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Daniele Traversaro; Giorgio Delzanno; Giovanna Guerrini – Informatics in Education, 2024
Concurrency is a complex to learn topic that is becoming more and more relevant, such that many undergraduate Computer Science curricula are introducing it in introductory programming courses. This paper investigates the combined use of Sonic Pi and Team-Based Learning to mitigate the difficulties in early exposure to concurrency. Sonic Pi, a…
Descriptors: Misconceptions, Programming Languages, Computer Science Education, Undergraduate Students
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
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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
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Dart, Evan H.; Radley, Keith C.; Briesch, Amy M.; Furlow, Christopher M.; Cavell, Hannah J.; Briesch, Amy M. – Behavioral Disorders, 2016
Two studies investigated the accuracy of eight different interval-based group observation methods that are commonly used to assess the effects of classwide interventions. In Study 1, a Microsoft Visual Basic program was created to simulate a large set of observational data. Binary data were randomly generated at the student level to represent…
Descriptors: Observation, Intervention, Simulation, Statistical Analysis
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Kazakoff, Elizabeth R.; Sullivan, Amanda; Bers, Marina U. – Early Childhood Education Journal, 2013
This paper examines the impact of programming robots on sequencing ability during a 1-week intensive robotics workshop at an early childhood STEM magnet school in the Harlem area of New York City. Children participated in computer programming activities using a developmentally appropriate tangible programming language CHERP, specifically designed…
Descriptors: Children, Robotics, Programming Languages, Control Groups