Although the growth models fit the data well, significant residual variances in the latent factors remain.

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          Psychological correlates of university students' academic performance: a systematic review and meta-analysis.

          A review of 13 years of research into antecedents of university students' grade point average (GPA) scores generated the following: a comprehensive, conceptual map of known correlates of tertiary GPA; assessment of the magnitude of average, weighted correlations with GPA; and tests of multivariate models of GPA correlates within and across research domains. A systematic search of PsycINFO and Web of Knowledge databases between 1997 and 2010 identified 7,167 English-language articles yielding 241 data sets, which reported on 50 conceptually distinct correlates of GPA, including 3 demographic factors and 5 traditional measures of cognitive capacity or prior academic performance. In addition, 42 non-intellective constructs were identified from 5 conceptually overlapping but distinct research domains: (a) personality traits, (b) motivational factors, (c) self-regulatory learning strategies, (d) students' approaches to learning, and (e) psychosocial contextual influences. We retrieved 1,105 independent correlations and analyzed data using hypothesis-driven, random-effects meta-analyses. Significant average, weighted correlations were found for 41 of 50 measures. Univariate analyses revealed that demographic and psychosocial contextual factors generated, at best, small correlations with GPA. Medium-sized correlations were observed for high school GPA, SAT, ACT, and A level scores. Three non-intellective constructs also showed medium-sized correlations with GPA: academic self-efficacy, grade goal, and effort regulation. A large correlation was observed for performance self-efficacy, which was the strongest correlate (of 50 measures) followed by high school GPA, ACT, and grade goal. Implications for future research, student assessment, and intervention design are discussed.
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            Approaches to learning in science: a longitudinal study.

            Longitudinal studies of students' approaches to learning in higher education can tell us much about the impact of the tertiary experience. More information about teaching and learning practices and how students respond to these may enable educators to better assist students to gain the maximum benefit from their tertiary studies. The study set out: (i) to monitor the change in approaches to learning over a three-year period; (ii) to evaluate the relationship between student age, sex and university entry mode on students' approaches to learning; and (iii) to evaluate the predictive validity of the SPQ scales on one mode of learning outcome, that being annual GPA. The sample consisted of 200 commencing students studying in a science course at an Australian university. The Biggs SPQ was administered in a first-year chemistry class and repeated at intervals of 4 and 8 months. This was followed by administration by post after 16 months and 30 months. Student approach to learning is dynamic and amenable to change as a result of the learning experience. Of the three SPQ scales, the achieving approach appears to undergo the greatest change with time, while the deep approach showed a consistent positive correlation with assessment outcomes. Student age was a major factor in both the SPQ scores and assessment outcomes but no gender effect was evident. Students see university study, and in particular the first year, as a survival course and adopt strategies suited to that task. Older students adopt approaches to study which differ from their younger colleagues and as a consequence they are in general more successful in the tertiary environment.
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              Developing deep learning approaches and personal teaching efficacy within a preservice teacher education context.

              University students' approaches to learning have been demonstrated to affect learning outcomes across a wide range of courses, favouring the use of a deep approach. Interventions to promote the use of deep approaches have had mixed success, with the most successful interventions involving large-scale course redesign.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2013
                3 July 2013
                : 8
                : 7
                : e67854
                Affiliations
                [1 ]Institute for Educational and Information Sciences, University of Antwerp, Antwerp, Belgium
                [2 ]Centre for Statistics at the University of Antwerp (StatUA), University of Antwerp, Antwerp, Belgium
                Chancellor College, University of Malawi, Malawi
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: LC VD SDM GV PVP. Performed the experiments: LC VD SDM GV PVP. Analyzed the data: LC VD SDM GV PVP. Contributed reagents/materials/analysis tools: LC VD SDM GV PVP. Wrote the paper: LC VD SDM GV PVP.

                Article
                PONE-D-13-01335
                10.1371/journal.pone.0067854
                3700906
                23844112
                d2a1d38c-a34b-4c04-973f-567d7cceaeff
                Copyright @ 2013

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 3 January 2013
                : 21 May 2013
                Page count
                Pages: 12
                Funding
                The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The research reported in this article was supported by a grant from the “Special Research Fund: New Research Initiatives” from the Research Board of the University of Antwerp. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Medicine
                Clinical Research Design
                Longitudinal Studies
                Social and Behavioral Sciences
                Psychology
                Behavior
                Attention (Behavior)
                Habits
                Human Performance
                Vigilance
                Cognitive Psychology
                Learning
                Motivation
                Applied Psychology
                Developmental Psychology

                Uncategorized
                Uncategorized

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