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The extent of variability in learning strategies and students' perceptions of the learning environment

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TLDR
In this paper, a study focused on discerning subgroups of learners with respect to variability in learning strategies and the role of students' learning environment perceptions in it, and the variability in deep and surface learning has been discussed as part of the trait vs. state debate.
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This article is published in Learning and Instruction.The article was published on 2008-04-01. It has received 90 citations till now. The article focuses on the topics: Learning environment & Cooperative learning.

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Using student-centred learning environments to stimulate deep approaches to learning: Factors encouraging or discouraging their effectiveness

TL;DR: In this paper, a review outlines encouraging and discouraging factors in stimulating the adoption of deep approaches to learning in student-centred learning environments, which can be situated in the context of the learning environment, in students' perceptions of that context and in characteristics of the students themselves.
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In search for the most informative data for feedback generation

TL;DR: This empirical contribution provides an application of Buckingham Shum and Deakin Crick's theoretical framework of dispositional learning analytics: an infrastructure that combines learning dispositions data with data extracted from computer-assisted, formative assessments and LMSs.
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Engineering students' conceptions of and approaches to learning through discussions in face-to-face and online contexts

TL;DR: In this paper, a study focused on students' conceptions of and approaches to learning through face-to-face and online discussions was carried out in a course in which students worked in small teams and in which team discussions took place both face to face and online.
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Constructivist learning environments and the (im)possibility to change students’ perceptions of assessment demands and approaches to learning

TL;DR: In this paper, the authors investigated whether students who participate in a constructivist learning environment change their perception of assessment demands towards more deep level demands and whether there is a relation between change in approaches to learning and change in the perceptions of the assessment demands.
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A Critical Discussion of Deep and Surface Processing: What It Means, How It Is Measured, the Role of Context, and Model Specification

TL;DR: In this article, the authors examined four areas that may contribute to the inconsistency and ambiguity of these research results: conceptualization, operationalization, situational factors, and model specification of deep and surface processing.
References
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Book

Using multivariate statistics

TL;DR: In this Section: 1. Multivariate Statistics: Why? and 2. A Guide to Statistical Techniques: Using the Book Research Questions and Associated Techniques.
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Multivariate Data Analysis

TL;DR: In this paper, a six-step framework for organizing and discussing multivariate data analysis techniques with flowcharts for each is presented, focusing on the use of each technique, rather than its mathematical derivation.
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Multivariate data analysis

TL;DR: This chapter discusses Structural Equation Modeling: An Introduction, and SEM: Confirmatory Factor Analysis, and Testing A Structural Model, which shows how the model can be modified for different data types.
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On qualitative differences in learning: i—outcome and process*

TL;DR: In this paper, the authors describe an attempt to identify different levels of processing of information among groups of Swedish university students who were asked to read substantial passages of prose and also about how they set about reading the passages.
Book

Problem-based learning : an approach to medical education

TL;DR: This book presents the scientific basis of problem-based learning and goes on to describe the approaches to problem- based medical learning that have been developed over the years at McMaster University, largely by Barrows and Tamblyn.