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Marcus Messer; Neil C. C. Brown; Michael Kölling; Miaojing Shi – ACM Transactions on Computing Education, 2025
Providing consistent summative assessment to students is important, as the grades they are awarded affect their progression through university and future career prospects. While small cohorts are typically assessed by a single assessor, such as the module/class leader, larger cohorts are often assessed by multiple assessors, typically teaching…
Descriptors: Foreign Countries, Grading, Interrater Reliability, Teaching Assistants
Osman Kayhan; Özgen Korkmaz; Recep Çakir – Computers in the Schools, 2024
The aim of this study is to examine the effects of high school students' perceptions of computational thinking skills and perceptions of logical and mathematical intelligence on their programming self-efficacy. Descriptive survey model as a quantitative research design was used in the research. The data were collected face to face on a voluntary…
Descriptors: Computation, Thinking Skills, Logical Thinking, Self Efficacy
Nardie Fanchamps; Emily van Gool; Lou Slangen; Paul Hennissen – Education and Information Technologies, 2024
Learning basic concepts of programming resulting in a development on computational thinking (CT) can be reached by means of digital programming environments. As a counterpart, the application of unplugged programming activities seems also to have promising potential regarding the impact on CT. The main characteristic of unplugged programming is…
Descriptors: Computation, Thinking Skills, Programming, Computer Peripherals
Selin Urhan; Selay Arkün Kocadere – Educational Technology & Society, 2024
This study investigated the effect of video lecture types on the performance of students in computational problem-solving practices. A total of 19 university students participated in the computational problem-solving practices that mostly required declarative knowledge, and 22 university students participated in the computational problem-solving…
Descriptors: Video Technology, Lecture Method, Problem Solving, Computation
Niloofar Mansoor; Cole S. Peterson; Michael D. Dodd; Bonita Sharif – ACM Transactions on Computing Education, 2024
Background and Context: Understanding how a student programmer solves different task types in different programming languages is essential to understanding how we can further improve teaching tools to support students to be industry-ready when they graduate. It also provides insight into students' thought processes in different task types and…
Descriptors: Biofeedback, Eye Movements, Computer Science Education, Programming Languages
Laurence New-Moore; Gusti Agung Ayu Mas Pramitasari – Compare: A Journal of Comparative and International Education, 2024
Following the work of Tamatea and Pramitasari in the Bali Coding Class (2018), we ask if liberal empowerment can sit alongside Bourdieu's social reproduction theory in framing a non-formal education coding class for rural Balinese youth. While a review of critical theory informed literature suggests not, we appropriate the work of Mills to read…
Descriptors: Foreign Countries, Coding, Rural Youth, Nonformal Education
Gabriela de Carvalho Barros Bezerra; Wilk Oliveira; Ana Cláudia Guimarães Santos; Juho Hamari – ACM Transactions on Computing Education, 2024
Despite recent high interest among researchers and practitioners in learning programming, even the most dedicated learners can struggle to find motivation for studying and practicing programming. Therefore, in recent years, several strategies (e.g., educational games, flipped classrooms, and visual programming languages) have been employed to…
Descriptors: Gamification, Programming, Computer Science Education, Workshops
Andrew Millam; Christine Bakke – Journal of Information Technology Education: Innovations in Practice, 2024
Aim/Purpose: This paper is part of a multi-case study that aims to test whether generative AI makes an effective coding assistant. Particularly, this work evaluates the ability of two AI chatbots (ChatGPT and Bing Chat) to generate concise computer code, considers ethical issues related to generative AI, and offers suggestions for how to improve…
Descriptors: Coding, Artificial Intelligence, Natural Language Processing, Computer Software
Yingbin Zhang; Yafei Ye; Luc Paquette; Yibo Wang; Xiaoyong Hu – Journal of Computer Assisted Learning, 2024
Background: Learning analytics (LA) research often aggregates learning process data to extract measurements indicating constructs of interest. However, the warranty that such aggregation will produce reliable measurements has not been explicitly examined. The reliability evidence of aggregate measurements has rarely been reported, leaving an…
Descriptors: Learning Analytics, Learning Processes, Test Reliability, Psychometrics
Odd Tore Kaufmann; Marianne Maugesten; Tamsin Meaney – Journal of Mathematics Teacher Education, 2024
As has been the case in many countries around the world, the new Norwegian curriculum from 2020 included programming as part of mathematics education. However, little is known about how prospective teachers perceive this addition in regard to their developing professional identities. When the results from an electronic survey of 394 prospective…
Descriptors: Professional Identity, Preservice Teachers, Mathematics Teachers, Mathematics Instruction
Stephanie Yang; Miles Baird; Eleanor O’Rourke; Karen Brennan; Bertrand Schneider – ACM Transactions on Computing Education, 2024
Students learning computer science frequently struggle with debugging errors in their code. These struggles can have significant downstream effects--negatively influencing how students assess their programming ability and contributing to their decision to drop out of CS courses. However, debugging instruction is often an overlooked topic, and…
Descriptors: Computer Science Education, Troubleshooting, Programming, Teaching Methods
Pere J. Ferrando; Ana Hernández-Dorado; Urbano Lorenzo-Seva – Structural Equation Modeling: A Multidisciplinary Journal, 2024
A frequent criticism of exploratory factor analysis (EFA) is that it does not allow correlated residuals to be modelled, while they can be routinely specified in the confirmatory (CFA) model. In this article, we propose an EFA approach in which both the common factor solution and the residual matrix are unrestricted (i.e., the correlated residuals…
Descriptors: Correlation, Factor Analysis, Models, Goodness of Fit
Xiao Liu; Zhiyong Zhang; Lijuan Wang – Grantee Submission, 2024
In psychology, researchers are often interested in testing hypotheses about mediation, such as testing the presence of a mediation effect of a treatment (e.g., intervention assignment) on an outcome via a mediator. An increasingly popular approach to testing hypotheses is the Bayesian testing approach with Bayes factors (BFs). Despite the growing…
Descriptors: Sample Size, Bayesian Statistics, Programming Languages, Simulation
Aysegul Yilmaz; Devkan Kaleci – Educational Policy Analysis and Strategic Research, 2024
The research aims to explore the acquisition of Computational Thinking (CT) sub-skills among 5th and 6th grade secondary school students in Turkey through a block-based programming application, code.org. It seeks to understand if mastering these skills is essential for students globally. This study involved seven volunteer students selected…
Descriptors: Foreign Countries, Computation, Thinking Skills, Mastery Learning
Han Wan; Hongzhen Luo; Mengying Li; Xiaoyan Luo – IEEE Transactions on Learning Technologies, 2024
Automatic program repair (APR) tools are valuable for students to assist them with debugging tasks since program repair captures the code modification to make a buggy program pass the given test-suite. However, the process of manually generating catalogs of code modifications is intricate and time-consuming. This article proposes contextual error…
Descriptors: Programming, Computer Science Education, Introductory Courses, Assignments

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