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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
Menon, Pratibha – Journal of Information Systems Education, 2023
This paper introduces a teaching process to develop students' problem-solving and programming efficacy in an introductory computer programming course. The proposed teaching practice provides step-by-step guidelines on using worked-out examples of code to demonstrate the applications of programming concepts. These coding demonstrations explicitly…
Descriptors: Introductory Courses, Programming, Computer Science Education, Feedback (Response)
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
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
Shi, Yang; Schmucker, Robin; Chi, Min; Barnes, Tiffany; Price, Thomas – International Educational Data Mining Society, 2023
Knowledge components (KCs) have many applications. In computing education, knowing the demonstration of specific KCs has been challenging. This paper introduces an entirely data-driven approach for: (1) discovering KCs; and (2) demonstrating KCs, using students' actual code submissions. Our system is based on two expected properties of KCs: (1)…
Descriptors: Computer Science Education, Data Analysis, Programming, Coding
Shi, Yang; Chi, Min; Barnes, Tiffany; Price, Thomas W. – International Educational Data Mining Society, 2022
Knowledge tracing (KT) models are a popular approach for predicting students' future performance at practice problems using their prior attempts. Though many innovations have been made in KT, most models including the state-of-the-art Deep KT (DKT) mainly leverage each student's response either as correct or incorrect, ignoring its content. In…
Descriptors: Programming, Knowledge Level, Prediction, Instructional Innovation
Haglund, Pontus; Strömbäck, Filip; Mannila, Linda – Informatics in Education, 2021
Controlling complexity through the use of abstractions is a critical part of problem solving in programming. Thus, becoming proficient with procedural and data abstraction through the use of user-defined functions is important. Properly using functions for abstraction involves a number of other core concepts, such as parameter passing, scope and…
Descriptors: Computer Science Education, Programming, Programming Languages, Problem Solving
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
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
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
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
Aivaloglou, Efthimia; van der Meulen, Anna – ACM Transactions on Computing Education, 2021
Courses in computer science curricula often involve group programming assignments. Instructors are required to take several decisions on assignment setup and monitoring, team formation policies, and grading systems. Group programming projects provide unique monitoring opportunities due to the availability of both product and process data, as well…
Descriptors: Student Attitudes, Grading, Cooperative Learning, Programming
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
What! No GUI? -- Teaching a Text Based Command Line Oriented Introduction to Computer Science Course
Goldstein, Ira – Information Systems Education Journal, 2019
Computer Science students need to acquire knowledge about both the hardware and software aspects of computing systems. It is necessary for them to understand how each layer interacts with one another. However, since Graphical User Interfaces have become ubiquitous, the opportunities to interact with the computer via a command prompt as part of…
Descriptors: Computer Science Education, Computer Software, Introductory Courses, Programming