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Showing 16 to 21 of 21 results Save | Export
Simulation-Based Sensitivity Analysis for Causal Mediation Studies
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Xu Qin; Fan Yang – Grantee Submission, 2022
Causal inference regarding a hypothesized mediation mechanism relies on the assumptions that there are no omitted pretreatment confounders (i.e., confounders preceding the treatment) of the treatment-mediator, treatment-outcome, and mediator-outcome relationships, and there are no posttreatment confounders (i.e., confounders affected by the…
Descriptors: Simulation, Correlation, Inferences, Attribution Theory
The Meta-Analytic Rain Cloud Plot: A New Approach to Visualizing Clearinghouse Data
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Kaitlyn G. Fitzgerald; Elizabeth Tipton – Grantee Submission, 2022
As the body of scientific evidence about effective policies and practices grows, so does the need to effectively communicate that evidence to policy-makers and practitioners. Clearinghouses have emerged to facilitate the evidence-based decision-making process for education practitioners. While the results and methods for developing and analyzing…
Descriptors: Meta Analysis, Scientific Research, Evidence Based Practice, Decision Making
Impact Study of the Coding as Another Language Curriculum: Study B
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Zhanxia Yang; Patricia Moore Shaffer; Courtney Hagan; Parastu Dubash; Marina Bers – Grantee Submission, 2023
The aim of this study was to explore how the Coding as Another Language using ScratchJr (CAL-ScratchJr) curriculum, developed by Boston College's DevTech Research Group utilizing the ScratchJr app, impacted second grade students' computational thinking, coding skills, and reading comprehension. To accomplish this, the research team randomly…
Descriptors: Coding, Programming Languages, Computer Science Education, School Districts
Stan: A Probabilistic Programming Language
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Carpenter, Bob; Gelman, Andrew; Hoffman, Matthew D.; Lee, Daniel; Goodrich, Ben; Betancourt, Michael; Brubaker, Marcus A.; Guo, Jiqiang; Li, Peter; Riddell, Allen – Grantee Submission, 2017
Stan is a probabilistic programming language for specifying statistical models. A Stan program imperatively defines a log probability function over parameters conditioned on specified data and constants. As of version 2.14.0, Stan provides full Bayesian inference for continuous-variable models through Markov chain Monte Carlo methods such as the…
Descriptors: Programming Languages, Probability, Bayesian Statistics, Monte Carlo Methods
Authoring Collaborative Intelligent Tutoring Systems
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Olsen, Jennifer K.; Belenky, Daniel M.; Aleven, Vincent; Rummel, Nikol; Sewall, Jonathan; Ringenberg, Michael – Grantee Submission, 2013
Authoring tools for Intelligent Tutoring System (ITS) have been shown to decrease the amount of time that it takes to develop an ITS. However, most of these tools currently do not extend to collaborative ITSs. In this paper, we illustrate an extension to the Cognitive Tutor Authoring Tools (CTAT) to allow for development of collaborative ITSs that…
Descriptors: Intelligent Tutoring Systems, Programming Languages, Fractions, Learning Processes
The Landscape of Computing Education in Utah
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Rich, Peter Jacob; Hu, Helen; Christensen, James; Ellsworth, Jordan – Grantee Submission, 2019
This report provides a comprehensive look at computer science (CS) education across Utah elementary, middle/jr. high, and high schools as of 2018. The Utah Expanding Computing Education Pathways (ECEP) team sent out a survey to all public schools in the state of Utah. The survey presented targeted questions depending on whether it was completed…
Descriptors: Computer Science Education, Public Schools, Teacher Attitudes, Enrollment Trends
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