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Kathy A. Mills; Jen Cope; Laura Scholes; Luke Rowe – Review of Educational Research, 2025
Teaching coding and computational thinking is an emerging educational imperative, now embedded in compulsory curriculum in the United States, Finland, the UK, Germany, Belgium, the Netherlands, New Zealand, and Australia. This meta-synthesis of 49 studies critically reviews recent international research (2009-2022) of coding and computational…
Descriptors: Coding, Programming, Computation, Thinking Skills
Cindy Royal – Journalism and Mass Communication Educator, 2025
Artificial intelligence (AI) has taken the forefront in discussions of the future of media and education. Although there are valid concerns, AI has the potential to be useful in learning new skills, particularly those related to computer programming. This case study depicts the ways AI was introduced to assist in teaching coding, specifically in a…
Descriptors: Artificial Intelligence, Coding, Programming, Computer Science Education
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
Ismaila Temitayo Sanusi; Enoch Shadrack Cudjoe; Musa Adekunle Ayanwale; Bisola Adepoju – SAGE Open, 2025
The increased trend of incorporating computer programming in the basic education system across countries requires the training of new educators. However, the current effort to increase the number of teachers teaching programming is through professional development programs for computer science (CS) teachers and from other content areas. Meanwhile,…
Descriptors: Preservice Teachers, Student Attitudes, Programming, Computer Science Education
Zifeng Liu; Wanli Xing; Xinyue Jiao; Chenglu Li; Wangda Zhu – Education and Information Technologies, 2025
The ability of large language models (LLMs) to generate code has raised concerns in computer science education, as students may use tools like ChatGPT for programming assignments. While much research has focused on higher education, especially for languages like Java and Python, little attention has been given to K-12 settings, particularly for…
Descriptors: High School Students, Coding, Artificial Intelligence, Electronic Learning
Ibrahim Albluwi; Raghda Hriez; Raymond Lister – ACM Transactions on Computing Education, 2025
Explain-in-Plain-English (EiPE) questions are used by some researchers and educators to assess code reading skills. EiPE questions require students to briefly explain (in plain English) the purpose of a given piece of code, without restating what the code does line-by-line. The premise is that novices who can explain the purpose of a piece of code…
Descriptors: Questioning Techniques, Programming, Computer Science Education, Student Evaluation
Rimma Nyman; Kajsa Bråting; Cecilia Kilhamn – International Journal of Mathematical Education in Science and Technology, 2025
In the wake of the present inclusion of programming in mathematics education, which is a feature of curricular revisions in many countries, we have analysed newly inserted programming activities in mathematics textbooks. The aim was to investigate how such activities relate to and potentially affect students' opportunities to learn mathematics.…
Descriptors: Secondary School Students, Mathematics Instruction, Programming, Computer Science Education
Nilüfer Atman Uslu; Aytug Onan – Education and Information Technologies, 2025
Understanding the emotions experienced by programming students, particularly concerning gender and education level, is increasingly critical. However, only limited research has used text data to examine these differences within the context of programming education and emotions. This study aims to determine programming students' emotions and any…
Descriptors: Programming, Psychological Patterns, Student Attitudes, Secondary School Students
Javier Del Olmo-Muñoz; Alicia Jiménez Toledo; Sergio Tirado-Olivares; José Antonio González-Calero; Ramón Cózar-Gutiérrez – Informatics in Education, 2025
The assessment of computational thinking (CT) is crucial for improving pedagogical practice, identifying areas for improvement, and implementing efficient educational interventions. Despite growing interest in CT in primary education, existing assessments often focus on specific dimensions, providing a fragmented understanding. In this research, a…
Descriptors: Computation, Thinking Skills, Elementary School Students, Grade 6
Kevin Slonka; Matthew North; Neelima Bhatnagar; Anthony Serapiglia – Information Systems Education Journal, 2025
Continuing to fill the literature gap, this research replicated and expands a prior study of student performance in database normalization in an introductory database course. The data was collected from four different universities, each having different prerequisite courses for their database course. Student performance on a database normalization…
Descriptors: Required Courses, Academic Achievement, Information Systems, Databases
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
Xin Gong; Weiqi Xu; Ailing Qiao; Zhixia Li – Journal of Computer Assisted Learning, 2025
Background: Robot programming can simultaneously cultivate learners' computational thinking (CT) and spatial thinking (ST). However, there is a noticeable gap in research focusing on the micro-level development patterns of learners' CT and ST and their interconnections. Objectives: This study aims to uncover the intricate development patterns and…
Descriptors: Mental Computation, Thinking Skills, Skill Development, Robotics
Willow S. Sauermilch; Michelle L. Ivey; Eric E. Rasmussen; Christina J. Najera – Journal of Autism and Developmental Disorders, 2025
Television programs have introduced viewers to characters on the autism spectrum (e.g., "Sesame Street," "The Good Doctor"), impacting audiences' knowledge and attitudes. Thus, it is essential that character representations convey accurate health information. This study explores how autistic portrayals across six adult and…
Descriptors: Autism Spectrum Disorders, Television Viewing, Programming (Broadcast), Symptoms (Individual Disorders)
Suppanut Sriutaisuk; Yu Liu; Seungwon Chung; Hanjoe Kim; Fei Gu – Educational and Psychological Measurement, 2025
The multiple imputation two-stage (MI2S) approach holds promise for evaluating the model fit of structural equation models for ordinal variables with multiply imputed data. However, previous studies only examined the performance of MI2S-based residual-based test statistics. This study extends previous research by examining the performance of two…
Descriptors: Structural Equation Models, Error of Measurement, Programming Languages, Goodness of Fit
Yoonhee Shin; Jaewon Jung; Seohyun Choi; Bokmoon Jung – Education and Information Technologies, 2025
This study investigates the effects of metacognitive and cognitive strategies for computational thinking (CT) on managing cognitive load and enhancing problem-solving skills in collaborative programming. Four different scaffolding conditions were provided to help learners optimize cognitive load and improve their problem-solving abilities. A total…
Descriptors: Scaffolding (Teaching Technique), Mental Computation, Cognitive Processes, Difficulty Level

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