A meta-analysis of self-monitoring on reading performance of K–12 students.

2018 ◽  
Vol 33 (1) ◽  
pp. 160-168 ◽  
Author(s):  
Guadalupe Guzman ◽  
Taryn S. Goldberg ◽  
H. Lee Swanson
Keyword(s):  
Meta Analysis ◽  
Reading Performance ◽  
Self Monitoring ◽  
K 12

A Meta-Analytic Review of the Relations Between Motivation and Reading Achievement for K–12 Students

2020 ◽  
Vol 90 (3) ◽  
pp. 420-456 ◽  
Author(s):  
Jessica R. Toste ◽  
Lisa Didion ◽  
Peng Peng ◽  
Marissa J. Filderman ◽  
Amanda M. McClelland
Keyword(s):  
Reading Achievement ◽  
Meta Analysis ◽  
Reading Performance ◽  
Sample Type ◽  
Active Engagement ◽  
12Th Grade ◽  
Analytic Review ◽  
Comprehensive Search ◽  
K 12 ◽  
Published Research

The purpose of this meta-analytic review was to investigate the relation between motivation and reading achievement among students in kindergarten through 12th grade. A comprehensive search of peer-reviewed published research resulted in 132 articles with 185 independent samples and 1,154 reported effect sizes (Pearson’s r). Results of our random-effects metaregression model indicate a significant, moderate relation between motivation and reading, r = .22, p < .001. Moderation analyses revealed that the motivation construct being measured influenced the relation between motivation and reading. There were no other significant moderating or interaction effects related to reading domain, sample type, or grade level. Evidence to support the bidirectional nature of the relation between motivation and reading was provided through longitudinal analyses, with findings suggesting that earlier reading is a stronger predictor of later motivation than motivation is of reading. Taken together, the findings from this meta-analysis provide a better understanding of how motivational processes relate to reading performance, which has important implications for developing effective instructional practices and fostering students’ active engagement in reading. Theoretical and practical implications of these findings for reading development are discussed.

Computational thinking in K-12 education. An insight through meta-analysis

2021 ◽  
pp. 1-26
Author(s):  
José Miguel Merino-Armero ◽  
José Antonio González-Calero ◽  
Ramón Cózar-Gutiérrez
Keyword(s):  
Meta Analysis ◽  
Computational Thinking ◽  
K 12

scholarly journals Effects of Gamification on Behavioral Change in Education: A Meta-Analysis

2021 ◽  
Vol 18 (7) ◽  
pp. 3550
Author(s):  
Jihoon Kim ◽  
Darla M. Castelli
Keyword(s):  
Behavioral Change ◽  
Information Science ◽  
Meta Analysis ◽  
Learning Outcome ◽  
Random Effects Model ◽  
Educational Setting ◽  
Short Term ◽  
Analytic Review ◽  
K 12 ◽  
Academic Search

Background: Gamified reward systems, such as providing digital badges earned for specific accomplishments, are related to student engagement in educational settings. The purpose of this study was to conduct a meta-analytic review to quantify the effects of gamified interventions on student behavioral change. Methods: A meta-analysis was performed using the following databases: The Academic Search Complete, Communication & Mass Media Complete, Education Source, ERIC, Library Information Science & Technology Abstracts, and PsycINFO. Inclusion in the review required: (a) peer-reviewed conducted between 2010 and 2019, (b) experimental controlled design, (c) gamification elements, and (d) educational setting. Results: Using a random-effects model, a statistically significant (Cohen’s d (ES) = 0.48, 95% CI = 0.33, 0.62) gamification effect was evidenced by moderate and positive grand effects sizes (ES). Gamification effects were higher with adults in higher education (ES = 0.95) than K-12 students (ES = 0.92). Brief interventions delivered in days or less than 1 week were significantly more effective (ES = 1.57) than interventions lasting up to 20 weeks (ES = 0.30). Interventions incorporating gamification elements across years (ES = −0.20) was adversely associated with behavioral change. Conclusions: Findings suggest that short-term over longer-term gamified interventions might be a promising way to initiate changes in learner’s behaviors and improve learning outcome.

scholarly journals Are K–12 Learners Motivated in Physical Education? A Meta-Analysis

2012 ◽  
Vol 83 (1) ◽  
pp. 36-48 ◽  
Author(s):  
Senlin Chen ◽  
Ang Chen ◽  
Xihe Zhu
Keyword(s):  
Physical Education ◽  
Meta Analysis ◽  
K 12

A Meta-Analysis of Testing Mode Effects in Grade K-12 Mathematics Tests

2007 ◽  
Vol 67 (2) ◽  
pp. 219-238 ◽  
Author(s):  
Shudong Wang ◽  
Hong Jiao ◽  
Michael J. Young ◽  
Thomas Brooks ◽  
John Olson
Keyword(s):  
Meta Analysis ◽  
Mode Effects ◽  
Mathematics Tests ◽  
Testing Mode ◽  
K 12

Who networks? – A meta-analysis of networking and personality

2020 ◽  
Vol 25 (5) ◽  
pp. 461-479
Author(s):  
Hadjira Bendella ◽  
Hans-Georg Wolff
Keyword(s):  
Meta Analysis ◽  
Medium Effect ◽  
Self Monitoring ◽  
Content Type ◽  
Affective Traits ◽  
Positive Effects ◽  
Social Idea ◽  
Medium Effect Size ◽  
External Networking ◽  
Behavioral Domains

PurposeNetworking refers to goal-directed behaviors focused on building and cultivating informal relationships to obtain career-related resources. According to Gibson et al.'s (2014) model, personality traits represent prominent and important antecedents of networking. This study seeks to provide robust evidence on relationships between personality and networking by summarizing prior research using meta-analytical tools.Design/methodology/approachThe authors classify linking attributes between networking and personality into social, idea-related, task-related and affective behavioral domains and additionally include three compound traits that relate to several domains. They investigate two potential moderators: internal vs. external networking and prominent networking measures. Their comprehensive literature search identified 41 studies with 46 independent samples.FindingsThe authors find that social, idea-related and task-related traits have positive relationships with networking of medium effect size, whereas affective traits exhibit small but significantly positive effects. The compound trait of proactive personality appears to be the best predictor of networking. Moderator analyses indicate that there were hardly any differences concerning internal and external networking and also prominent measures.Originality/valueThe present study goes beyond narrative reviews contributing the first quantitative summary of these relationships. It identifies four behavioral domains that represent characteristics relevant to networking. The findings largely corroborate, but at times correct, narrative reviews on dispositional antecedents of networking. The authors highlight the importance of compound traits that have yet been overlooked by narrative reviews (e.g. self-monitoring).

scholarly journals Deep Brain Stimulation Is Effective for Treatment-Resistant Depression: A Meta-Analysis and Meta-Regression

2020 ◽  
Vol 9 (9) ◽  
pp. 2796
Author(s):  
Frederick L. Hitti ◽  
Andrew I. Yang ◽  
Mario A. Cristancho ◽  
Gordon H. Baltuch
Keyword(s):  
Deep Brain Stimulation ◽  
Brain Stimulation ◽  
Meta Analysis ◽  
Treatment Resistant Depression ◽  
Treatment Resistant ◽  
Significant Difference ◽  
Resistant Depression ◽  
Meta Regression ◽  
K 12 ◽  
Deep Brain

Major depressive disorder (MDD) is a leading cause of disability and a significant cause of mortality worldwide. Approximately 30–40% of patients fail to achieve clinical remission with available pharmacological treatments, a clinical course termed treatment-resistant depression (TRD). Numerous studies have investigated deep brain stimulation (DBS) as a therapy for TRD. We performed a meta-analysis to determine efficacy and a meta-regression to compare stimulation targets. We identified and screened 1397 studies. We included 125 citations in the qualitative review and considered 26 for quantitative analysis. Only blinded studies that compared active DBS to sham stimulation (k = 12) were included in the meta-analysis. The random-effects model supported the efficacy of DBS for TRD (standardized mean difference = −0.75, <0 favors active stimulation; p = 0.0001). The meta-regression did not demonstrate a statistically significant difference between stimulation targets (p = 0.45). While enthusiasm for DBS treatment of TRD has been tempered by recent randomized trials, this meta-analysis reveals a significant effect of DBS for the treatment of TRD. Additionally, the majority of trials have demonstrated the safety and efficacy of DBS for this indication. Further trials are required to determine the optimal stimulation parameters and patient populations for which DBS would be effective. Particular attention to factors including electrode placement technique, patient selection, and long-term follow-up is essential for future trial design.

Socioeconomic Status and Academic Outcomes in Developing Countries: A Meta-Analysis

2019 ◽  
Vol 89 (6) ◽  
pp. 875-916 ◽  
Author(s):  
Sung won Kim ◽  
Hyunsun Cho ◽  
Lois Y. Kim
Keyword(s):  
Socioeconomic Status ◽  
Developing Countries ◽  
Academic Outcomes ◽  
Meta Analysis ◽  
Empirical Studies ◽  
Developed Countries ◽  
Industrialized Countries ◽  
And Gender ◽  
Meta Analyses ◽  
K 12

Despite the multiple meta-analyses documenting the association between socioeconomic status (SES) and achievement, none have examined this question outside of English-speaking industrialized countries. This study is the first meta-analytic effort, to the best of our knowledge, to focus on developing countries. Based on 49 empirical studies representing 38 countries, and a sample of 2,828,216 school-age students (grades K–12) published between 1990 and 2017, we found an overall weak relation between SES and academic outcomes. Results for attainment outcomes were stronger than achievement outcomes, and the effect size was stronger in more economically developed countries. The SES-academic outcome relation was further moderated by grade level and gender. There were no differences in the strength of the relation by specific SES measures of income/consumption, education, and wealth/home resources. Our results provide evidence that educational inequalities are wider in higher income countries, creating a serious challenge for developing countries as they expand school access.

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