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The Power of Feedback Revisited: A Meta-Analysis of Educational Feedback Research.

ABSTRACT: A meta-analysis (435 studies, k = 994, N > 61,000) of empirical research on the effects of feedback on student learning was conducted with the purpose of replicating and expanding the Visible Learning research (Hattie and Timperley, 2007; Hattie, 2009; Hattie and Zierer, 2019) from meta-synthesis. Overall results based on a random-effects model indicate a medium effect (d = 0.48) of feedback on student learning, but the significant heterogeneity in the data shows that feedback cannot be understood as a single consistent form of treatment. A moderator analysis revealed that the impact is substantially influenced by the information content conveyed. Furthermore, feedback has higher impact on cognitive and motor skills outcomes than on motivational and behavioral outcomes. We discuss these findings in the light of the assumptions made in The power of feedback (Hattie and Timperley, 2007). In general, the results suggest that feedback has rightly become a focus of teaching research and practice. However, they also point toward the necessity of interpreting different forms of feedback as independent measures.

SUBMITTER: Wisniewski B

PROVIDER: S-EPMC6987456 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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The Power of Feedback Revisited: A Meta-Analysis of Educational Feedback Research.

Wisniewski Benedikt B Zierer Klaus K Hattie John J

Frontiers in psychology 20200122

A meta-analysis (435 studies, k = 994, N > 61,000) of empirical research on the effects of feedback on student learning was conducted with the purpose of replicating and expanding the Visible Learning research (Hattie and Timperley, 2007; Hattie, 2009; Hattie and Zierer, 2019) from meta-synthesis. Overall results based on a random-effects model indicate a medium effect (d = 0.48) of feedback on student learning, but the significant heterogeneity in the data shows that ...[more]

PMID: 32038429

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Project description:BackgroundConditional power of network meta-analysis (NMA) can support the planning of randomized controlled trials (RCTs) assessing medical interventions. Conditional power is the probability that updating existing inconclusive evidence in NMA with additional trial(s) will result in conclusive evidence, given assumptions regarding trial design, anticipated effect sizes, or event probabilities.MethodsThe present work aimed to estimate conditional power for potential future trials on antidepressant treatments. Existing evidence was based on a published network of 502 RCTs conducted between 1979-2018 assessing acute antidepressant treatment in major depressive disorder (MDD). Primary outcomes were efficacy in terms of the symptom change on the Hamilton Depression Scale (HAMD) and tolerability in terms of the dropout rate due to adverse events. The network compares 21 antidepressants consisting of 231 relative treatment comparisons, 164 (efficacy) and 127 (tolerability) of which are currently assumed to have inconclusive evidence.ResultsRequired sample sizes to achieve new conclusive evidence with at least 80% conditional power were estimated to range between N = 894 - 4190 (efficacy) and N = 521 - 1246 (tolerability). Otherwise, sample sizes ranging between N = 49 - 485 (efficacy) and N = 40 - 320 (tolerability) may require stopping for futility based on a boundary at 20% conditional power. Optimizing trial designs by considering multiple trials that contribute both direct and indirect evidence, anticipating alternative effect sizes or alternative event probabilities, may increase conditional power but required sample sizes remain high. Antidepressants having the greatest conditional power associated with smallest required sample sizes were identified as those on which current evidence is low, i.e., clomipramine, levomilnacipran, milnacipran, nefazodone, and vilazodone, with respect to both outcomes.ConclusionsThe present results suggest that conditional power to achieve new conclusive evidence in ongoing or future trials on antidepressant treatments is low. Limiting the use of the presented conditional power analysis are primarily due to the estimated large sample sizes which would be required in future trials as well as due to the well-known small effect sizes in antidepressant treatments. These findings may inform researchers and decision-makers regarding the clinical relevance and justification of research in ongoing or future antidepressant RCTs in MDD.

Project description:Parental care (any non-genetic contribution by a parent that appears likely to increase the fitness of its offspring) is a widespread trait exhibited by a broad range of animal taxa. In addition to influencing the fitness of parent(s) and offspring, parental care may be inextricably involved in other evolutionary processes, such as sexual selection and the evolution of endothermy. Yet, recent work has demonstrated that bias related to taxonomy is prevalent across many biological disciplines, and research in parental care may be similarly burdened. Thus, I used parental care articles published in six leading journals of fundamental behavioral sciences (Animal Behaviour, Behavioral Ecology, Behavioral Ecology and Sociobiology, Ethology, Hormones and Behavior, and Physiology & Behavior) from 2001-2010 (n?=?712) to examine the year-to-year dynamics of two types of bias related to taxonomy across animals: (1) taxonomic bias, which exists when research output is not proportional to the frequency of organisms in nature, and (2) taxonomic citation bias, which is a proxy for the breadth of a given article-specifically, the proportion of articles cited that refer solely to the studied taxon. I demonstrate that research on birds likely represents a disproportionate amount of parental care research and, thus, exhibits taxonomic bias. Parental care research on birds and mammals also refers to a relatively narrow range of taxonomic groups when discussing its context and, thus, exhibits taxonomic citation bias. Further, the levels of taxonomic bias and taxonomic citation bias have not declined over the past decade despite cautionary messages about similar bias in related disciplines--in fact, taxonomic bias may have increased. As in Bonnet et al. (2002), my results should not be interpreted as evidence of an 'ornithological Mafia' conspiring to suppress other taxonomic groups. Rather, I generate several rational hypotheses to determine why bias persists and to guide future work.

Dataset Information

The Power of Feedback Revisited: A Meta-Analysis of Educational Feedback Research.

Publications

The Power of Feedback Revisited: A Meta-Analysis of Educational Feedback Research.

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