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Showing 1 to 15 of 729 results Save | Export
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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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Leah Bidlake; Eric Aubanel; Daniel Voyer – ACM Transactions on Computing Education, 2025
Research on mental model representations developed by programmers during parallel program comprehension is important for informing and advancing teaching methods including model-based learning and visualizations. The goals of the research presented here were to determine: how the mental models of programmers change and develop as they learn…
Descriptors: Schemata (Cognition), Programming, Computer Science Education, Coding
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Rubén Buitrago; Jesús Salinas; Oscar Boude – Knowledge Management & E-Learning, 2024
Design patterns for learning are about articulating, testing and sharing the principles of problem solving in the educational context. In this way, multiple patterns are developed to solve common problems, described in various pattern language formats. Therefore, this work is about characterizing and establishing functional relationships between…
Descriptors: Delphi Technique, Programming Languages, Programming, Computer Software
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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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Ainhoa Berciano; Astrid Cuida; María-Luisa Novo – Education and Information Technologies, 2025
In the last two decades, computational thinking has gained wide relevance in international educational systems. The inclusion of this new type of thinking poses educational challenges with some underlying research questions that need to be answered to meet these challenges with quality. Thus, this study focuses on analyzing the difficulties that…
Descriptors: Coding, Translation, Programming Languages, Sequential Approach
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David Shilane; Nicole Di Crecchio; Nicole L. Lorenzetti – Teaching Statistics: An International Journal for Teachers, 2024
Educational curricula in data analysis are increasingly fundamental to statistics, data science, and a wide range of disciplines. The educational literature comparing coding syntaxes for instruction in data analysis recommends utilizing a simple syntax for introductory coursework. However, there is limited prior work to assess the pedagogical…
Descriptors: Programming, Data Science, Programming Languages, Coding
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Davi Bernardo Silva; Deborah Ribeiro Carvalho; Carlos N. Silla – IEEE Transactions on Learning Technologies, 2024
Throughout a programming course, students develop various source code tasks. Using these tasks to track students' progress can provide clues to the strengths and weaknesses found in each learning topic. This practice allows the teacher to intervene in learning in the first few weeks of class and maximize student gains. However, the biggest…
Descriptors: Computation, Models, Ability Grouping, Programming
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Austin Wyman; Zhiyong Zhang – Grantee Submission, 2025
Automated detection of facial emotions has been an interesting topic for multiple decades in social and behavioral research but is only possible very recently. In this tutorial, we review three popular artificial intelligence based emotion detection programs that are accessible to R programmers: Google Cloud Vision, Amazon Rekognition, and…
Descriptors: Artificial Intelligence, Algorithms, Computer Software, Identification
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Alex Yue Feng Zhu – British Journal of Educational Technology, 2024
Research has shown that even though standardized financial education has gained prevalence to promote financial literacy over the past decade, it has had little effect on personal financial planning. The present study used a randomized control trial to examine the effectiveness of a Python-based personalized financial projection on young working…
Descriptors: Financial Education, Programming Languages, Financial Literacy, Money Management
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Lucy D'Agostino McGowan; Travis Gerke; Malcolm Barrett – Journal of Statistics and Data Science Education, 2024
This article introduces a collection of four datasets, similar to Anscombe's quartet, that aim to highlight the challenges involved when estimating causal effects. Each of the four datasets is generated based on a distinct causal mechanism: the first involves a collider, the second involves a confounder, the third involves a mediator, and the…
Descriptors: Statistics Education, Programming Languages, Statistical Inference, Causal Models
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Elena Novak; Chia-Ling Kuo; Janet Lynne Tassell; Grace Morris – TechTrends: Linking Research and Practice to Improve Learning, 2024
Recently, creativity has been acknowledged for its importance in improving computer science learning and attitudes. However, very little is known about how to integrate creativity in preservice teacher computing education. Toward this end, we developed a creativity-enhancement intervention in an online Creative Computing instructional module to…
Descriptors: Preservice Teachers, Elementary School Teachers, Creativity, Intervention
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Suppanut Sriutaisuk; Yu Liu; Seungwon Chung; Hanjoe Kim; Fei Gu – Educational and Psychological Measurement, 2025
The multiple imputation two-stage (MI2S) approach holds promise for evaluating the model fit of structural equation models for ordinal variables with multiply imputed data. However, previous studies only examined the performance of MI2S-based residual-based test statistics. This study extends previous research by examining the performance of two…
Descriptors: Structural Equation Models, Error of Measurement, Programming Languages, Goodness of Fit
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Andrea Maffia; Carola Manolino; Elisa Miragliotta – Educational Studies in Mathematics, 2025
Research literature about visually impaired students' approach to mathematics is still very scarce, especially in the case of algebra, even though mathematical content is becoming increasingly accessible thanks to assistive technologies. This paper presents a case study aimed at describing a blind subject's process of algebraic symbol manipulation…
Descriptors: Algebra, Blindness, Mathematics Education, Symbols (Mathematics)
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Mark W. Isken – INFORMS Transactions on Education, 2025
A staple of many spreadsheet-based management science courses is the use of Excel for activities such as model building, sensitivity analysis, goal seeking, and Monte-Carlo simulation. What might those things look like if carried out using Python? We describe a teaching module in which Python is used to do typical Excel-based modeling and…
Descriptors: Spreadsheets, Models, Programming Languages, Monte Carlo Methods
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Niloofar Mansoor; Cole S. Peterson; Michael D. Dodd; Bonita Sharif – ACM Transactions on Computing Education, 2024
Background and Context: Understanding how a student programmer solves different task types in different programming languages is essential to understanding how we can further improve teaching tools to support students to be industry-ready when they graduate. It also provides insight into students' thought processes in different task types and…
Descriptors: Biofeedback, Eye Movements, Computer Science Education, Programming Languages
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