The ability of large language models (LLMs) to generate code has raised concerns in computer science education, as students may use tools like ChatGPT for programming assignments. While much research has focused on higher education, especially for languages like Java and Python, little attention has been given to K-12 settings, particularly for…

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…

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…

Automatically detecting bugs in student program code is critical to enable formative feedback to help students pinpoint errors and resolve them. Deep learning models especially code2vec and ASTNN have shown great success for "large-scale" code classification. It is not clear, however, whether they can be effectively used for bug…

An organization's infrastructure rests upon the premise that cybersecurity professionals have specific knowledge in administrating and protecting it against outside threats. Without this expertise, sensitive information could be leaked to malicious actors and cause damage to critical systems. In order to facilitate this process, the presented work…

Contract cheating is a significant concern in higher education, requiring a multifaceted teaching and learning approach to address it. Quizzing students about their writing to promote engagement, confirm authorship and detect cheating has not yet been investigated systematically. Therefore, in this study, our objective was to explore the validity…

Background/purpose: This study investigates how knowledge, attitudes, and practices (KAP) influence cybersecurity awareness (CSA) among students in Thai educational institutions. The research addresses regional disparities in cybersecurity readiness by incorporating a culturally responsive adaptation of the KAP model. Materials/methods: A…

We present a privacy-friendly early-detection framework to identify students at risk of failing in introductory programming courses at university. The framework was validated for two different courses with annual editions taken by higher education students (N = 2 080) and was found to be highly accurate and robust against variation in course…

Like much of the world, the United States is rapidly implementing the teaching of computer science into both primary and secondary school curricula. Uncovering what challenges U.S. schools in general--and rural U.S. schools in the unique environment of more mountainous regions of the U.S. in particular--face in implementing new curricula is not…

The integration of Internet of Things (IoT), Artificial Intelligence (AI), and cybersecurity presents new opportunities for innovation and entrepreneurship, yet traditional educational approaches often lack the interdisciplinary and applied focus required to develop these competencies. This study evaluates the impact of an experiential learning…

Background: Learning to code is increasingly embedded in secondary and higher education curricula, where solving programming exercises plays an important role in the learning process and in formative and summative assessment. Unfortunately, students admit that copying code from each other is a common practice and teachers indicate they rarely use…

Software vulnerabilities have become a severe cybersecurity issue. There are numerous resources of industry best practices available, but it is still challenging to effectively teach secure coding practices. The resources are not designed for classroom usage because the amount of information is overwhelming for students. There are efforts in…

In this research, a mixed-method approach was employed to conduct large-scale eye-tracking measurements, traditionally associated with high costs and extensive time commitments. Utilizing consumer-grade webcams in conjunction with open-source software, data was collected from an expansive cohort of students, thereby demonstrating the scalability…

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…

Cheating has been a long-standing issue in university assessments. However, the release of ChatGPT and other free-to-use generative AI tools has provided a new and distinct method for cheating. Students can run many assessment questions through the tool and generate a superficially compelling answer, which may or may not be accurate. We ran a…