Open-source hardware and software platforms have played an important role in democratizing access to technology and education in computer science and engineering. Recent advancements in tools, such as KiCad, MicroPython, and Thonny, integrated development environment potentially accelerate low-budget educational applications, providing a smooth…

Contribution: A general-purpose model for integrating an intelligent tutoring system within a serious game for use in higher education. Additionally, this article also offers discussions of proper serious game design informed by in-classroom observations and student responses. Background: Personalized learning in higher education has become a key…

Contributions: To address the interpretability issues in artificial intelligence (AI)-powered classroom discourse models, we employ explainable AI methods to unpack classroom discourse analysis from deep learning-based models and evaluate the effects of model explanations on STEM teachers. Background: Deep learning techniques have been used to…

Contribution: An AI model for speech emotion recognition (SER) in the educational domain to analyze the correlation between students' emotions, discussed topics in teams, and academic performance. Background: Research suggests that positive emotions are associated with better academic performance. On the other hand, negative emotions have a…

Contribution: A novel undergraduate course design at the intersection of software engineering (SE) and machine learning (ML) based on industry-reported challenges. Background: ML professionals report that building ML systems is different enough that we need new knowledge about how to infuse ML into software production. For instance, various…

Contribution: A novel proactive and collaborative learning paradigm was proposed to engage learners with different backgrounds and enable effective retention and transfer of the multidisciplinary artificial intelligence (AI)-cybersecurity knowledge. Specifically, the proposed learning paradigm contains: 1) an immersive learning environment to…

Contributions: In this article, a generative artificial intelligence (AI)-based Q&A system has been developed by integrating information retrieval and natural language processing techniques, using course materials as a knowledge base and facilitating real-time student interaction through a chat interface. Background: The rise of advanced AI…

Contribution: This article investigates the impact of gamified learning on high school students (grades 9-12) in computer science, emphasizing learner engagement, knowledge improvement, and overall satisfaction. It contributes insights into the effectiveness of gamification in enhancing educational outcomes. Background: Gamification in education…

Contribution: This study qualitatively uncovered meaning for why and what was motivating to undergraduates participating in an educational human-robot interaction (HRI) experience. A data corpus of four documents (groups) was evaluated from a quasi-experimental, nonequivalent control (n = 23) and treatment (n = 61) research design revealing three…

Contributions: An adoption framework to include generative artificial intelligence (GenAI) in the university curriculum. It identifies and highlights the role of different stakeholders (university management, students, staff, etc.) during the adoption process. It also proposes an objective approach based upon an evaluation matrix to assess the…

Contributions: The Chinese University of Hong Kong (CUHK)-Jockey Club AI for the Future Project (AI4Future) co-created the first pretertiary AI curriculum at the secondary school level for Hong Kong and evaluated its efficacy. This study added to the AI education community by introducing a new AI curriculum framework. The preposttest multifactors…

Contribution: This study incorporates competition-based learning (CBL) into machine learning courses. By engaging students in innovative problem-solving challenges within information competitions, revealing that students' participation in online problem-solving competitions can improve their information technology, and showcase competitions can…

Machine learning (ML) is increasingly utilized in the development and assurance of safety-critical systems (SCSs) nowadays, much like other complex problems. Safety is the topmost priority in SCS, hence, developers who are working in this area must possess extensive knowledge of both ML and SCS. This article presents a methodical investigation…

Contribution: The proposed work carries out the training and testing of the available data through an artificial neural network and develops a model to allocate the subject for maximum outcome. The system also provides percentagewise correlation among all the possible subjects of best fit to allocate among the faculty members. Background: Data…

Artificial intelligence (AI) in programming teaching is something that still has to be explored, since in this area assessment tools that allow grading the students work are the most common ones, but there are not many tools aimed toward providing feedback to the students in the process of creating their program. In this work a small sized…