Computer Applications in Engineering Education最新文献

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.

In the era of Industry 4.0, laser-based additive manufacturing (LBAM) has gained substantial momentum in the production of complex lightweight structures in several domains such as aerospace, civil, and biomedical engineering. The increasing demand for consistent and precise manufacturing processes has urged the manufacturing industry to consider the coupling of topology optimization (TO) and laser powder bed fusion (LPBF) in the design of sophisticatedly novel topologies that are unattainable through traditional processes. Notably, this union has demonstrated a highly efficient and productive capability toward the manufacturing industry. In line with this accelerated pace, engineering programs within universities exert significant effort to revise and update their engineering curriculum design to incorporate emerging manufacturing technologies providing students with skills that are aligned with the actual industrial context. In this article, a computer-aided design (CAD)/computer-aided engineering (CAE)/computer-aided manufacturing (CAM) project-based laboratory framework is proposed combining TO and LPBF exploiting a simulation-based environment integrating CAD, CAE, and CAM. The structure of the proposed CAD/CAE/CAM design methodology is revisited to discern the added value of the newly developed framework and its particularity in assisting aerospace engineering students to meet industrial expectations. A new CAD/CAE/CAM project-based laboratory framework has been developed integrating TO and LPBF using advanced engineering tools within the aerospace engineering education.

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.

Computational Thinking (CT) can be defined as the thought processes involved in formulating problems so that their solutions can be represented as sequential steps and algorithms. It is a key skill for children in the 21st century. However, it is unclear how CT can be developed most effectively in children. Several pedagogical methodologies have been proposed and are being investigated. The main aim of this paper is to test the hypothesis which states that using three-dimensional (3D) simulated robots helps in the learning of programming and CT concepts, such as directions, loops, conditionals, and functions. The research questions are: Does this hypothesis hold true? Are some concepts easier or better learned than others and to what extent? The goal is to measure and evaluate the effect of using as a learning tool a platform with 3D simulated robots and realistic physics, and compare it with the standard Scratch learning tool which does not use robotics but a two-dimensional (2D) cartoon avatar they are already familiar with. For practical reasons, a quasiexperimental design with nonequivalent groups and 85 second-year Secondary Education students (ages 12–13) was performed. They were separated into control and experimental groups and followed a seven-session intervention with the baseline 2D Scratch and the 3D simulated robots platform, respectively. Both used a visual block programming language and the same activities. To have quantitative and reliable results, a widely accepted CT test has been used, pre- and postintervention. Also qualitative feedback is presented. The obtained results show that using the platform with simulated 3D robots significantly helps when developing students' CT. With it, the students do learn basic programming concepts and reach higher scores in the CT test. This improvement applies to all CT-analyzed concepts except in functions where the grades are maintained. Furthermore, students manage to master the activities on the 3D simulated robots platform, which reflects on the empowerment the platform has got in them.

Connecting the chemical industry with the academic environment has created a unique opportunity to apply experiential learning in many areas of teaching. A new approach of using the existing operator training simulator, which is basically a digital twin of a new dicyclopentadiene plant, was used to educate and train students from technical universities. Using this simulator, students can gain adequate knowledge for control, process optimization, and problem solving under nonstandard operating conditions. Simulating a dynamic process in the Aspen HYSYS interface along with elements of a real industrial control system and control interface, and especially the online visualization of the results, helps students understand the physicochemical principles through their own intervention and experience of the consequences. The training simulator's ability to accurately reflect ongoing processes can be verified by students during a guided tour of a production plant. The experience with student learning so far shows that this is a very attractive and, above all, effective tool for extending the teaching of chemical engineering, control, and automation of chemical processes.