Computer Applications in Engineering Education最新文献

Software simulation programs and virtual reality (VR) have become powerful tools for several educational purposes, and recently, they were used in a wide range of applications. In cases of inaccessibility to labs, workshops, or industries, as happened before in the coronavirus disease 2019 pandemic, these tools could be effectively integrated with practical lab experiments. In this study, a computational fluid dynamics (CFD) simulation and a VR module were utilized to simulate heat transfer by conduction through various experimental cases. The CFD simulation results were obtained using ANSYS/FLUENT software. Meantime, the experimental data were obtained by carrying out three experiments of heat conduction with different heat transfer rates through simple, composite, and different cross-sectional area bars. At last, the experimental procedure and devices used were virtually constructed using SolidWorks software as three-dimensional models, which were then extruded into VR and augmented reality models. It was found that the simulation results closely align with the experimental ones, and the temperature profile in both cases has the same behavior with small differences, which indicates the validity of the developed module to be used as a simulation of the actual experiments. In addition to improving knowledge of heat transfer principles, this combination of simulation and VR technology advances many Sustainable Development Goals (SDGs), including advancing quality education (SDG 4) and innovation in higher education (SDG 9). Additionally, this method assists in achieving the course learning objectives by mimicking real-world lab experiments, guaranteeing that students graduate from the course with the required information and abilities.

This paper introduces Education Platform for Equivalent Resistance (EDUPERES) and Gamification of Equivalent Resistance (GAMERES), two different parts of a new computer aided education platform with interactive and imaginative design and game elements, which have been created during 4 years. In Vocational School of Transportation of Eskişehir Technical University, electrical circuit analysis is a compact course which exhaustively yet quickly covers all the DC and AC circuit concepts. During the course, it is observed that some students have difficulties in some basic capabilities such as calculation of equivalent resistance of either a standard or a compact circuit, dividing currents, and so on. More sadly, this inability spreads to the rest of the semester. This study aims to overcome this issue through a smart interactive education platform and gamification. The first part, that is, EDUPERES visualizes and animates the solutions of electrical circuits. To make the students exercise circuit questions, it provides an interface which simulates the comfort of using paper and pencil. This platform is powered by a smart algorithm to watch almost all of the actions of the students and to give prompt warnings. It allows students to transform the shapes of compact circuits during circuit reduction. The second part, that is, GAMERES imaginatively converts the circuit questions into action, competition, shooter, puzzle, and maze games. Via box plots and Mann–Whitney–Wilcoxon nonparametric tests, it is shown that EDUPERES and GAMERES can significantly increase students' learning. The success of EDUPERES and GAMERES is discussed with regard to previous studies and gamers' motivations.

Digital societies require professionals in the Technology and Engineering sectors, but their lack, particularly of women, requires a thorough understanding of this gender gap. This research analyzes the beliefs and opinions of university engineering students about the gender gap in their professional fields by means of a community detection algorithm to identify groups of students with similar belief patterns. This study leverages a community detection algorithm to analyze the beliefs of 590 engineering students regarding the gender gap in their field, together with a correlational and explanatory design using a quantitative paradigm. A validated questionnaire focusing on the professional dimension was used. The algorithm identified three student communities, two gender-sensitive and one gender-insensitive. The study uncovered a concerning lack of awareness regarding the gender gap among engineering students. Many participants did not recognize the importance of increasing the representation of professional women, maintained the belief that the gender gap affects only women, and assumed that men and women are equally paid. However, women show a higher level of awareness, while men perceive the gender gap as a passing trend, which is worrying. Students recognize the importance of integrating a gender perspective into university and engineering curricula. It is worrying that many students doubt the existence of the gender gap and that both genders lack knowledge about gender gap issues. Finally, community detection algorithms could efficiently and automatically analyze gender gap issues or other unrelated topics.

This article presents an integrated educational module for undergraduate traffic engineering at the microscale level. When dealing with a complex transportation system, the education program should cultivate students’ acquisition of both in-depth traffic specialization and breadth of engineering knowledge. For the educational instruction of the signal phase design, this article presents an integrated design that includes several engineering subjects: signal phase design, circuits and electronics, and object-oriented programming (OOP). Due to the lengthy evolution of signal phase design and the high-end industrial standards for this issue, this well-structured problem requires an instructional design to adopt a worked example that integrates varied engineering domains. The integrated design session is intended to deliver education through designing a miniature signal controller while creating an immersive situation and encouraging social teamwork. Feedback from participating students has been positive, indicating the achievement of the planned learning objectives and better mastery of engineering practices.

The knowledge-based prerequisite framework (KPF) is an alternative to the course-based prerequisite framework (CPF), which is widely used for curriculum design. The KPF is more flexible because it only requires essential prerequisite knowledge, while the CPF is more rigid and requires students to take all prerequisite courses. Since the number of prerequisite knowledge terms is, in general, much greater than the number of prerequisite courses, flexibility can cause additional complexity. Furthermore, the KPF inevitably requires handling semantics of defined knowledge terms. This work presents a novel Artificial Intelligence (AI) Planning mathematical model that enables the KPF by automatically verifying prerequisite knowledge and incorporating hierarchical semantic relationships among knowledge terms into the model. The proposed model significantly improves the quality of course planning solutions by finding hidden or better solutions that could not be obtained without semantics consideration. The results of the comprehensive experiments show the optimality of the solutions obtained by the mathematical model and demonstrate the outperformance of incorporation of the semantics into the mathematical model, in terms of the quality of solutions. Finally, the experimental results on scalability show the necessity of the development of efficient heuristic algorithms.

The purpose of the investigation was to evaluate the utility of ChatGPT, a state-of-the-art language model developed by Open AI, in the context of civil engineering education. To achieve this objective, 44 civil engineering students from a large state university in the United States were recruited and asked to respond to three questions pertaining to Construction Surveying and Geomatics. The students were then introduced to ChatGPT and provided with guidelines on how the platform could be utilized for educational purposes, including obtaining answers to questions like those presented to them earlier. The students were then given the opportunity to leverage ChatGPT to obtain responses to questions they had been presented with earlier and any other related queries of interest. Subsequently, the students were asked to provide written responses to the same questions they were presented with earlier, but without access to ChatGPT or its response, to assess any knowledge gains. The investigation also captured the student's acceptance and perceived usability based on their experience of using ChatGPT. The findings indicated that the student's written responses were more thorough, detailed, and informative after utilizing ChatGPT. The results also revealed that ChatGPT was largely well-received by the students and they held a positive perception of the AI platform. The findings can inform efforts targeted at successfully integrating AI tools for civil engineering education.

Engineering can enhance students' theoretical knowledge and practical application skills when integrated into K-12 education. This approach encourages students to contemplate technology and engineering in more depth. Field programmable gate array (FPGA) technology training is becoming increasingly important, especially for vocational high school technical teachers. This study focuses on providing FPGA technology training to these vocational and technical teachers. The aim is to improve their theoretical understanding of FPGA digital design and practical application skills. By incorporating the latest technology into their courses, educators can offer students in-depth learning and practical experience in electronic engineering and digital design. The training program covered the basics of FPGA, its applications, and how it can benefit vocational high schools in laboratory environments. A total of 34 technical teachers participated in the training program. The effectiveness of the program was evaluated through pre- and posttraining questionnaires. The results showed that most of the questionnaire items were statistically and practically significant and varied according to the teachers' department, teaching experience, and level of education.

This paper introduces the El Greco Platform, a Python programming platform for distance learning that employs an educational robot. This website allows prospective learners to remotely control $��\; ��\text{El}��$ Greco, a social humanoid robot designed to be cost-effective, simple to construct, and appropriate for use in education. El Greco is capable of performing multiple tasks, including combined movements. These Robot capabilities can be programmed using either Python code or the Blockly library, which adds an editor to an application that visualizes coding concepts as interlocking blocks. Programming a robot appears to be a significantly more effective and creative method for students to learn a programming language. This educational tool was designed primarily for use by students and allows anyone to learn Python while controlling a robot for free. El Greco Platform features gamification elements that increase the enjoyment and engagement of the learning experience while reinforcing the concepts taught. The survey results on students aged 13–18 revealed that the El Greco Platform captivated the study participants and positively affected their attitudes toward programming and robotics. In addition, it significantly impacted their comprehension of programming and motivated them to seek additional opportunities to expand their knowledge of robotics and programming.

This article presents a descriptive, correlational, and quantitative study investigating the learning processes of undergraduate construction engineering and architecture students. The study aims to analyze the effectiveness of an alternative learning method compared to traditional approaches in engineering, architecture and construction education. The study focuses on the use of a mobile application (CAMPUS Javeriana) as a tool for experiential learning by using digital technologies, such as construction videos and photos, infographic images, building information modeling (BIM) models, virtual and augmented reality, among others, within the app. Forty-six architecture students participated in the study, divided into control and experimental groups within each of three undergraduate courses. Pretest and posttest questionnaires were administered to assess the students' learning outcomes, preferences, and perception of the importance of learning technologies. The test results were analyzed using scatter plots, and statistical analysis was conducted using the Jamovi package in R Studio. The students' perceived importance of the mobile app and their preference to use it in the future were also evaluated. Contextual factors such as student characteristics, available resources, and instructors' teaching style were taken into consideration. The study implemented rubrics based on the Expected Learning Results for each course to measure the overall academic performance. Furthermore, the study explores the concept of learning gain and its relationship with the obtained results, shedding light on experiences, perceptions, and academic performance in the specific context of construction education. Findings suggest a positive impact on learning outcomes and perception as a result of using a series of multi-media technologies in the mobile application.