Computer Applications in Engineering Education最新文献

{"title":"Correction to “A Systematic Review of Technology-Enhanced Learning Approaches to Foster Construction Engineering and Management Competencies”","authors":"","doi":"10.1002/cae.70104","DOIUrl":"https://doi.org/10.1002/cae.70104","url":null,"abstract":"<p>Marchiori, R., Song, S., Moon, J., Awoyemi, D., Ghooreian, A. and Ramenzapour, E. (2025). A Systematic Review of Technology-Enhanced Learning Approaches to Foster Construction Engineering and Management Competencies. <i>Computer Applications in Engineering Education</i> 33: e70074. https://doi.org/10.1002/cae.70074</p><p>In the article coauthor's first name has been misspelled. The correct author name is Erfan Ramezanpour.</p><p>We apologize for this error.</p>","PeriodicalId":50643,"journal":{"name":"Computer Applications in Engineering Education","volume":"33 6","pages":""},"PeriodicalIF":2.2,"publicationDate":"2025-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cae.70104","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145469428","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of a Unity3D-Based Virtual Simulation Tool for Hydrogen Fuel Cell Performance Testing in Engineering Education","authors":"Lei Ma,&nbsp;Junjie Xiong,&nbsp;Xin Wang,&nbsp;Zhaoxin Yan,&nbsp;Luochao Ji,&nbsp;Junfu Zhangi,&nbsp;Lian Zhang,&nbsp;Heng Xiao","doi":"10.1002/cae.70095","DOIUrl":"https://doi.org/10.1002/cae.70095","url":null,"abstract":"<div>\u0000 \u0000 <p>With the rapid advancement of the renewable energy industry, hydrogen fuel cells, known for their high energy conversion efficiency, low pollution, and minimal noise during operation, remain at the forefront of industrial research. Consequently, the production processes and performance testing methods of hydrogen fuel cells have become essential components in the curricula of relevant educational institutions. This study develops a virtual simulation engineering education software based on Unity3D, specifically designed to facilitate learning for students and educators in secondary vocational, higher vocational, and tertiary institutions regarding hydrogen fuel cell performance testing. By leveraging existing preparatory materials, the software integrates core professional knowledge, such as the working principles and system structures of hydrogen fuel cells. The theoretical and practical teaching content was determined based on course design requirements. Furthermore, the development process was outlined, including software design, model and scene construction, implementation of interactive functions, software testing, and deployment. Evaluation of the software's functionality and educational effectiveness revealed positive feedback from both teachers and students. The software enhanced students' understanding of hydrogen fuel cell performance testing, improved teaching and learning efficiency, and contributed to greater educational equity.</p>\u0000 </div>","PeriodicalId":50643,"journal":{"name":"Computer Applications in Engineering Education","volume":"33 6","pages":""},"PeriodicalIF":2.2,"publicationDate":"2025-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145407366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Hardware-in-the-Loop and 3D Simulation Framework for Active Learning in Engineering Education","authors":"Jessica S. Ortiz,&nbsp;Manuel A. Masapanta,&nbsp;Víctor H. Andaluz,&nbsp;Christian P. Carvajal","doi":"10.1002/cae.70101","DOIUrl":"https://doi.org/10.1002/cae.70101","url":null,"abstract":"<p>This paper describes the implementation of an industrial control system using the Hardware-in-the-Loop (HIL) technique, integrating a Siemens S7-1200 PLC with a virtual plant developed in Unity 3D, using the Modbus TCP communication protocol. This integration allows real-time simulation of industrial processes in a safe, immersive and interactive environment, facilitating the design, testing and validation of control strategies without the need for a physical plant. As part of the study, usability tests were carried out to verify whether the proposed solution is suitable for use as a teaching resource by engineering students. The evaluation was applied to two groups of 20 students each, who interacted with the virtual environment and executed control and monitoring tasks of the simulated process. The results obtained show a satisfactory acceptance of the platform, highlighting its usefulness as a support tool for the understanding and manipulation of automated processes in a controlled environment. This approach proves to be an efficient, safe and scalable alternative for training in industrial automation, aligned with the principles of Industry 4.0.</p>","PeriodicalId":50643,"journal":{"name":"Computer Applications in Engineering Education","volume":"33 6","pages":""},"PeriodicalIF":2.2,"publicationDate":"2025-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cae.70101","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145406949","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Intelligent Teaching Assistant System for Enhanced Online Engineering Education: A Dual-Teacher Model","authors":"Yuhui Yang,&nbsp;Hao Zhang,&nbsp;Yan Jiang","doi":"10.1002/cae.70098","DOIUrl":"https://doi.org/10.1002/cae.70098","url":null,"abstract":"<div>\u0000 \u0000 <p>As online education rapidly grows, traditional engineering education faces challenges such as limited resources, lack of interaction, and insufficient personalized support. This study proposes an Intelligent Teaching Assistant (ITA) system integrated with AI, applied in a “Dual-Teacher” online model, to enhance teaching effectiveness and student experience in engineering courses. This study assesses the ITA system's application in the “Dual-Teacher” model. We hypothesize that the system can improve students' learning experience, engagement, self-efficacy, and academic performance by providing personalized support, real-time Q&amp;A, and emotional feedback. This study designed the ITA system architecture based on an engineering student needs survey and developed the “ChatZJU” ITA system, which was tested in the “Computer Architecture” course. A total of 80 third-year undergraduates were randomly assigned to the experimental group (“Dual-Teacher” model with ITA system support) and the control group (traditional teaching model). Data were collected through questionnaires, academic performance records, and engagement metrics, and were analyzed using statistical methods analysis. The experimental group showed significantly improved learning experience, engagement, and academic performance. The ITA system's personalized learning paths, Q&amp;A, and emotional support enhanced motivation and participation. The ITA system effectively addresses the limitations of traditional online courses, improving student outcomes. Future research will focus on refining algorithms, expanding applications, and enhancing emotional support features.</p>\u0000 </div>","PeriodicalId":50643,"journal":{"name":"Computer Applications in Engineering Education","volume":"33 6","pages":""},"PeriodicalIF":2.2,"publicationDate":"2025-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145406644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Designing Earthquake-Resistant Buildings With Karamba3D: A Method for Teaching Indonesian Architecture Students","authors":"Felicia Wagiri,&nbsp;Dany Perwita Sari","doi":"10.1002/cae.70097","DOIUrl":"https://doi.org/10.1002/cae.70097","url":null,"abstract":"<div>\u0000 \u0000 <p>The design and implementation of seismic structures in architecture are essential for enhancing safety and accessibility during earthquakes. However, many Indonesian architecture students lack the skills to design and analyze earthquake-resistant buildings. This gap is especially concerning given Indonesia's high vulnerability to seismic events, where building safety and resilience are critical. This paper examines the introduction of instructional simulations in an undergraduate architecture program with a specialization in earthquake-resistant design, utilizing Rhino-Grasshopper software. The teaching methods focus on improving earthquake resistance through advanced computational modeling, with an emphasis on structural optimization and performance-based design. Applied to second-year students, this approach led to 80% of them effectively incorporating simulation tools into their project designs. This method offers a comprehensive framework for integrating earthquake-resistant design into architectural education, providing a practical guide for students in earthquake-prone regions like Indonesia.</p>\u0000 </div>","PeriodicalId":50643,"journal":{"name":"Computer Applications in Engineering Education","volume":"33 6","pages":""},"PeriodicalIF":2.2,"publicationDate":"2025-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145367046","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Who Is the Best Helper for University Students' Mathematical Creativity? A Quasi-Experimental Study of Human–ChatGPT, Human–Google, and Human–Human Co-Creation","authors":"Zhiwei Liu,&nbsp;Haode Zuo,&nbsp;Jue Feng,&nbsp;Yongjing Lu","doi":"10.1002/cae.70100","DOIUrl":"https://doi.org/10.1002/cae.70100","url":null,"abstract":"<div>\u0000 \u0000 <p>Recent studies suggest that working with ChatGPT can generate more creative outcomes than humans alone. However, does ChatGPT retain its creative edge when humans have access to alternative information sources, such as Google Search or a human peer. This study addressed this question through a quasi-experiment with 230 Chinese university students in three groups (the human–ChatGPT group, the human–Google group, and human–human dyads) and a mathematical creativity task. The results showed that the human–ChatGPT group generated the most flexible and fluent solutions, while the human–human group produced the most original solutions in solving mathematical creativity tasks. The human–human group accurately assessed their actual performance, while the human–ChatGPT group overestimated it, and the human–Google group underestimated it. Furthermore, the study revealed that the human–Google group encountered greater difficulties, invested more effort, and reported lower levels of interest compared to the human–human and human–ChatGPT groups. Students found Google less useful than ChatGPT and their human peers. Similarly, students also found Google less effective than ChatGPT and their peers in enhancing self-efficacy. These findings highlight the benefits of human–human and human–ChatGPT co-creation in fostering mathematical creativity and call for further research on how to combine human inspiration with ChatGPT support to enhance it.</p>\u0000 </div>","PeriodicalId":50643,"journal":{"name":"Computer Applications in Engineering Education","volume":"33 6","pages":""},"PeriodicalIF":2.2,"publicationDate":"2025-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145366864","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Integrated Framework for Automated Measurement and Prediction of Program Outcome Attainment in Engineering Education","authors":"Selcan Kaplan Berkaya,&nbsp;Zeynep Batmaz,&nbsp;Mehmet Kilicarslan,&nbsp;Serkan Gunal","doi":"10.1002/cae.70094","DOIUrl":"https://doi.org/10.1002/cae.70094","url":null,"abstract":"<div>\u0000 \u0000 <p>Program Outcomes (POs) are critical for engineering program accreditation, yet traditional evaluation methods often lack objectivity, consistency, and timely feedback. While machine learning (ML) has been applied to predict general student success, its use for predicting PO attainment levels from early academic data remains underexplored. This study introduces an integrated framework for computer engineering programs, combining a systematic PO assessment model with ML-driven prediction. The assessment model quantifies PO attainment rates (POAR) from weighted course assessments, mappings between Course Learning Outcomes (CLOs) and POs, CLO-assessment relationships, and student grades. Using these POARs, various ML techniques were trained on historical data from 327 graduates, utilizing their grades from 25 early-semester courses and graduation POARs. Our findings demonstrate that POARs can be successfully predicted from this early data, achieving a mean absolute percentage error around 5%. Consequently, this study presents a scalable and objective tool that (1) provides a systematic framework for POAR measurement; (2) offers an effective ML model for predicting graduation POARs of students; and (3) delivers data-driven insights for proactive student support, timely interventions, and evidence-based curriculum optimization, thereby supporting continuous program improvement and accreditation efforts.</p></div>","PeriodicalId":50643,"journal":{"name":"Computer Applications in Engineering Education","volume":"33 6","pages":""},"PeriodicalIF":2.2,"publicationDate":"2025-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145366863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Teaching Variables Interaction Effects Through a Battery-Aging Case Study in Undergraduate Engineering","authors":"Daniela Galatro,&nbsp;Berhane Bein Sertu,&nbsp;Sourojeet Chakraborty","doi":"10.1002/cae.70099","DOIUrl":"https://doi.org/10.1002/cae.70099","url":null,"abstract":"<div>\u0000 \u0000 <p>When performing mathematical modeling, engineering education primarily focuses on understanding first principles to represent a phenomenon or process. With the advent of Machine Learning (ML), data-driven approaches to mathematical models have disrupted and challenged these traditional teaching/learning approaches. Data interpretability captures different dimensions, since engineers seek accurate predictions, causation, and analyze the interaction effects of process variables when modeling. While the effects of interaction effects have been previously taught using regression techniques, complex datasets might require employing alternative methods to precisely capture the complexity and nonlinear behavior. In this study, we present the conscious design of a novel teaching and learning approach for data-driven modeling, using a case study of the degradation of lithium-ion batteries to illustrate the interaction effects in modeling. We have selected there different interaction effects approaches when modeling: a regression model, exploratory data analysis, and ML. A validation and preassessment of the proposed teaching strategy were conducted to enhance the preparation and implementation of an in-class session, including strategies for its classroom integration. Our approach is innovative within the undergraduate engineering education context, since it introduces and highlights the significance of interaction effects to enhance students' abilities to interpret data, and think critically. This approach is totally reproducible, may be applied across other engineering disciplines, and has practical implications that could lead to its potential assimilation and utilization in industry.</p>\u0000 </div>","PeriodicalId":50643,"journal":{"name":"Computer Applications in Engineering Education","volume":"33 6","pages":""},"PeriodicalIF":2.2,"publicationDate":"2025-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145366311","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Pythagorean Academy Application—Design, Development, Implementation, and Evaluation of a Mobile Game for the Junior High School Geometry","authors":"Dimitra Tzoumpa,&nbsp;Eleni Seralidou,&nbsp;Athanasios Alougdelis,&nbsp;Christos Douligeris","doi":"10.1002/cae.70093","DOIUrl":"https://doi.org/10.1002/cae.70093","url":null,"abstract":"<div>\u0000 \u0000 <p>Educational mobile game applications can effectively support learning by offering engaging ways to present difficult concepts. This is especially beneficial for teaching secondary school Geometry, which many students find challenging. This paper introduces <i>Pythagorean Academy</i>, a mobile app aligned with the Greek junior high school curriculum. The app not only tests students' understanding but also provides corrective feedback and theory explanations—features uncommon in educational apps. It also accommodates students with visual impairments and learning disabilities, such as Attention Deficit Hyperactivity Disorder, through tailored visuals and audio support. Incorporating gamification elements, the app boosts motivation and promotes autonomous learning, making Geometry more accessible and enjoyable. Statistical methods, including the Mann–Whitney <i>U</i>-test and the Wilcoxon signed rank test, evaluate the app's effectiveness. This study demonstrates how integrating Geometry concepts into a gaming framework can leverage modern technology to improve Geometry education.</p>\u0000 </div>","PeriodicalId":50643,"journal":{"name":"Computer Applications in Engineering Education","volume":"33 6","pages":""},"PeriodicalIF":2.2,"publicationDate":"2025-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145366391","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CADuBoost: Enhancing Education in Mechanical 3D CAD Modeling Through Automated Grading and Feedback System","authors":"Yeongjun Yoon,&nbsp;Yeseong Jeon,&nbsp;Jaeyeon Kim,&nbsp;Seohui Han,&nbsp;Hyungki Kim,&nbsp;Soonjo Kwon","doi":"10.1002/cae.70096","DOIUrl":"https://doi.org/10.1002/cae.70096","url":null,"abstract":"<div>\u0000 \u0000 <p>3D CAD modeling technology has become an essential tool for product design across various industries, including machinery, aerospace, automotive, architecture, and healthcare. Consequently, numerous educational institutions offer training programs and certification exams to enhance and evaluate the modeling proficiency of 3D CAD system users. However, the manual grading process currently employed in 3D CAD modeling exams reveals several limitations, such as excessive time and effort, and challenges in maintaining consistency in evaluations. In mechanical CAD systems, in particular, users can create the same model using different features, making precise grading criteria essential. Additionally, the lack of self-directed learning capabilities among learners has emerged as a pressing issue, highlighting the need for more effective educational solutions. To address these challenges, this study introduces CADuBoost, an automated grading and feedback system for 3D CAD modeling education in mechanical engineering. CADuBoost compares student-submitted 3D CAD models with reference models through a comprehensive evaluation framework that processes both geometric and non-geometric data. Shape evaluation is conducted using neutral formats such as STEP and STL through point cloud comparison, multi-view image analysis, and dimensional accuracy measurement. Non-geometric evaluation is performed by extracting and analyzing design history and constraint information via the 3D CAD system's API. Furthermore, by providing visual feedback through color-coded geometric differences and detailed design history analysis, the system delivers personalized feedback that effectively fosters self-directed learning. The effectiveness of CADuBoost was validated through experiments in real educational settings, showing possibilities to improving students' modeling proficiency and self-directed learning abilities. This system is expected to enhance instructors' efficiency and improve the overall quality of education.</p></div>","PeriodicalId":50643,"journal":{"name":"Computer Applications in Engineering Education","volume":"33 6","pages":""},"PeriodicalIF":2.2,"publicationDate":"2025-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145366399","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}