2016
DOI: 10.1038/npjscilearn.2016.13
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Learning strategies: a synthesis and conceptual model

Abstract: The purpose of this article is to explore a model of learning that proposes that various learning strategies are powerful at certain stages in the learning cycle. The model describes three inputs and outcomes (skill, will and thrill), success criteria, three phases of learning (surface, deep and transfer) and an acquiring and consolidation phase within each of the surface and deep phases. A synthesis of 228 meta-analyses led to the identification of the most effective strategies. The results indicate that ther… Show more

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Cited by 284 publications
(236 citation statements)
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References 67 publications
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“…PST 6 rejected what he/she described as "traditional didactic manner". In this regard PST 6 manifests the view that principles of learning, potentially emphasising facilitation and co-construction (alignment with "teaching pedagogy evidence"), are preferable to a more didactic approach favoured by the author and East Asian educators (e.g., Huang & Leung, 2004;Lai & Murray, 2012;Leung et al, 2015;Li, 2004), meta-data analysts (e.g., Hattie, 2009;Hattie & Donoghue, 2016), and cognitive load theorists (e.g., Chen et al, 2016;Kirschner, Sweller, & Clark, 2006;Sweller, 2016;Tricot & Sweller, 2014). It needs to be noted, however, that while the views of PST 6 provide a reasonably coherent justification for existing generic mathematics teacher education programs and curriculum courses/subjects, they are counter to those expressed by the majority of the pre-service teachers enrolled in the mathematics course informing this study.…”
Section: Discussionmentioning
confidence: 99%
“…PST 6 rejected what he/she described as "traditional didactic manner". In this regard PST 6 manifests the view that principles of learning, potentially emphasising facilitation and co-construction (alignment with "teaching pedagogy evidence"), are preferable to a more didactic approach favoured by the author and East Asian educators (e.g., Huang & Leung, 2004;Lai & Murray, 2012;Leung et al, 2015;Li, 2004), meta-data analysts (e.g., Hattie, 2009;Hattie & Donoghue, 2016), and cognitive load theorists (e.g., Chen et al, 2016;Kirschner, Sweller, & Clark, 2006;Sweller, 2016;Tricot & Sweller, 2014). It needs to be noted, however, that while the views of PST 6 provide a reasonably coherent justification for existing generic mathematics teacher education programs and curriculum courses/subjects, they are counter to those expressed by the majority of the pre-service teachers enrolled in the mathematics course informing this study.…”
Section: Discussionmentioning
confidence: 99%
“…This also accords with our earlier observations, which showed that despite the recent emphasis on achievement, the focus of schools has been on learning procedures and concept, how to know more efficiently and effectively. While students are now ready to learn, it makes teachers should have the skill to enable their "learning sense" and increase the 'how to learn' proficiencies of students (Hattie & Donoghue, 2016). Those top-ten learning models explained elaborately and clearly in this module.…”
Section: The Research Methodsmentioning
confidence: 99%
“…This timing of inquiry, however, seems to be of importance. Hattie and Donoghue (), who performed a meta‐synthesis of a large series of meta‐analyses comprising a total of close to 19,000 individual studies, explicitly mentioned that some more engaged forms of learning and instruction show less favourable effect sizes when they are introduced in the curriculum at a point when the necessary surface knowledge that is needed as a starting point for gaining (deep) conceptual knowledge has not yet been acquired. Schneider and Preckel () also presenting a meta‐synthesis, likewise found that prior instruction (and the associated prior knowledge) is a moderator variable for the effectiveness of engaged forms of learning such as problem‐based learning and inquiry learning.…”
Section: Combining Inquiry With (Technology‐based) Pedagogical Guidancementioning
confidence: 99%