Journal of Research on Educational Effectiveness最新文献_第3页

Quantifying and Predicting Variation in the Medium-Term Effects of an Oversubscribed Prekindergarten Program 量化和预测超额学前班计划的中期效应变化

IF 1.8 4区教育学

Journal of Research on Educational Effectiveness Pub Date : 2024-03-13 DOI: 10.1080/19345747.2023.2286280

Rebecca Unterman, Christina Weiland

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Mentors Matter Recruitment Replication & Extension: Investigating Effects Across Implementation Years 导师很重要招募、复制和推广：跨实施年效果调查

IF 1.8 4区教育学

Journal of Research on Educational Effectiveness Pub Date : 2024-01-12 DOI: 10.1080/19345747.2023.2287615

Matthew Ronfeldt, Emanuele Bardelli, Matthew Truwit, Kevin Schaaf, Julie Baker

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Statistical Power Analysis for Univariate Meta-Analysis: A Three-Level Model 单变量元分析的统计功率分析：三层模型

IF 1.8 4区教育学

Journal of Research on Educational Effectiveness Pub Date : 2024-01-04 DOI: 10.1080/19345747.2023.2290544

Bixi Zhang, Spyros Konstantopoulos

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The Impacts of a Standards-Based Grading System Emphasizing Formative Assessment, Feedback, and Re-Assessment: A Mixed Methods, Cluster Randomized Control Trial in Ninth Grade Mathematics Classrooms 强调形成性评价、反馈和再评价的基于标准的评分系统的影响：九年级数学课堂的混合方法、分组随机对照试验

IF 1.8 4区教育学

Journal of Research on Educational Effectiveness Pub Date : 2024-01-03 DOI: 10.1080/19345747.2023.2287594

Steven L. Kramer, Michael A. Posner, Alexander S. Browman, Nancy R. Lawrence, Jennifer Roem, Kathleen Krier

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Reading Aloud to Children, Social Inequalities and Vocabulary Development: Evidence from a Randomized Controlled Trial 儿童朗读、社会不平等和词汇发展：来自随机对照试验的证据

IF 1.8 4区教育学

Journal of Research on Educational Effectiveness Pub Date : 2024-01-03 DOI: 10.1080/19345747.2023.2283475

Carlo Barone, Denis Fougère, Karine Martel

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Intervention Effect or Measurement Artifact? Using Invariance Models to Reveal Response-Shift Bias in Experimental Studies 干预效应还是测量假象？使用不变量模型揭示实验研究中的反应偏移

IF 1.8 4区教育学

Journal of Research on Educational Effectiveness Pub Date : 2024-01-03 DOI: 10.1080/19345747.2023.2284768

Margarita Olivera-Aguilar, Samuel H. Rikoon

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Redefining Populations of Inference for Generalizations from Small Studies 重新定义从小型研究中归纳出的推论群体

IF 1.8 4区教育学

Journal of Research on Educational Effectiveness Pub Date : 2024-01-03 DOI: 10.1080/19345747.2023.2290546

Wendy Chan, Jimin Oh, Katherine J. Wilson

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Estimating Treatment Effects with the Explanatory Item Response Model 用解释性项目反应模型估算治疗效果

IF 1.8 4区教育学

Journal of Research on Educational Effectiveness Pub Date : 2024-01-03 DOI: 10.1080/19345747.2023.2287601

Joshua B. Gilbert

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Student Behavior Ratings and Response to Tier 1 Reading Intervention: Which Students Do Not Benefit? 学生行为评分和对一级阅读干预的反应:哪些学生没有受益?

IF 1.7 4区教育学

Journal of Research on Educational Effectiveness Pub Date : 2024-01-01 Epub Date: 2023-04-10 DOI: 10.1080/19345747.2023.2194894

Wilhelmina van Dijk, Christopher Schatschneider, Stephanie Al Otaiba, Sara A Hart

{"title":"Student Behavior Ratings and Response to Tier 1 Reading Intervention: Which Students Do Not Benefit?","authors":"Wilhelmina van Dijk, Christopher Schatschneider, Stephanie Al Otaiba, Sara A Hart","doi":"10.1080/19345747.2023.2194894","DOIUrl":"10.1080/19345747.2023.2194894","url":null,"abstract":"Core reading instruction and interventions have differential effects based on student characteristics such as cognitive ability and pre-intervention skill level. Evidence for differential effect based on affective characteristics is scant and ambiguous; however, students with problem behavior are more often non-responsive to core reading instruction and intensive reading interventions. In this study, we estimated the range of students' behavior ratings in which a core reading instruction intervention was effective using a data set including 3,024 students in K-3. Data came from seven independent studies evaluating the Individualized Student Instruction (ISI) Tier 1 reading intervention and were pooled using integrative data analysis. We estimated Johnson-Neyman intervals of student behavior ratings that showed a treatment effect both at the within and between classroom level. ISI was effective in improving reading scores (b=0.51, p=.020, d = 0.08). However, students with very low or very high behavior ratings did not benefit from the approaches (range of behavior rating factor scores: -0.95 - 2.87). At the classroom level, students in classrooms with a higher average of problem behaviors did not benefit from ISI (average classroom behavior rating factor score: 0.05 - 4.25). Results suggest differentiating instruction alone is not enough for students with behavior problems to grow in reading ability.","PeriodicalId":47260,"journal":{"name":"Journal of Research on Educational Effectiveness","volume":null,"pages":null},"PeriodicalIF":1.7,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11309152/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45518336","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Using a Multi-Site RCT to Predict Impacts for a Single Site: Do Better Data and Methods Yield More Accurate Predictions? 使用多站点RCT预测单个站点的影响:更好的数据和方法能产生更准确的预测吗?

IF 1.8 4区教育学

Journal of Research on Educational Effectiveness Pub Date : 2024-01-01 Epub Date: 2023-04-13 DOI: 10.1080/19345747.2023.2180464

Robert B Olsen, Larry L Orr, Stephen H Bell, Elizabeth Petraglia, Elena Badillo-Goicoechea, Atsushi Miyaoka, Elizabeth A Stuart

{"title":"Using a Multi-Site RCT to Predict Impacts for a Single Site: Do Better Data and Methods Yield More Accurate Predictions?","authors":"Robert B Olsen, Larry L Orr, Stephen H Bell, Elizabeth Petraglia, Elena Badillo-Goicoechea, Atsushi Miyaoka, Elizabeth A Stuart","doi":"10.1080/19345747.2023.2180464","DOIUrl":"10.1080/19345747.2023.2180464","url":null,"abstract":"Multi-site randomized controlled trials (RCTs) provide unbiased estimates of the average impact in the study sample. However, their ability to accurately predict the impact for individual sites outside the study sample, to inform local policy decisions, is largely unknown. To extend prior research on this question, we analyzed six multi-site RCTs and tested modern prediction methods-lasso regression and Bayesian Additive Regression Trees (BART)-using a wide range of moderator variables. The main study findings are that: (1) all of the methods yielded accurate impact predictions when the variation in impacts across sites was close to zero (as expected); (2) none of the methods yielded accurate impact predictions when the variation in impacts across sites was substantial; and (3) BART typically produced \"less inaccurate\" predictions than lasso regression or than the Sample Average Treatment Effect. These results raise concerns that when the impact of an intervention varies considerably across sites, statistical modelling using the data commonly collected by multi-site RCTs will be insufficient to explain the variation in impacts across sites and accurately predict impacts for individual sites.","PeriodicalId":47260,"journal":{"name":"Journal of Research on Educational Effectiveness","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10914338/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42133979","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0