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Showing 1 to 15 of 24 results Save | Export
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Guangrui Fan; Dandan Liu; Rui Zhang; Lihu Pan – International Journal of STEM Education, 2025
Purpose: This study investigates the impact of AI-assisted pair programming on undergraduate students' intrinsic motivation, programming anxiety, and performance, relative to both human-human pair programming and individual programming approaches. Methods: A quasi-experimental design was conducted over two academic years (2023-2024) with 234…
Descriptors: Artificial Intelligence, Computer Software, Technology Uses in Education, Programming
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Jorge N. Tendeiro; Rink Hoekstra; Tsz Keung Wong; Henk A. L. Kiers – Teaching Statistics: An International Journal for Teachers, 2025
Most researchers receive formal training in frequentist statistics during their undergraduate studies. In particular, hypothesis testing is usually rooted on the null hypothesis significance testing paradigm and its p-value. Null hypothesis Bayesian testing and its so-called Bayes factor are now becoming increasingly popular. Although the Bayes…
Descriptors: Statistics Education, Teaching Methods, Programming Languages, Bayesian Statistics
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Xiaoheng Yan; Gila Hanna – International Journal of Mathematical Education in Science and Technology, 2025
As new technological developments continue to change the educational landscape, it is not an exception in the area of proof and proving. This classroom note introduces the use of one of the trending proofs assistants -- the Lean theorem prover. We first provide a technical account of Lean, then exemplify Lean proofs in propositional logic, number…
Descriptors: Mathematics Instruction, Undergraduate Students, Mathematical Logic, Validity
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Eunsung Park; Jongpil Cheon – Journal of Educational Computing Research, 2025
Debugging is essential for identifying and rectifying errors in programming, yet time constraints and students' trivialization of errors often hinder progress. This study examines differences in debugging challenges and strategies among students with varying computational thinking (CT) competencies using weekly coding journals from an online…
Descriptors: Undergraduate Students, Programming, Computer Software, Troubleshooting
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Harry Barton Essel; Dimitrios Vlachopoulos; Henry Nunoo-Mensah; John Opuni Amankwa – British Journal of Educational Technology, 2025
Conversational user interfaces (CUI), including voice interfaces, which allow users to converse with computers via voice, are gaining wide popularity. VoiceBots allow users to receive a response in real-time, regardless of the communication device. VoiceBots have been explored in fields such as customer service to automate repetitive queries and…
Descriptors: Foreign Countries, Artificial Intelligence, Program Effectiveness, Undergraduate Students
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Austin Wyman; Zhiyong Zhang – Grantee Submission, 2025
Automated detection of facial emotions has been an interesting topic for multiple decades in social and behavioral research but is only possible very recently. In this tutorial, we review three popular artificial intelligence based emotion detection programs that are accessible to R programmers: Google Cloud Vision, Amazon Rekognition, and…
Descriptors: Artificial Intelligence, Algorithms, Computer Software, Identification
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Mark W. Isken – INFORMS Transactions on Education, 2025
A staple of many spreadsheet-based management science courses is the use of Excel for activities such as model building, sensitivity analysis, goal seeking, and Monte-Carlo simulation. What might those things look like if carried out using Python? We describe a teaching module in which Python is used to do typical Excel-based modeling and…
Descriptors: Spreadsheets, Models, Programming Languages, Monte Carlo Methods
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Mark Frydenberg; Anqi Xu; Jennifer Xu – Information Systems Education Journal, 2025
This study explores student perceptions of learning to code by evaluating AI-generated Python code. In an experimental exercise given to students in an introductory Python course at a business university, students wrote their own solutions to a Python program and then compared their solutions with AI-generated code. They evaluated both solutions…
Descriptors: Student Attitudes, Programming, Computer Software, Quality Assurance
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Diana Kirk; Andrew Luxton-Reilly; Ewan Tempero – ACM Transactions on Computing Education, 2025
Objectives: Code style is an important aspect of text-based programming because programs written with good style are considered easier to understand and change and so improve the maintainability of the delivered software product. However teaching code style is complicated by the existence of many style guides and standards that contain…
Descriptors: Computer Science Education, Programming, Computer Software, Teaching Methods
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Nichole Orench-Rivera; April Bednarski; Paul Craig; Austin Talbot – Journal of College Science Teaching, 2025
Advancements in computation and machine learning have revolutionized science, enabling researchers to address once insurmountable challenges. Bioinformatics, a field that heavily relies on computer-driven analysis of biological data, has greatly benefited from these developments. However, traditional bioinformatics instruction frequently lacks the…
Descriptors: Coding, Computer Science Education, Integrated Curriculum, Programming
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Ndudi Okechukwu Ezeamuzie; Mercy Noyenim Ezeamuzie – Review of Educational Research, 2025
Computer programming provides a framework for interdisciplinary learning in sciences, arts and languages. However, increasing integration of programming in K--12 shows that the block-based and text-based dichotomy of programming environments does not reflect the spectrum of their affordance. Hence, educators are confronted with a fundamental…
Descriptors: Kindergarten, Elementary Secondary Education, Computer Science Education, Programming
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Rebeckah K. Fussell; Megan Flynn; Anil Damle; Michael F. J. Fox; N. G. Holmes – Physical Review Physics Education Research, 2025
Recent advancements in large language models (LLMs) hold significant promise for improving physics education research that uses machine learning. In this study, we compare the application of various models for conducting a large-scale analysis of written text grounded in a physics education research classification problem: identifying skills in…
Descriptors: Physics, Computational Linguistics, Classification, Laboratory Experiments
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Meina Zhu – Journal of Computer Assisted Learning, 2025
Background: Computer programming learning and education play a critical role in preparing a workforce equipped with the necessary skills for diverse fields. ChatGPT and YouTube are technologies that support self-directed programming learning. Objectives: This study aims to examine the sentiments and primary topics discussed in YouTube comments…
Descriptors: Computer Science Education, Programming, Social Media, Video Technology
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Manuel T. Rein; Jeroen K. Vermunt; Kim De Roover; Leonie V. D. E. Vogelsmeier – Structural Equation Modeling: A Multidisciplinary Journal, 2025
Researchers often study dynamic processes of latent variables in everyday life, such as the interplay of positive and negative affect over time. An intuitive approach is to first estimate the measurement model of the latent variables, then compute factor scores, and finally use these factor scores as observed scores in vector autoregressive…
Descriptors: Measurement Techniques, Factor Analysis, Scores, Validity
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Gerard Dummer; Elwin Savelsbergh; Paul Drijvers – Informatics in Education, 2025
Programmed control systems are ubiquitous in the present-day world. In current educational practice, however, these systems are hardly being addressed, and little is known about children's spontaneous understandings about such systems. Therefore, we explored pupils' understandings prior to instruction in three concrete settings: a car park, an…
Descriptors: Elementary School Students, Grade 3, Grade 6, Computer Science Education
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