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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
Anna Rechtácková; Radek Pelánek; Tomáš Effenberger – ACM Transactions on Computing Education, 2025
Code quality is a critical aspect of programming, as high-quality code is easier to maintain, and code maintenance constitutes the majority of software costs. Consequently, code quality should be emphasized in programming education. While previous research has identified numerous code quality defects commonly made by students, the current state…
Descriptors: Programming, Computer Science Education, Error Patterns, Automation
Ishaya Gambo; Faith-Jane Abegunde; Omobola Gambo; Roseline Oluwaseun Ogundokun; Akinbowale Natheniel Babatunde; Cheng-Chi Lee – Education and Information Technologies, 2025
The current educational system relies heavily on manual grading, posing challenges such as delayed feedback and grading inaccuracies. Automated grading tools (AGTs) offer solutions but come with limitations. To address this, "GRAD-AI" is introduced, an advanced AGT that combines automation with teacher involvement for precise grading,…
Descriptors: Automation, Grading, Artificial Intelligence, Computer Assisted Testing
Zifeng Liu; Wanli Xing; Chenglu Li; Fan Zhang; Hai Li; Victor Minces – Journal of Learning Analytics, 2025
Creativity is a vital skill in science, technology, engineering, and mathematics (STEM)-related education, fostering innovation and problem-solving. Traditionally, creativity assessments relied on human evaluations, such as the consensual assessment technique (CAT), which are resource-intensive, time-consuming, and often subjective. Recent…
Descriptors: Creativity, Elementary School Students, Artificial Intelligence, Man Machine Systems
Smitha S. Kumar; Michael A. Lones; Manuel Maarek; Hind Zantout – ACM Transactions on Computing Education, 2025
Programming demands a variety of cognitive skills, and mastering these competencies is essential for success in computer science education. The importance of formative feedback is well acknowledged in programming education, and thus, a diverse range of techniques has been proposed to generate and enhance formative feedback for programming…
Descriptors: Automation, Computer Science Education, Programming, Feedback (Response)
Umar Alkafaween; Ibrahim Albluwi; Paul Denny – Journal of Computer Assisted Learning, 2025
Background: Automatically graded programming assignments provide instant feedback to students and significantly reduce manual grading time for instructors. However, creating comprehensive suites of test cases for programming problems within automatic graders can be time-consuming and complex. The effort needed to define test suites may deter some…
Descriptors: Automation, Grading, Introductory Courses, Programming
Victor-Alexandru Padurean; Tung Phung; Nachiket Kotalwar; Michael Liut; Juho Leinonen; Paul Denny; Adish Singla – International Educational Data Mining Society, 2025
The growing need for automated and personalized feedback in programming education has led to recent interest in leveraging generative AI for feedback generation. However, current approaches tend to rely on prompt engineering techniques in which predefined prompts guide the AI to generate feedback. This can result in rigid and constrained responses…
Descriptors: Automation, Student Writing Models, Feedback (Response), Programming
Olaperi Okuboyejo; Sigrid Ewert; Ian Sanders – ACM Transactions on Computing Education, 2025
Regular expressions (REs) are often taught to undergraduate computer science majors in the Formal Languages and Automata (FLA) course; they are widely used to implement different software functionalities such as search mechanisms and data validation in diverse fields. Despite their importance, the difficulty of REs has been asserted many times in…
Descriptors: Automation, Feedback (Response), Error Patterns, Error Correction
Xiner Liu; Andres Felipe Zambrano; Ryan S. Baker; Amanda Barany; Jaclyn Ocumpaugh; Jiayi Zhang; Maciej Pankiewicz; Nidhi Nasiar; Zhanlan Wei – Journal of Learning Analytics, 2025
This study explores the potential of the large language model GPT-4 as an automated tool for qualitative data analysis by educational researchers, exploring which techniques are most successful for different types of constructs. Specifically, we assess three different prompt engineering strategies -- Zero-shot, Few-shot, and Fewshot with…
Descriptors: Coding, Artificial Intelligence, Automation, Data Analysis

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