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Thomas, Paul JoseKutty – ProQuest LLC, 2021
Software modeling is an integral practice for software engineers especially as the complexity of software solutions increase. There is precedent in industry to model information systems in terms of functions, structures, and behaviors. While constructing these models, abstraction and systems thinking are employed to determine elements essential to…
Descriptors: Computer Science Education, Programming Languages, Academic Achievement, College Students
Jun-Ming Su – Education and Information Technologies, 2024
With the rapid growth of web applications, web application security (WAS) has become an important cybersecurity issue. For effective WAS protection, it is necessary to cultivate and train personnel, especially beginners, to develop correct concepts and practical hands-on abilities through cybersecurity education. At present, many methods offer…
Descriptors: Computer Science Education, Information Security, Computer Security, Web Sites
Shao-Chen Chang; Charoenchai Wongwatkit – Education and Information Technologies, 2024
As computational thinking becomes increasingly essential, the challenge of designing effective teaching approaches to foster students' abilities in this area persists, especially for higher order thinking skills. This study addresses this challenge by proposing and implementing a peer assessment-based Scrum project (PA-SP) learning approach in…
Descriptors: Peer Evaluation, Computer Science Education, Programming, Mental Computation
Mehmet Firat; Saniye Kuleli – Journal of Educational Technology and Online Learning, 2024
This research investigates the comparative effectiveness of the ChatGPT and the Google search engine in facilitating the self-learning of JavaScript functions among undergraduate open and distance learning students. The study employed a quasi-experimental post-test control group design to analyze the variables of disorientation, satisfaction,…
Descriptors: Comparative Analysis, Web Sites, Computer Software, Artificial Intelligence
Zhanxia Yang; Marina Bers – Computer Science Education, 2024
Background and Context: Historically, women have been underrepresented in computer science. To address this gender gap, researchers advocate for high-quality computer science programs for early childhood. Objectives: This study examines gender differences in coding performance before and after implementing a 24-lesson visual programming curriculum…
Descriptors: Gender Differences, Grade 1, Elementary School Students, Programming
Abhishek Vaish; Ravindra Kumar; Samo Bobek; Simona Sternad – Journal of Cybersecurity Education, Research and Practice, 2024
The cyber security education market has grownup exponentially, with a CAGR of 13.9 % as reported by Data Intelo. The report published by the World Economic Forum 2023 indicates a shortfall of 2.27 million cyber security experts in 2021 across different roles and hence manifest that Skill-based cyber security education is the need of the hour.…
Descriptors: Experiential Learning, Computer Networks, Information Security, Computer Security
Aleksandar Milenkovic; Nemanja Vucicevic – International Electronic Journal of Mathematics Education, 2024
The contents of calculus, known for their complexity, present significant challenges for students, particularly in mastering multiple integrals and effectively visualizing related concepts. The transition to distance learning prompted by the COVID-19 pandemic has further complicated the learning process in multiple integrals. In line with this and…
Descriptors: Mathematics Instruction, Mathematics Achievement, Calculus, COVID-19
Audrey Ellis; Tracie Yorke; Charles Ansell – Complete College America, 2025
As artificial intelligence reshapes many aspects of society and workforce, many colleges and universities have focused on developing technical AI programs within computer science departments. But preparing students and faculty for an AI-enabled future requires more than technical training--it demands a broader approach to AI literacy and…
Descriptors: Artificial Intelligence, Higher Education, Computer Software, Technology Integration
Phung, Tung; Cambronero, José; Gulwani, Sumit; Kohn, Tobias; Majumdarm, Rupak; Singla, Adish; Soares, Gustavo – International Educational Data Mining Society, 2023
Large language models (LLMs), such as Codex, hold great promise in enhancing programming education by automatically generating feedback for students. We investigate using LLMs to generate feedback for fixing syntax errors in Python programs, a key scenario in introductory programming. More concretely, given a student's buggy program, our goal is…
Descriptors: Computational Linguistics, Feedback (Response), Programming, Computer Science Education
Tsabari, Stav; Segal, Avi; Gal, Kobi – International Educational Data Mining Society, 2023
Automatically identifying struggling students learning to program can assist teachers in providing timely and focused help. This work presents a new deep-learning language model for predicting "bug-fix-time", the expected duration between when a software bug occurs and the time it will be fixed by the student. Such information can guide…
Descriptors: College Students, Computer Science Education, Programming, Error Patterns
Holman, Justin O.; Hacherl, Allie – Journal of Statistics and Data Science Education, 2023
It has become increasingly important for future business professionals to understand statistical computing methods as data science has gained widespread use in contemporary organizational decision processes in recent years. Used by scores of academics and practitioners in a variety of fields, Monte Carlo simulation is one of the most broadly…
Descriptors: Teaching Methods, Monte Carlo Methods, Programming Languages, Statistics Education
Felipe A. Feichas; Rodrigo D. Seabra – Informatics in Education, 2023
This research discusses the use of a gamified web platform for studying software modeling with Unified Modeling Language (UML). Although UML is constantly being improved and studied, many works show that there is difficulty in teaching and learning the subject, due to the complexity of its concepts and the students' cognitive difficulties with…
Descriptors: Gamification, Computer Software, Models, Teaching Methods
Hao, Qiang; Smith, David H., IV; Ding, Lu; Ko, Amy; Ottaway, Camille; Wilson, Jack; Arakawa, Kai H.; Turcan, Alistair; Poehlman, Timothy; Greer, Tyler – Computer Science Education, 2022
Background and Context: automated feedback for programming assignments has great potential in promoting just-in-time learning, but there has been little work investigating the design of feedback in this context. Objective: to investigate the impacts of different designs of automated feedback on student learning at a fine-grained level, and how…
Descriptors: Computer Science Education, Feedback (Response), Teaching Methods, Comparative Analysis
Nathan H. Bean – ProQuest LLC, 2022
Learning to program has long been known to be a difficult task, requiring a student to develop both fluency in the syntax and grammar of a formal programming language and learn the problem-solving approaches and techniques of computational thinking. The successful teaching strategies of the past have involved maintaining small teacher-student…
Descriptors: Algorithms, Coding, Supplementary Education, Programming
Sharman, Jonathan; Acemyan, Claudia Ziegler; Kortum, Philip; Wallach, Dan – International Journal of Computer Science Education in Schools, 2021
Software security is inevitably dependent on developers' ability to to design and implement software without security bugs. Perhaps unsurprisingly, developers often fail to do this. Our goal is to understand this from a usability perspective, identifying how we might best train developers and equip them with the right software tools. To this end,…
Descriptors: Teaching Methods, Computer Science Education, Undergraduate Students, Computer Software

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