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Diana Franklin; Paul Denny; David A. Gonzalez-Maldonado; Minh Tran – Cambridge University Press & Assessment, 2025
Generative AI is a disruptive technology that has the potential to transform many aspects of how computer science is taught. Like previous innovations such as high-level programming languages and block-based programming languages, generative AI lowers the technical expertise necessary to create working programs, bringing the power of computation…
Descriptors: Artificial Intelligence, Technology Uses in Education, Computer Science Education, Expertise
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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
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Yunsung Kim; Jadon Geathers; Chris Piech – International Educational Data Mining Society, 2024
"Stochastic programs," which are programs that produce probabilistic output, are a pivotal paradigm in various areas of CS education from introductory programming to machine learning and data science. Despite their importance, the problem of automatically grading such programs remains surprisingly unexplored. In this paper, we formalize…
Descriptors: Grading, Automation, Accuracy, Programming
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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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Cheers, Hayden; Lin, Yuqing – Computer Science Education, 2023
Background and Context: Source code plagiarism is a common occurrence in undergraduate computer science education. Many source code plagiarism detection tools have been proposed to address this problem. However, such tools do not identify plagiarism, nor suggest what assignment submissions are suspicious of plagiarism. Source code plagiarism…
Descriptors: Plagiarism, Programming, Computer Science Education, Identification
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Rahaman, Md. Afzalur; Hoque, Abu Sayed Md. Latiful – International Journal of Learning Technology, 2022
For the last decades, programming courses are being taught in nearly every educational sector. Students are now more likely to use an e-learning platform compared to traditional system because of lower internet costs, remote access, and faster communication facilities. For a programming course studied in both manual and e-learning platforms,…
Descriptors: Evaluation Methods, Programming, Assignments, Automation
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Rodrigues, Luiz; Pereira, Filipe; Toda, Armando; Palomino, Paula; Oliveira, Wilk; Pessoa, Marcela; Carvalho, Leandro; Oliveira, David; Oliveira, Elaine; Cristea, Alexandra; Isotani, Seiji – ACM Transactions on Computing Education, 2022
Students face several difficulties in introductory programming courses (CS1), often leading to high dropout rates, student demotivation, and lack of interest. The literature has indicated that the adequate use of gamification might improve learning in several domains, including CS1. However, the understanding of which (and how) factors influence…
Descriptors: Gamification, Programming, Computer Science Education, Introductory Courses
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Cheers, Hayden; Lin, Yuqing; Yan, Weigen – Informatics in Education, 2023
Source code plagiarism is a common occurrence in undergraduate computer science education. Many source code plagiarism detection tools have been proposed to address this problem. However, most of these tools only measure the similarity between assignment submissions, and do not actually identify which are suspicious of plagiarism. This work…
Descriptors: Plagiarism, Assignments, Computer Software, Computer Science Education
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Kim, J. B.; Zhong, Chen; Liu, Hong – Journal of Information Systems Education, 2023
Cybersecurity education is becoming increasingly important in modern society, and hands-on practice is an essential element. Although instructors provide hands-on labs in their cybersecurity courses, traditional lab exercises often fail to effectively motivate students. Hence, many instructors desire to incorporate gamification in hands-on…
Descriptors: Gamification, Information Security, Class Activities, Active Learning
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Ellie Lovellette; Dennis J. Bouvier; John Matta – ACM Transactions on Computing Education, 2024
In recent years, computing education researchers have investigated the impact of problem context on students' learning and programming performance. This work continues the investigation motivated, in part, by cognitive load theory and educational research in computer science and other disciplines. The results of this study could help inform…
Descriptors: Computer Science Education, Student Evaluation, Context Effect, Problem Solving
Sirazum Munira Tisha – ProQuest LLC, 2023
Most existing autograders used for grading programming assignments are based on unit testing, which is tedious to implement for programs with graphical output and does not allow testing for other code aspects, such as programming style or structure. We present a novel autograding approach based on machine learning that can successfully check the…
Descriptors: Computer Software, Grading, Programming, Assignments
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Wang, Hai; Wang, Shouhong – Journal of Information Systems Education, 2023
NoSQL databases have been used in organizations for decades. Few database textbooks on the market, however, have suitable materials about NoSQL beyond general introductions for typical business students. In fact, users of the typical NoSQL systems on the software market need to have certain computer programming skills. This teaching tip introduces…
Descriptors: Databases, Programming, Computer Science Education, Business Administration Education
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Rebecca L. Matz; Mark Mills; Holly A. Derry; Benjamin T. Hayward; Caitlin Hayward – British Journal of Educational Technology, 2024
Mastery-based assignments typically provide students with multiple opportunities to improve their performance, but getting students to take advantage of these opportunities is difficult. We report on the implementation of a two-part series of nudges designed to improve students' engagement with and performance on mastery-based assignments in…
Descriptors: Mastery Learning, Scores, Assignments, Prompting
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Ayaan M. Kazerouni; Melissa Lee; Aleata Hubbard Cheuoua; Aakash Gautam; Sahar Hooshmand; Paul Salvador Inventado; Eun-Young Kang; Jane Lehr; Yu Sun; Kevin A. Wortman; Ilmi Yoon; Zoë Wood – ACM Transactions on Computing Education, 2025
Background and Context. Computing is considered a fundamental skill for civic engagement, self-expression, and employment opportunity. Despite this, there exist significant equity gaps in post-secondary computing enrollment and retention. Specifically, in the California State University (CSU) system, which serves close to half a million…
Descriptors: Computer Science Education, Social Responsibility, Introductory Courses, Undergraduate Students
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Cory A. Campbell; Sridhar Ramamoorti – Advances in Accounting Education: Teaching and Curriculum Innovations, 2023
We use design thinking in the context of accounting pedagogy to exploit recent advances in cybernetics in the form of generative artificial intelligence technology. Relying on the intuition that supplementing or augmenting human argumentation (natural intelligence or NI) with parallel AI output can produce better student written assignments, we…
Descriptors: Accounting, Business Education, Artificial Intelligence, Cybernetics
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