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Bin Tan; Hao-Yue Jin; Maria Cutumisu – Computer Science Education, 2024
Background and Context: Computational thinking (CT) has been increasingly added to K-12 curricula, prompting teachers to grade more and more CT artifacts. This has led to a rise in automated CT assessment tools. Objective: This study examines the scope and characteristics of publications that use machine learning (ML) approaches to assess…
Descriptors: Computation, Thinking Skills, Artificial Intelligence, Student Evaluation
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Nicole D. Martin; Stephanie N. Baker; Madeline Haynes; Jayce R. Warner – Computer Science Education, 2024
Background and Context: As computer science (CS) education expands and the need for well-prepared CS teachers grows, understanding what motivates teachers to teach CS can help address challenges to recruiting, preparing, and retaining teachers. Objective: The goal of this work was to develop and validate a scale that measures teachers' motivation…
Descriptors: Computer Science Education, Teacher Motivation, Measurement Techniques, Construct Validity
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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
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Gane, Brian D.; Israel, Maya; Elagha, Noor; Yan, Wei; Luo, Feiya; Pellegrino, James W. – Computer Science Education, 2021
Background & Context: We describe the rationale, design, and initial validation of computational thinking (CT) assessments to pair with curricular lessons that integrate fractions and CT. Objective: We used cognitive models of CT (learning trajectories; LTs) to design assessments and obtained evidence to support a validity argument. Method: We…
Descriptors: Test Construction, Test Validity, Evaluation Methods, Student Evaluation
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Guenaga, Mariluz; Eguíluz, Andoni; Garaizar, Pablo; Gibaja, Juanjo – Computer Science Education, 2021
Background and Context: Despite many initiatives to develop Computational Thinking (CT), not much is known about how early programmers develop CT and how we can assess their learning. Objective: Determine if the analysis of students' interactions with an online platform allows understanding the development of CT, how we can convert data collected…
Descriptors: Computation, Thinking Skills, Skill Development, Cognitive Tests
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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