Revisiting the Knowledge Gap Hypothesis: A Meta-Analysis of Thirty-Five Years of Research

2009 ◽  
Vol 86 (3) ◽  
pp. 513-532 ◽  
Author(s):  
Yoori Hwang ◽  
Se-Hoon Jeong

This knowledge gap meta-analysis examines (a) average effect size of the gap, (b) impact of media publicity, and (c) moderators of the gap. Positive correlation between education and level of knowledge ( r = .28) was found, with no differences in the size of the gap (a) over time and (b) between issues of higher and lower publicity. However, gap magnitude was moderated by topic, setting, knowledge measure, and study design, but not by publication status, country, and sampling method. Relatively smaller gaps were found for (a) health-science topics compared to social-political topics and (b) local/personal issues compared to international issues.

2021 ◽  
pp. 1-33
Author(s):  
Chantal VAN DIJK ◽  
Elise VAN WONDEREN ◽  
Elly KOUTAMANIS ◽  
Gerrit Jan KOOTSTRA ◽  
Ton DIJKSTRA ◽  
...  

Abstract Although cross-linguistic influence at the level of morphosyntax is one of the most intensively studied topics in child bilingualism, the circumstances under which it occurs remain unclear. In this meta-analysis, we measured the effect size of cross-linguistic influence and systematically assessed its predictors in 750 simultaneous and early sequential bilingual children in 17 unique language combinations across 26 experimental studies. We found a significant small to moderate average effect size of cross-linguistic influence, indicating that cross-linguistic influence is part and parcel of bilingual development. Language dominance, operationalized as societal language, was a significant predictor of cross-linguistic influence, whereas surface overlap, language domain and age were not. Perhaps an even more important finding was that definitions and operationalisations of cross-linguistic influence and its predictors varied considerably between studies. This could explain the absence of a comprehensive theory in the field. To solve this issue, we argue for a more uniform method of studying cross-linguistic influence.


2002 ◽  
Vol 6 (1) ◽  
pp. 59-71 ◽  
Author(s):  
Jean M. Twenge ◽  
W. Keith Campbell

Socioeconomic status (SES) has a small but significantrelationship with self-esteem (d = .15, r = .08) in a meta-analysis of 446 samples (total participant N = 312,940). Higher SES individuals report higher self-esteem. The effect size is very small in young children, increases substantially during young adulthood, continues higher until middle age, and is then smaller for adults over the age of 60. Gender interacts with birth cohort: The effect size increased over time for women but decreased over time for men. Asians and Asian Americans show a higher effect size, and occupation and education produce higher correlations with self-esteem than income does. The results are most consistent with a social indicator or salience model.


2016 ◽  
Author(s):  
Sara Ballouz ◽  
Jesse Gillis

AbstractBackgroundDisagreements over genetic signatures associated with disease have been particularly prominent in the field of psychiatric genetics, creating a sharp divide between disease burdens attributed to common and rare variation, with study designs independently targeting each. Meta-analysis within each of these study designs is routine, whether using raw data or summary statistics, but combining results across study designs is atypical. However, tests of functional convergence are used across all study designs, where candidate gene sets are assessed for overlaps with previously known properties. This suggests one possible avenue for combining not study data, but the functional conclusions that they reach.MethodIn this work, we test for functional convergence in autism spectrum disorder (ASD) across different study types, and specifically whether the degree to which a gene is implicated in autism is correlated with the degree to which it drives functional convergence. Because different study designs are distinguishable by their differences in effect size, this also provides a unified means of incorporating the impact of study design into the analysis of convergence.ResultsWe detected remarkably significant positive trends in aggregate (p < 2.2e-16) with 14 individually significant properties (FDR<0.01), many in areas researchers have targeted based on different reasoning, such as the fragile X mental retardation protein (FMRP) interactor enrichment (FDR 0.003). We are also able to detect novel technical effects and we see that network enrichment from protein-protein interaction data is heavily confounded with study design, arising readily in control data.ConclusionsWe see a convergent functional signal for a subset of known and novel functions in ASD from all sources of genetic variation. Meta-analytic approaches explicitly accounting for different study designs can be adapted to other diseases to discover novel functional associations and increase statistical power.


Author(s):  
Elvi Suryanti ◽  
Asrizal Asrizal ◽  
Fatni Mufit

ABSTRAKTujuan penelitian ini adalah untuk mengetahui pengaruh Model discovery learning terhadap penguasaan konsep dan pengetahuan fisika SMA. Metode yang digunakan dalam penelitian ini adalah meta-analisis. Teknik analisis data dalam penelitian ini menggunakan perhitungan nilai effect size untuk setiap artikel. Berdasarkan meta analisis yang dilakukan, dapat dinyatakan bahwa hasil penelitian ini yaitu : 1) pengaruh model discovery learning terhadap penguasaan konsep dan pengetahuan  fisika SMA ditinjau dari tahun terbit artikel memberikan efek yang Sangat Tinggi terdapat pada tahun 2017,2018, dan 2020 dengan masing-masing rata-rata effect size yaitu 1,6; 1,15; dan 1,62. 2) pengaruh model discovery learning terhadap penguasaan konsep dan pengetahuan  fisika SMA ditinjau dari tingkatan kelas memberikan efek Sangat Tinggi terdapat pada kelas XI dengan rata-rata effect size 1,25. 3) pengaruh discovery learning terhadap penguasaan konsep fisika SMA memberikan efek Sangat Tinggi  terdapat pada artikel keenam (J6) dengan  nilai effect size 2,38. 4) pengaruh discovery learning terhadap pengetahuan  fisika SMA memberikan efek Sangat Tinggi  terdapat pada artikel kesepuluh (J10) dengan  nilai effect size 3,95. Hal ini menunjukkan bahwa terdapat pengaruh model discovery learning terhadap penguasaan konsep dan pengetahuan  fisika SMA. Kata kunci: Discovery Learning; Penguasaan Konsep; Pengetahuan. ABSTRACTThe purpose of this study was to determine the effect of the discovery learning model on mastery of high school physics concepts and knowledge. The method used in this research is meta-analysis. The data analysis technique in this study uses the calculation of the effect size value for each article. Based on the meta-analysis carried out, it can be stated that the results of this study are: 1) the effect of the discovery learning model on mastery of concepts and knowledge of high school physics in terms of the year the article was published gave a Very High effect in 2017,2018, and 2020 with each the average effect size is 1.6; 1.15; and 1.62. 2) the influence of the discovery learning model on the mastery of concepts and knowledge of high school physics in terms of grade level gives a very high effect in class XI with an average effect size of 1.25. 3) the effect of discovery learning on mastery of high school physics concepts gives a Very High effect found in the sixth article (J6) with an effect size value of 2.38. 4) the effect of discovery learning on high school physics knowledge gives a very high effect in the tenth article (J10) with an effect size value of 3.95. This shows that there is an influence of the discovery learning model on the mastery of high school physics concepts and knowledge. Keywords: Discovery Learning; Concept Mastery; Knowledge.


Author(s):  
M. Ifdal Hafiz Chan ◽  
Edja Annisa Septia ◽  
Kurnia Febrianti ◽  
Desnita Desnita

ABSTRAKTujuan dari penelitian ini adalah untuk melihat efektivitas dari beberapa model pembelajaran dalam meningkatkan pemahaman konsep fisika siswa SMA. Penelitian ini merupakan penelitian meta-analisis yang menggambarkan effect size dari penelitian-penelitian pendidikan mengenai pengaruh model-model pembelajaran terhadap pemahaman konsep fisika siswa SMA. Model pembelajaran yang di bandingkan dalam penelitian meta-analisis ini adalah model pembelajaran Discovery Learning, Inkuiri, Kooperatif, Direct Instruction, dan Problem Based Learning. Model pembelajaran yang memiliki efektivitas tertinggi adalah model pembelajaran Langsung (Direct Instruction) dengan nilai rata-rata effect size 1.43 yang termasuk dalam kategori tinggi. Model pembelajaran lain yang juga memiliki nilai rata-rata effect size yang termasuk dalam kategori tinggi adalah model pembelajaran Inkuiri dengan nilai rata-rata effect size 1.39, model pembelajaran Kooperatif dengan nilai rata-rata effect size 1.11, model pembelajaran Discovery Learning dengan nilai rata-rata effect size 0.96, serta model pembelajaran Problem Based Learning dengan nilai rata-rata effect size 0.92. Kata kunci: Meta-Analisis; Discovery Learning; Inkuiri; Kooperatif; Direct Instruction; Problem Based Learning; Pemahaman Konsep; Fisika ABSTRACT The purpose of this study was to see the effectiveness of several learning models in improving the understanding of physics concepts for high school students. This research is a meta-analysis that describes the effect size of educational studies regarding the influence of learning models on the understanding of physics concepts for high school students. The learning models compared in this meta-analysis are the Discovery Learning, Inquiry, Cooperative, Direct Instruction, and Problem Based Learning learning models. The learning model that has the highest effectiveness is the Direct Instruction model with an average effect size value of 1.43 which is included in the high category. Other learning models that also have an average effect size value that is included in the high category are the Inquiry learning model with an average effect size value of 1.39, the Cooperative learning model with an average effect size value of 1.11, and the Discovery Learning learning model with an average value. the average effect size is 0.96, as well as the Problem Based Learning model with an average effect size value of 0.92. Keywords: Meta-Analysis; Discovery Learning; Inquiry; Cooperative; Direct Instruction; Problem Based Learning; Concept Understanding; Physics.


1996 ◽  
Vol 15 (2) ◽  
pp. 157-174 ◽  
Author(s):  
Richard P. Niemiec ◽  
Christian Sikorski ◽  
Herbert J. Walberg

This article concerns the effects of learner control in computer-assisted instruction (CAI). After reviewing previous reviews of research on the topic, twenty-four studies of learner control were subjected to meta-analysis. The results of both the review and meta-analysis are equivocal. Several reviews indicate that learner control works less well with younger, less able students. Other reviews indicate that, given optimal conditions, learner control can work with any students. The meta-analysis, however, yielded an average effect size that was small and negative suggesting that the average student would be slightly better off without it. Although learner control has theoretical appeal, its effects on learning seem neither powerful nor consistent.


2021 ◽  
pp. 1932202X2110615
Author(s):  
Russell T. Warne

Recently, Picho-Kiroga (2021) published a meta-analysis on the effect of stereotype threat on females. Their conclusion was that the average effect size for stereotype threat studies was d = .28, but that effects are overstated because the majority of studies on stereotype threat in females include methodological characteristics that inflate the apparent effect size. In this response, I show that Picho-Kiroga et al. (2021) committed fundamental errors in their meta-analysis that undermine confidence in the article and warrant major corrections. But even if the data were not flawed, the conclusion that Picho-Kiroga et al. (2021) should have reached is that their results are most consistent with a population effect size of zero. There is no compelling evidence that stereotype threat is a real phenomenon in females.


2017 ◽  
Vol 31 (2) ◽  
pp. 137-159 ◽  
Author(s):  
Fuschia M. Sirois ◽  
Danielle S. Molnar ◽  
Jameson K. Hirsch ◽  
Mitja Back

The equivocal and debated findings from a 2007 meta–analysis, which viewed perfectionism as a unidimensional construct, suggested that perfectionism was unrelated to procrastination. The present meta–analysis aimed to provide a conceptual update and reanalysis of the procrastination–perfectionism association guided by both a multidimensional view of perfectionism and self–regulation theory. The random–effects meta–analyses revealed a small to medium positive average effect size ( r = .23; k = 43, N = 10 000; 95% confidence interval (95% CI) [0.19, 0.27]) for trait procrastination and perfectionistic concerns and a small to medium negative average effect size ( r = −.22; k = 38, N = 9544; 95% CI [−0.26, −0.18]) for procrastination and perfectionistic strivings. The average correlations remained significant after statistically accounting for the joint variance between the two perfectionism dimensions via semi–partial correlations. For perfectionistic concerns, but not perfectionistic strivings, the effects depended on the perfectionism measure used. All effects did not vary by the trait procrastination measure used or the respondent's sex. Our findings confirm that from a multidimensional perspective, trait procrastination is both positively and negatively associated with higher–order perfectionism dimensions and further highlights the value of a self–regulation perspective for understanding the cognitive, affective and behavioural dynamics that characterise these traits. Copyright © 2017 European Association of Personality Psychology


1992 ◽  
Vol 17 (4) ◽  
pp. 363-374 ◽  
Author(s):  
Donald B. Rubin

A traditional meta-analysis can be thought of as a literature synthesis, in which a collection of observed studies is analyzed to obtain summary judgments about overall significance and size of effects. Many aspects of the current set of statistical tools for meta-analysis are highly useful—for example, the development of clear and concise effect-size indicators with associated standard errors. I am less happy, however, with more esoteric statistical techniques and their implied objects of estimation (i.e., their estimands) which are tied to the conceptualization of average effect sizes, weighted or otherwise, in a population of studies. In contrast to these average effect sizes of literature synthesis, I believe that the proper estimand is an effect-size surface, which is a function only of scientifically relevant factors, and which can only be estimated by extrapolating a response surface of observed effect sizes to a region of ideal studies. This effect-size surface perspective is presented and contrasted with the literature synthesis perspective. The presentation is entirely conceptual. Moreover, it is designed to be provocative, thereby prodding researchers to rethink traditional meta-analysis and ideally stimulating meta-analysts to attempt effect-surface estimations.


2020 ◽  
Author(s):  
Julia M. Haaf ◽  
Jeffrey N. Rouder

The most prominent goal when conducting a meta-analysis is to estimate the true effect size across a set of studies. This approach is problematic whenever the analyzed studies are inconsistent, i.e. some studies show an effect in the predicted direction while others show no effect and still others show an effect in the opposite direction. In case of such an inconsistency, the average effect may be a product of a mixture of mechanisms. The first question in any meta-analysis should therefore be whether all studies show an effect in the same direction. To tackle this question a model with multiple ordinal constraints is proposed---one constraint for each study in the set. This "every study" model is compared to a set of alternative models, such as an unconstrained model that predicts effects in both directions. If the ordinal constraints hold, one underlying mechanism may suffice to explain the results from all studies. A major implication is then that average effects become interpretable. We illustrate the model-comparison approach using Carbajal et al.'s (2020) meta-analysis on the familiar-word-recognition effect, show how predictor analyses can be incorporated in the approach, and provide R-code for interested researchers. As common in meta-analysis, only surface statistics (such as effect size and sample size) are provided from each study, and the modeling approach can be adapted to suit these conditions.


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