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Maya B. Mathur – Research Synthesis Methods, 2024
Meta-analyses can be compromised by studies' internal biases (e.g., confounding in nonrandomized studies) as well as publication bias. These biases often operate nonadditively: publication bias that favors significant, positive results selects indirectly for studies with more internal bias. We propose sensitivity analyses that address two…
Descriptors: Meta Analysis, Attribution Theory, Publications, Bias
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Jorge N. Tendeiro; Rink Hoekstra; Tsz Keung Wong; Henk A. L. Kiers – Teaching Statistics: An International Journal for Teachers, 2025
Most researchers receive formal training in frequentist statistics during their undergraduate studies. In particular, hypothesis testing is usually rooted on the null hypothesis significance testing paradigm and its p-value. Null hypothesis Bayesian testing and its so-called Bayes factor are now becoming increasingly popular. Although the Bayes…
Descriptors: Statistics Education, Teaching Methods, Programming Languages, Bayesian Statistics
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Ken Frank; Guan Saw; Qinyun Lin; Ran Xu; Joshua Rosenberg; Spiro Maroulis; Bret Staudt Willet – Grantee Submission, 2025
This is a practical guide for applying the Impact Threshold for a Confounding Variable and the Robustness of Inference to Replacement using the konfound packages in Stata and R as well as the R-shiny app. It includes motivation worked examples, and tutorials.
Descriptors: Robustness (Statistics), Statistical Inference, Programming Languages, Computer Software
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Maya B. Mathur – Research Synthesis Methods, 2024
As traditionally conceived, publication bias arises from selection operating on a collection of individually unbiased estimates. A canonical form of such selection across studies (SAS) is the preferential publication of affirmative studies (i.e., those with significant, positive estimates) versus nonaffirmative studies (i.e., those with…
Descriptors: Meta Analysis, Research Reports, Research Methodology, Research Problems
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Muradoglu, Melis; Cimpian, Joseph R.; Cimpian, Andrei – Journal of Cognition and Development, 2023
Mixed-effects models are an analytic technique for modeling repeated measurement or nested data. This paper explains the logic of mixed-effects modeling and describes two examples of mixed-effects analyses using R. The intended audience of the paper is psychologists who specialize in cognitive development research. Therefore, the concepts and…
Descriptors: Cognitive Development, Models, Programming Languages, Psychologists
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Temesgen Samuel; Hsiu-Ling Chen; Abebayehu Yohannes – Journal of Computer Assisted Learning, 2025
Background: As highly interactive hands-on learning tools, robots can inspire new generations of mathematics students. However, to date, no comprehensive systematic reviews have been conducted on robot-assisted mathematics education from K-12 through higher education. Hence, it is important to explore the research evidence of robot-assisted…
Descriptors: Mathematics Instruction, Robotics, Technology Uses in Education, Elementary Secondary Education
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Bougioukas, Konstantinos I.; Diakonidis, Theodoros; Mavromanoli, Anna C.; Haidich, Anna-Bettina – Research Synthesis Methods, 2023
An overview of reviews aims to collect, assess, and synthesize evidence from multiple systematic reviews (SRs) on a specific topic using rigorous and reproducible methods. An important methodological challenge in conducting an overview of reviews is the management of overlapping data due to the inclusion of the same primary studies in SRs. We…
Descriptors: Programming Languages, Open Source Technology, Evaluation Methods, Evidence
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Seckin-Kapucu, Munise – Journal of Education in Science, Environment and Health, 2023
This study aims to examine the methodological trends and findings in studies on robotic coding in science education published between 2015-2022 comprehensively and holistically. For this purpose, the articles related to the subject were systematically reviewed. In addition, web of Science and SCOPUS databases were scanned for keywords related to…
Descriptors: Robotics, Coding, Programming, Research Methodology
Shan Jiang – ProQuest LLC, 2023
Piecewise latent growth modeling (PLGM) is a class of longitudinal models using a structural equation modeling framework to describe stage-like, discontinuous change of individuals over time. PLGM breaks the overall time window into non-overlapped segments where separate functions can be fitted to represent differential growth patterns for each…
Descriptors: Programming Languages, Structural Equation Models, Social Sciences, Research Methodology
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Konstantinos I. Bougioukas; Paschalis Karakasis; Konstantinos Pamporis; Emmanouil Bouras; Anna-Bettina Haidich – Research Synthesis Methods, 2024
Systematic reviews (SRs) have an important role in the healthcare decision-making practice. Assessing the overall confidence in the results of SRs using quality assessment tools, such as "A MeaSurement Tool to Assess Systematic Reviews 2" (AMSTAR 2), is crucial since not all SRs are conducted using the most rigorous methods. In this…
Descriptors: Programming Languages, Research Methodology, Decision Making, Medical Research
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Dennis Tay – Journal of Statistics and Data Science Education, 2024
Data analytics and programming skills are increasingly important in the humanities, especially in disciplines like linguistics due to the rapid growth of natural language processing (NLP) technologies. However, attitudes and perceptions of students as novice learners, and the attendant pedagogical implications, remain underexplored. This article…
Descriptors: Data Analysis, Programming, Linguistics, Graduate Students
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Thakur, Khusbu; Kumar, Vinit – New Review of Academic Librarianship, 2022
A vast amount of published scholarly literature is generated every day. Today, it is one of the biggest challenges for organisations to extract knowledge embedded in published scholarly literature for business and research applications. Application of text mining is gaining popularity among researchers and applications are growing exponentially in…
Descriptors: Information Retrieval, Data Analysis, Research Methodology, Trend Analysis
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Rovshenov, Atajan; Sarsar, Firat – Journal of Educational Technology and Online Learning, 2023
This study examines the methodological dimensions of programming education articles published in educational sciences journals indexed in SSCI by exploring their general trends. To do this, 162 articles published between January 2012 and February 2020 in 30 international journals indexed in SSCI were analyzed with a systematic review method using…
Descriptors: Computer Science Education, Programming, Educational Trends, Trend Analysis
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Berssanette, Joao Henrique; de Francisco, Antonio Carlos – IEEE Transactions on Education, 2022
Contribution: This article features a systematic literature review with the objective of presenting a study that reflects the current scenario of research on the cognitive load theory (CLT) in the domain of teaching and learning computer programming. Background: Computer programming is a highly cognitive skill, requiring mastering multiple…
Descriptors: Cognitive Ability, Programming, Computer Science Education, Mastery Learning
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Özyurt, Hacer; Özyurt, Özcan – Journal of Pedagogical Research, 2020
This study aims to examine the effects of Visual Programming course conducting in accordance with design-based research on students' learning experiences. The study was conducted in the fall semester in 2017-2018 at Software Engineering Department in Technology Faculty of a university in the north of Turkey. The sample of the study consists of 12…
Descriptors: Computer Science Education, Programming, Design, Learning Experience
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