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建模整个高等教育阶段学习策略的变化:多指标潜在增长视角。

Modeling change in learning strategies throughout higher education: a multi-indicator latent growth perspective.

机构信息

Institute for Educational and Information Sciences, University of Antwerp, Antwerp, Belgium.

出版信息

PLoS One. 2013 Jul 3;8(7):e67854. doi: 10.1371/journal.pone.0067854. Print 2013.

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.

摘要

高等教育阶段学习策略的变化是学生学习方法领域的一个重要研究课题。尽管关于这个课题的研究越来越具有纵向性,但分析仍然主要依赖于传统的统计方法。本研究的创新性在于它使用了多指标潜在增长分析,以便更准确地估计学习策略量表的一般和差异发展。此外,还估计了潜在增长模型的预测强度。该样本由一个佛兰德大学学院的学生队列组成,其中 245 名学生通过填写学习风格量表的加工和调节策略量表--短版本,参与了三次测量。独立样本 t 检验显示,纵向组是开始上大学学院的学生的非随机子集。对于每个量表,都使用 Mplus 6.1 估计了一个多指标潜在增长模型。结果表明,平均而言,在高等教育阶段,非延迟继续学业的学生似乎会转向高质量的学习,而不是漫无目的和表面导向的学习。此外,发现纵向组的学生在初始水平上存在差异,而令人意外的是,他们在随时间的变化上没有差异。尽管增长模型很好地拟合了数据,但潜在因素仍然存在显著的残差方差。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c40/3700906/04b024137c88/pone.0067854.g001.jpg

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