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Xiao Liu; Zhiyong Zhang; Lijuan Wang – Grantee Submission, 2024
In psychology, researchers are often interested in testing hypotheses about mediation, such as testing the presence of a mediation effect of a treatment (e.g., intervention assignment) on an outcome via a mediator. An increasingly popular approach to testing hypotheses is the Bayesian testing approach with Bayes factors (BFs). Despite the growing…
Descriptors: Sample Size, Bayesian Statistics, Programming Languages, Simulation
Tan, Teck Kiang – Practical Assessment, Research & Evaluation, 2022
Power analysis based on the analytical t-test is an important aspect of a research study to determine the sample size required to detect the effect for the comparison of two means. The current paper presents a reader-friendly procedure for carrying out the t-test power analysis using the various R add-on packages. While there is a growing of R…
Descriptors: Programming Languages, Sample Size, Bayesian Statistics, Intervention
Kane Meissel; Esther S. Yao – Practical Assessment, Research & Evaluation, 2024
Effect sizes are important because they are an accessible way to indicate the practical importance of observed associations or differences. Standardized mean difference (SMD) effect sizes, such as Cohen's d, are widely used in education and the social sciences -- in part because they are relatively easy to calculate. However, SMD effect sizes…
Descriptors: Computer Software, Programming Languages, Effect Size, Correlation
Manuel T. Rein; Jeroen K. Vermunt; Kim De Roover; Leonie V. D. E. Vogelsmeier – Structural Equation Modeling: A Multidisciplinary Journal, 2025
Researchers often study dynamic processes of latent variables in everyday life, such as the interplay of positive and negative affect over time. An intuitive approach is to first estimate the measurement model of the latent variables, then compute factor scores, and finally use these factor scores as observed scores in vector autoregressive…
Descriptors: Measurement Techniques, Factor Analysis, Scores, Validity
Tahereh Firoozi; Okan Bulut; Mark J. Gierl – International Journal of Assessment Tools in Education, 2023
The proliferation of large language models represents a paradigm shift in the landscape of automated essay scoring (AES) systems, fundamentally elevating their accuracy and efficacy. This study presents an extensive examination of large language models, with a particular emphasis on the transformative influence of transformer-based models, such as…
Descriptors: Turkish, Writing Evaluation, Essays, Accuracy
Merkle, Edgar C.; Fitzsimmons, Ellen; Uanhoro, James; Goodrich, Ben – Grantee Submission, 2021
Structural equation models comprise a large class of popular statistical models, including factor analysis models, certain mixed models, and extensions thereof. Model estimation is complicated by the fact that we typically have multiple interdependent response variables and multiple latent variables (which may also be called random effects or…
Descriptors: Bayesian Statistics, Structural Equation Models, Psychometrics, Factor Analysis
Asmaa Bengueddach; Djamila Hamdadou – International Society for Technology, Education, and Science, 2024
The COVID-19 pandemic, an unprecedented global health crisis, has not only significantly impacted public health but has also caused substantial disruptions to conventional education systems. In response to these challenges, our institution has undertaken innovative measures within the realm of education. A pivotal aspect of our response involves…
Descriptors: Personal Autonomy, Online Courses, Educational Change, Coding
Nikola M. Luburic; Luka Z. Doric; Jelena J. Slivka; Dragan Lj. Vidakovic; Katarina-Glorija G. Grujic; Aleksandar D. Kovacevic; Simona B. Prokic – IEEE Transactions on Learning Technologies, 2025
Software engineers are tasked with writing functionally correct code of high quality. Maintainability is a crucial code quality attribute that determines the ease of analyzing, modifying, reusing, and testing a software component. This quality attribute significantly affects the software's lifetime cost, contributing to developer productivity and…
Descriptors: Intelligent Tutoring Systems, Coding, Computer Software, Technical Occupations
Metcalf, Shari J.; Reilly, Joseph M.; Jeon, Soobin; Wang, Annie; Pyers, Allyson; Brennan, Karen; Dede, Chris – Computer Science Education, 2021
Background and Context: This study looks at computational thinking (CT) assessment of programming artifacts within the context of CT integrated with science education through computational modeling. Objective: The goal is to explore methodologies for assessment of student-constructed computational models through two lenses: functionality and…
Descriptors: Evaluation Methods, Computation, Thinking Skills, Science Education
Price, Thomas W.; Dong, Yihuan; Zhi, Rui; Paaßen, Benjamin; Lytle, Nicholas; Cateté, Veronica; Barnes, Tiffany – International Journal of Artificial Intelligence in Education, 2019
In the domain of programming, a growing number of algorithms automatically generate data-driven, next-step hints that suggest how students should edit their code to resolve errors and make progress. While these hints have the potential to improve learning if done well, few evaluations have directly assessed or compared the quality of different…
Descriptors: Comparative Analysis, Programming Languages, Data Analysis, Evaluation Methods
Picones, Gio; PaaBen, Benjamin; Koprinska, Irena; Yacef, Kalina – International Educational Data Mining Society, 2022
In this paper, we propose a novel approach to combine domain modelling and student modelling techniques in a single, automated pipeline which does not require expert knowledge and can be used to predict future student performance. Domain modelling techniques map questions to concepts and student modelling techniques generate a mastery score for a…
Descriptors: Prediction, Academic Achievement, Learning Analytics, Concept Mapping
Orr, J. Walker; Russell, Nathaniel – International Educational Data Mining Society, 2021
The assessment of program functionality can generally be accomplished with straight-forward unit tests. However, assessing the design quality of a program is a much more difficult and nuanced problem. Design quality is an important consideration since it affects the readability and maintainability of programs. Assessing design quality and giving…
Descriptors: Programming Languages, Feedback (Response), Units of Study, Computer Science Education
Finch, Holmes – Practical Assessment, Research & Evaluation, 2022
Researchers in many disciplines work with ranking data. This data type is unique in that it is often deterministic in nature (the ranks of items "k"-1 determine the rank of item "k"), and the difference in a pair of rank scores separated by "k" units is equivalent regardless of the actual values of the two ranks in…
Descriptors: Data Analysis, Statistical Inference, Models, College Faculty
Petrie, Christopher – Computer Science Education, 2022
Background and Context: Computational Thinking (CT) has been recently integrated into new and revised Digital Technologies content (DTC) in the Technology learning area of the New Zealand School Curriculum. Objective: To aid this change, this research examined how CT supports learning outcomes in both music and programming with the Sonic Pi…
Descriptors: Interdisciplinary Approach, Outcomes of Education, Computer Science Education, Programming
Beckman, Matthew D.; Çetinkaya-Rundel, Mine; Horton, Nicholas J.; Rundel, Colin W.; Sullivan, Adam J.; Tackett, Maria – Journal of Statistics and Data Science Education, 2021
A version control system records changes to a file or set of files over time so that changes can be tracked and specific versions of a file can be recalled later. As such, it is an essential element of a reproducible workflow that deserves due consideration among the learning objectives of statistics courses. This article describes experiences and…
Descriptors: Statistics Education, Data Analysis, Teaching Methods, Graduate Students
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