Computer Applications in Engineering Education最新文献

With the development of digitalization and the advent of Industry 4.0, education in Smart Construction has undergone great revamping. Engineering System Analysis and Optimization (ESAO) is a cross-disciplinary undergraduate course under the curricula of the Smart Construction Major. However, due to its difficulty and poor linkage to real project-related problems, students lack interest in learning it. This study proposes developing a simulation program that is integrated into the course to improve learning effectiveness. The simulation program includes the following two models: (1) A subway station model that helps to understand the design and functions of a real subway station, the pedestrian flow in the subway station, and the evacuation pattern of pedestrians when a fire hazard occurs; (2) A road intersection model that was used to illustrate the functions of the intersection and explain how to select the optimal parameters to enhance the vehicle pass-through rate. In order to assess the effects of the simulation program, the study used both quantitative and qualitative analyses. In the quantitative analysis, the participants were assigned to two groups: (1) the experimental group and (2) the control group by comparing their exam scores. Additionally, the qualitative analysis, including interviews and casual conversations, was adopted to attain students' opinions about the simulation program. Based on the analysis results, the simulation program has been demonstrated to increase the competence, confidence, and interest of students when compared to conventional teaching approaches.

Higher education is undergoing a global transition as metaverse technologies, including persistent 3D worlds, extended reality, embodied avatars, and interoperable data infrastructures, move from speculative hype to early adoption. This study synthesizes insights from three illustrative institutional initiatives: the MSc in Metaverse at the University of Nicosia (Cyprus), the MSc in Metaverse Technology at The Hong Kong Polytechnic University (Hong Kong), and the Metaverse School of Engineering at the University of Tokyo (Japan). It provides a cross-case comparative review informed by activity theory, the Community of Inquiry framework, and self-determination theory. The analysis highlights how platforms, curricula, policies, assessment practices, and learner identities are orchestrated to scaffold presence, agency, collaboration, and knowledge transfer. Five recurrent mechanisms emerge across cases: (1) spatial presence and embodied rehearsal sup interdisciplinary skill formation; (2) instrumented collaboration and project-based learning generating process data for assessment; (3) integration of micro-credentialing and blockchain-backed verification into institutional quality assurance; (4) equity scaffolds addressing device access, usability, and multilingual participation; and (5) platform governance strategies balancing local ecosystem requirements with global interoperability standards. The study concludes with a set of design principles and a maturity model to guide institutions considering metaverse-enabled education at scale across diverse cultural and disciplinary contexts.

Practical competence is the core requirement for talent training in engineering education. As a critical component of power systems, the electrical operation of substations is not only related to actual operational safety but also an important part of electrical engineering teaching. However, the traditional teaching mode is deficient in practical resources, interactive experience, and collaborative training, which makes it challenging to meet the demand for competence-oriented cultivation in the context of new engineering disciplines. To enhance students' practical skills and engineering cognition, this paper designs and develops an interactive virtual substation simulation training system based on virtual simulation technology. The system integrates a 2D operational interface with a 3D immersive environment, creating a multi-modal, multi-level training platform that covers structural construction, operational drills, and team collaboration. A state synchronization mechanism enables an engineering-level collaborative training experience. To evaluate the system's effectiveness, 90 volunteers participated in a questionnaire survey and controlled experiments. The results indicate that the system significantly improves students' operational skills, spatial understanding, and learning initiative. This system provides a high-fidelity, highly engaging platform for engineering training and offers a feasible path for transforming practical teaching models, demonstrating promising application potential and scalability.

To address the limitations of traditional teaching models in cultivating interdisciplinary talent for the new era, this study presents a teaching reform initiative for the “Principles of Concrete Structure Design” course, grounded in a blended learning and role-experiencing model. The reform involved restructuring the content, creating in-person role-experiencing scenarios, reshaping a comprehensive blended learning framework, and implementing a diversified assessment system. These measures effectively tackled chronic issues such as limited student engagement, the theory–practice gap, challenges in integrating ideological and political education, and simple evaluation methods. Five years of teaching practice have yielded significant outcomes: (1) For students, the reforms have fostered a marked increase in course participation and satisfaction, along with a notable enhancement in their research and practical capabilities. (2) For faculty, they have facilitated simultaneous improvements in both teaching efficiency and research proficiency. (3) For the course itself, its quality and impact have gained national recognition, as evidenced by its designation as a National-Level First-Class Blended Course in China. This study demonstrates that the proposed model offers a valuable reference for enhancing engineering education quality and fostering innovative engineering talent.

This paper proposes a course designed for engineering students about digital image processing using tools from the Jupyter ecosystem, including Jupyter Notebooks, JupyterHub, and Jupyter Widgets. The course integrates theoretical concepts with different practical applications through project work and real-world case analysis to ensure involvement and comprehension. Jupyter Widgets represent one of the main features of the course and enable interactive learning through data manipulation capabilities that create dynamic visualizations. Two other important components of the course are case studies and projects. These components teach students how to solve real-world image processing problems and strengthen their problem-solving skills. Additionally, regular exercises reinforce learning and ensure that students can apply theoretical knowledge in practical scenarios. While a survey conducted among participants indicated a generally positive reception, the focus on Jupyter tools and real-world applications was particularly appreciated, demonstrating the course's success in bridging the gap between theory and practice. Future iterations of the course will continue to build on these strengths, further enhancing the educational experience and better preparing students for professional careers in engineering.

Scenario-based teaching supported by computerized solutions is an effective way to increase student engagement and to improve conceptual understanding in engineering education. In this study, we present bioXL3p, an Excel-based simulation tool designed to help undergraduate environmental engineering students learn fundamentals of activated sludge processes. A structured set of in-class and homework simulation activities, which aims to reinforce theoretical knowledge through guided simulations, was developed in which students are instructed to conduct computer simulations using bioXL3p. A total of 15 activities comprising 7 for carbon removal and fundamentals, 6 for nitrogen removal and 2 for phosphorus removal were proposed. The activities are well aligned with program outcomes from national and international accreditation frameworks such as ABET, EUR-ACE, and MÜDEK, focusing on problem analysis, simulation-based design, and lifelong learning skills. The method was implemented with a total of 23 students over 4 years. After excluding inconsistent responses, participants reported high perceived gains in conceptual understanding (mean = 4.53; N = 17) and confidence in applying activated sludge modeling to design problems. The accompanying database and supporting materials provide an open-source resource for integrating proposed method into environmental engineering curricula. Future development plans include more flexible versions of the tool (possible bioXL Pro and bioXL Ultimate), enabling model selection and user-defined model structures.

Human–computer interaction is a branch of computer science dedicated to the study of how human beings use computers and using the knowledge to develop hardware and software that are efficient and satisfying to users. The purpose of this paper was to develop an instructional approach in human–computer interaction in which students undertake a series of small projects requiring engineering and design skills. Accordingly, we designed three projects, (1) to design the user interface of a digital system taking into consideration performance-related and ergonomics-related parameters, (2) to design a new typeface for any specific application or user group, and (3) to test the usability of a digital system by objectively assessing measurable parameters, such as effectiveness and efficiency, and self-reported parameters, such as satisfaction and cognitive load. The projects involved interaction with end users and using state-of-the-art software tools. This approach was used to teach 104 undergraduate students during the autumn semester of 2024. An analysis showed that the projects provided the students an opportunity to collaborate with their peer and they performed better in examination.

Large language models (LLMs) brought the possibility of enhancing chatbot interactions in educational platforms by providing students adapted support throughout the learning process. This study presents the design and development process of an LLM-powered educational platform prototype and its evaluation in a single learning session on the Computer Networks and Telecommunications course at a technical faculty specialized in information systems and technologies. The proposed platform combines a microlearning paradigm and the availability of LLM chatbot support after each learning unit for students to clarify misconceptions and deepen knowledge and comprehension. The prototype was built using Angular for the client-side application and Express.js for the backend with Firebase Firestore as the database solution. It leveraged the OPENAI GPT-4o model through the available Application Programming Interface (API) for providing the chatbot, which was instructed to offer support for students in the context of the mentioned course. As a result, students generally found the chatbot to be a useful support tool in the learning process, with higher effectiveness reported for clarifying theoretical concepts compared to assisting with practical tasks. This perception aligns with expert evaluations of the chatbot's responses, which revealed statistically significant differences between theoretical and practical answers in terms of factual accuracy, relevance, completeness, and coherence, but not in fluency. Despite these observed differences, both student and expert assessments were overall positive across both types of questions. Even though single-session evaluation limits generalizability of results, these findings suggest feasibility and promising results within this educational context since the chatbot is perceived as a valuable component of the learning experience.