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Adriana Villavicencio; Wendy Martin; Cheri Fancsali; Maya Israel – Journal of Research on Technology in Education, 2025
Because of the rapid expansion of computer science (CS) education, educational leaders must consider how to recruit, prepare, and support teachers who typically do not have a background in CS. This study examines two professional development (PD) approaches used to introduce CS education to non-CS teachers. We aim to understand if/how each model…
Descriptors: Computer Science Education, Models, Faculty Development, Professional Autonomy
Jaildo Tavares Pequeno; Benjamim Fonseca; Joaquim Bernardino Oliveira Lopes – International Journal of Technology and Design Education, 2024
This work aims to identify teaching and learning practices in practical classes of Computer Network Technology courses, which promote the use of the Physical Laboratory (PL) as an epistemic tool to improve learning in epistemic terms. Content analysis of Multimodal Narrations (MN) of three classes by two teachers were used. An MN aggregates and…
Descriptors: Epistemology, Learning Processes, Mediation Theory, Computer Science Education
Jinshui Wang; Shuguang Chen; Zhengyi Tang; Pengchen Lin; Yupeng Wang – Education and Information Technologies, 2025
Mastering SQL programming skills is fundamental in computer science education, and Online Judging Systems (OJS) play a critical role in automatically assessing SQL codes, improving the accuracy and efficiency of evaluations. However, these systems are vulnerable to manipulation by students who can submit "cheating codes" that pass the…
Descriptors: Programming, Computer Science Education, Cheating, Computer Assisted Testing
Meija Lohiniva; Ville Isomöttönen – ACM Transactions on Computing Education, 2025
Context: Introductory programming courses often face high dropout and failure rates, a challenge widely addressed in computing education research. Collaborative methods, such as group work and pair programming, have been proposed as potential solutions, as they are believed to enhance students' study motivation. Objective: This article provides a…
Descriptors: Cooperative Learning, Student Motivation, Introductory Courses, Computer Science Education
Liargkovas, Georgios; Papadopoulou, Angeliki; Kotti, Zoe; Spinellis, Diomidis – IEEE Transactions on Education, 2022
Contribution: Determine and analyze the gap between software practitioners' education outlined in the 2014 IEEE/ACM software engineering education knowledge (SEEK) and industrial needs pointed by Wikipedia articles referenced in Stack Overflow (SO) posts. Background: Previous work has uncovered deficiencies in the coverage of computer…
Descriptors: Industry, Knowledge Level, Computer Software, Computer Science
Peer reviewedJennifer L. Maeng; Timothy Konold; Khushbu Singh – Grantee Submission, 2025
The study examined the Advancing Rural Computer Science (ARCS) program, a professional development initiative designed to improve elementary teachers' computer science (CS) content knowledge, pedagogical practices, and self-efficacy, with the goal of enhancing K-5 students' interest in and knowledge of CS. ARCS was funded through USED EIR…
Descriptors: Rural Schools, Computer Science Education, Faculty Development, Elementary School Teachers
Herminio Bodon; Vishesh Kumar; Marcelo Worsley – ACM Transactions on Computing Education, 2025
Objectives: Athletics and sports represent a focal part of adolescence for millions of youth around the world. However, opportunities to engage in computer science (CS) learning experiences are less prevalent, particularly among Hispanic and low-income communities. Recently, researchers have explored ways to bridge these, seemingly, disparate…
Descriptors: Design, Computer Science Education, Physical Education, Athletics
Leah Bidlake; Eric Aubanel; Daniel Voyer – ACM Transactions on Computing Education, 2025
Research on mental model representations developed by programmers during parallel program comprehension is important for informing and advancing teaching methods including model-based learning and visualizations. The goals of the research presented here were to determine: how the mental models of programmers change and develop as they learn…
Descriptors: Schemata (Cognition), Programming, Computer Science Education, Coding
Muntasir Hoq; Ananya Rao; Reisha Jaishankar; Krish Piryani; Nithya Janapati; Jessica Vandenberg; Bradford Mott; Narges Norouzi; James Lester; Bita Akram – International Educational Data Mining Society, 2025
In Computer Science (CS) education, understanding factors contributing to students' programming difficulties is crucial for effective learning support. By identifying specific issues students face, educators can provide targeted assistance to help them overcome obstacles and improve learning outcomes. While identifying sources of struggle, such as…
Descriptors: Computer Science Education, Programming, Misconceptions, Error Patterns
Haoze Du; Richard Li; Edward Gehringer – International Educational Data Mining Society, 2025
Evaluating the performance of Large Language Models (LLMs) is a critical yet challenging task, particularly when aiming to avoid subjective assessments. This paper proposes a framework for leveraging subjective metrics derived from the class textual materials across different semesters to assess LLM outputs across various tasks. By utilizing…
Descriptors: Artificial Intelligence, Performance, Evaluation, Automation
Jesper Dannath; Alina Deriyeva; Benjamin Paaßen – International Educational Data Mining Society, 2025
Research on the effectiveness of Intelligent Tutoring Systems (ITSs) suggests that automatic hint generation has the best effect on learning outcomes when hints are provided on the level of intermediate steps. However, ITSs for programming tasks face the challenge to decide on the granularity of steps for feedback, since it is not a priori clear…
Descriptors: Intelligent Tutoring Systems, Programming, Computer Science Education, Undergraduate Students
Muldner, Kasia; Jennings, Jay; Chiarelli, Veronica – ACM Transactions on Computing Education, 2023
This article reviews literature on worked examples in the context of programming activities. We focus on two types of examples, namely, code-tracing and code-generation, because there is sufficient research on these to warrant a review. We synthesize key results according to themes that emerged from the review. This synthesis aims to provide…
Descriptors: Problem Solving, Programming, Computer Science Education, Literature Reviews
Radek Pelánek – ACM Transactions on Computing Education, 2025
Learning environments for programming education need a comprehensive task set that guides students from basic programming concepts to complex challenges. For creating such a task set, it is beneficial to utilize the concept of a design space--a systematic mapping of design dimensions and choices along these dimensions. We propose an iterative…
Descriptors: Computer Science Education, Programming, Design, Task Analysis
Jérôme Brender; Laila El-Hamamsy; Christian Giang; Laura Mathex; Tanja Käser; Francesco Mondada – Educational Technology Research and Development, 2025
Generalist primary school computer science (CS) teachers are often reluctant to introduce CS activities that go beyond CS unplugged tasks. To address this challenge, we drew from constructive alignment principles to implement a new programming modality for primary school: the handwriting programming language (HPL). HPL brings programming…
Descriptors: Handwriting, Programming Languages, Computer Science Education, Teaching Methods
Mehmet Basaran; Ömer Faruk Vural; Sermin Metin; Sabiha Tamur – International Journal of Early Childhood, 2025
This study investigates ChatGPT's perspectives on coding education for preschool children to provide a comprehensive understanding that is valuable for educators in early childhood education. An instrumental case study approach was employed, utilizing qualitative research design and case study methods. Data were gathered using a structured…
Descriptors: Preschool Education, Computer Science Education, Coding, Artificial Intelligence

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