Publication Date
In 2025 | 0 |
Since 2024 | 1 |
Since 2021 (last 5 years) | 3 |
Since 2016 (last 10 years) | 5 |
Since 2006 (last 20 years) | 5 |
Descriptor
Source
Teaching of Psychology | 2 |
International Educational… | 1 |
International Journal of… | 1 |
Journal of Educational… | 1 |
Journal of Statistics and… | 1 |
Practical Assessment,… | 1 |
Author
Goldstein, Miriam D. | 2 |
Adams, Bryan | 1 |
Atar, Hakan Yavuz | 1 |
Baller, Daniel | 1 |
Cummiskey, Kevin | 1 |
Esther S. Yao | 1 |
Jonas, Bryan | 1 |
Joseph, Anny-Claude | 1 |
Kane Meissel | 1 |
Lin, Guan-Yu | 1 |
Reilly, Joseph M. | 1 |
More ▼ |
Publication Type
Journal Articles | 6 |
Reports - Descriptive | 4 |
Reports - Research | 3 |
Speeches/Meeting Papers | 1 |
Education Level
Higher Education | 3 |
Postsecondary Education | 3 |
Audience
Practitioners | 2 |
Teachers | 2 |
Location
Taiwan | 1 |
Laws, Policies, & Programs
Assessments and Surveys
Motivated Strategies for… | 1 |
What Works Clearinghouse Rating
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
Saatcioglu, Fatima Munevver; Atar, Hakan Yavuz – International Journal of Assessment Tools in Education, 2022
This study aims to examine the effects of mixture item response theory (IRT) models on item parameter estimation and classification accuracy under different conditions. The manipulated variables of the simulation study are set as mixture IRT models (Rasch, 2PL, 3PL); sample size (600, 1000); the number of items (10, 30); the number of latent…
Descriptors: Accuracy, Classification, Item Response Theory, Programming Languages
Adams, Bryan; Baller, Daniel; Jonas, Bryan; Joseph, Anny-Claude; Cummiskey, Kevin – Journal of Statistics and Data Science Education, 2021
Since the publishing of Nolan and Temple Lang's "Computing in the Statistics Curriculum" in 2010, the American Statistical Association issued new recommendations in the revised GAISE college report. To reflect modern practice and technologies, they emphasize giving students experience with multivariable thinking. Students develop…
Descriptors: Multivariate Analysis, Statistics Education, Teaching Methods, Thinking Skills
Reilly, Joseph M.; Schneider, Bertrand – International Educational Data Mining Society, 2019
Collaborative problem solving in computer-supported environments is of critical importance to the modern workforce. Coworkers or collaborators must be able to co-create and navigate a shared problem space using discourse and non-verbal cues. Analyzing this discourse can give insights into how consensus is reached and can estimate the depth of…
Descriptors: Problem Solving, Discourse Analysis, Cooperative Learning, Computer Assisted Instruction
Lin, Guan-Yu – Journal of Educational Computing Research, 2016
This study has two central purposes: First, it examines not only the roles of gender and persistence in undergraduate computing majors' learning self-efficacy, computer self-efficacy, and programming self-efficacy but also Bandura's hypothesized sources of self-efficacy; second, it examines the influence of sources of efficacy on the three…
Descriptors: Sex Role, Persistence, Self Efficacy, Beliefs

Goldstein, Miriam D.; Strube, Michael J. – Teaching of Psychology, 1995
Describes two QuickBASIC programs that provide students direct experience with interpreting correlation scatter-plots. Maintains that the programs can be used in classroom exercises to highlight factors that influence the size of a Pearson correlation coefficient. (CFR)
Descriptors: Computer Software Development, Computer Uses in Education, Correlation, Data Analysis

Strube, Michael; Goldstein, Miriam D. – Teaching of Psychology, 1995
Describes a QuickBASIC program for demonstrating the differences between main effects and interactions in factorial designs. The program can be used in conjunction with a traditional lecture to improve student understanding and develop skills in recognizing main effects and interactions from graphic displays. (CFR)
Descriptors: Computer Software Development, Computer Uses in Education, Correlation, Data Analysis