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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
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
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
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
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
Margulieux, Lauren; Ketenci, Tuba Ayer; Decker, Adrienne – Computer Science Education, 2019
Background and context: The variables that researchers measure and how they measure them are central in any area of research, including computing education. Which research questions can be asked and how they are answered depends on measurement. Objective: To summarize the commonly used variables and measurements in computing education and to…
Descriptors: Measurement Techniques, Standards, Evaluation Methods, Computer Science Education
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
Burgueño, Loli; Vallecillo, Antonio; Gogolla, Martin – Computer Science Education, 2018
Models are expanding their use for many different purposes in the field of software engineering and, due to their importance, universities have started incorporating modeling courses into their programs. Being a relatively new discipline, teaching modeling concepts brings in new challenges. Our contribution in this paper is threefold. First, we…
Descriptors: Engineering Education, Programming, Computer Software, Teaching Methods
Hamouda, Sally; Shaffer, Clifford A. – Computer Science Education, 2016
In this paper, we study the relationship between the use of "crib sheets" or "cheat sheets" and performance on in-class exams. Our extensive survey of the existing literature shows that it is not decisive on the questions of when or whether crib sheets actually help students to either perform better on an exam or better learn…
Descriptors: Cheating, Documentation, Data, Evaluation Methods
Nutbrown, Stephen; Higgins, Colin – Computer Science Education, 2016
This article explores the suitability of static analysis techniques based on the abstract syntax tree (AST) for the automated assessment of early/mid degree level programming. Focus is on fairness, timeliness and consistency of grades and feedback. Following investigation into manual marking practises, including a survey of markers, the assessment…
Descriptors: Programming, Grading, Evaluation Methods, Feedback (Response)