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Gerit Wagner; Laureen Thurner – Journal of Information Systems Education, 2025
Git, as the leading version-control system, is frequently employed by software developers, digital product managers, and knowledge workers. Information systems (IS) students aspiring to fill software engineering, management, or research positions would therefore benefit from familiarity with Git. However, teaching Git effectively can be…
Descriptors: Computer Science Education, Information Systems, Teaching Methods, Computer Software
Zeynep Güler; Burcu Güngör Cabbar; Sami Özgür – Journal of Science Learning, 2024
This study aims to determine those topics and concepts that biology and science teacher candidates find most challenging to learn in biology lessons. A qualitative case study research method was used to this end. A total of 132 science and biology teacher candidates studying at a state university were asked to write down the ten subjects or…
Descriptors: Biology, Science Education, Science Teachers, Preservice Teachers
Rafael Mellado; Claudio Cubillos – Journal of Computer Assisted Learning, 2024
Background: Effective learning in computer programming courses has been a constant challenge for university teachers and has become a relevant competence for current professionals. The literature on gamification in learning presents mixed results, mainly due to problems in instructional design and inconsistency in gamification. Studies with…
Descriptors: Engineering Education, College Students, Computer Software, Technical Occupations
Andrea Wilson; Cheryl Burleigh – Journal of Educational Research and Practice, 2025
Protecting research integrity is crucial for maintaining trust in the scholarly record. Historically, threats to research integrity stemmed from deliberate human actions, such as data manipulation and misrepresentation. Generative artificial intelligence (GAI) is increasingly prevalent in higher education and is capable of generating research data…
Descriptors: Artificial Intelligence, Computer Software, Technology Integration, Accuracy
Aronshtam, Lior; Shrot, Tammar; Shmallo, Ronit – Education and Information Technologies, 2021
Improving code while preserving its functionality is a common task in the hi-tech industry. Yet students have difficulties improving an algorithm's run-time complexity by an order of magnitude. The paper focuses on assessing students' abilities in this area. We designed a Structure of the Observed Learning Outcome (SOLO) taxonomy, using software…
Descriptors: Difficulty Level, Computer Software, Taxonomy, Coding
Roger Young; Emily Courtney; Alexander Kah; Mariah Wilkerson; Yi-Hsin Chen – Teaching of Psychology, 2025
Background: Multiple-choice item (MCI) assessments are burdensome for instructors to develop. Artificial intelligence (AI, e.g., ChatGPT) can streamline the process without sacrificing quality. The quality of AI-generated MCIs and human experts is comparable. However, whether the quality of AI-generated MCIs is equally good across various domain-…
Descriptors: Item Response Theory, Multiple Choice Tests, Psychology, Textbooks
Mimi Ismail; Ahmed Al - Badri; Said Al - Senaidi – Journal of Education and e-Learning Research, 2025
This study aimed to reveal the differences in individuals' abilities, their standard errors, and the psychometric properties of the test according to the two methods of applying the test (electronic and paper). The descriptive approach was used to achieve the study's objectives. The study sample consisted of 74 male and female students at the…
Descriptors: Achievement Tests, Computer Assisted Testing, Psychometrics, Item Response Theory
Daniele Traversaro; Giorgio Delzanno; Giovanna Guerrini – Informatics in Education, 2024
Concurrency is a complex to learn topic that is becoming more and more relevant, such that many undergraduate Computer Science curricula are introducing it in introductory programming courses. This paper investigates the combined use of Sonic Pi and Team-Based Learning to mitigate the difficulties in early exposure to concurrency. Sonic Pi, a…
Descriptors: Misconceptions, Programming Languages, Computer Science Education, Undergraduate Students
Gregory J. Crowther; Usha Sankar; Leena S. Knight; Deborah L. Myers; Kevin T. Patton; Lekelia D. Jenkins; Thomas A. Knight – Journal of Microbiology & Biology Education, 2023
The biology education literature includes compelling assertions that unfamiliar problems are especially useful for revealing students' true understanding of biology. However, there is only limited evidence that such novel problems have different cognitive requirements than more familiar problems. Here, we sought additional evidence by using…
Descriptors: Science Instruction, Artificial Intelligence, Scoring, Molecular Structure
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
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
Yun Huang; Christian Dieter Schunn; Julio Guerra; Peter L. Brusilovsky – ACM Transactions on Computing Education, 2024
Programming skills are increasingly important to the current digital economy, yet these skills have long been regarded as challenging to acquire. A central challenge in learning programming skills involves the simultaneous use of multiple component skills. This article investigates why students struggle with integrating component skills--a…
Descriptors: Programming, Computer Science Education, Error Patterns, Classification
Tingting Feng – Education and Information Technologies, 2024
The globalization of educational processes has intensified the introduction of interactive learning forms. Education systems around the world have undergone transformation, modernization, and innovation. These processes also implied the implementation of advanced technological tools to improve the quality of teaching various subjects, including…
Descriptors: Computer Storage Devices, Computer Software, Computer Oriented Programs, Influence of Technology
Ümran Üstünbas – International Journal of Modern Education Studies, 2024
In an era of major advances in the digital world, artificial intelligence has been a part of programs, tools, applications, and platforms. It has also been integrated into fields of education including language teaching and learning. To this end, ChatGPT, one of the most recent AI-driven systems, has been proposed to support language learners'…
Descriptors: English Language Learners, English (Second Language), Artificial Intelligence, Speech Skills