Computer Applications in Engineering Education最新文献

{"title":"A Comparison of the Programming-Oriented Computational Thinking Skills of Engineering and Nonengineering Students at Turkish Universities","authors":"Nihal Menzi Çetin","doi":"10.1002/cae.70069","DOIUrl":"https://doi.org/10.1002/cae.70069","url":null,"abstract":"<div>\u0000 \u0000 <p>This study examines the programming-oriented computational thinking (PoCT) skills of engineering and nonengineering faculty students, comparing them in terms of grade level and the three subdimensions of PoCT: Conceptual knowledge, algorithmic thinking, and evaluation. Additionally, the study investigates the extent to which students' PoCT skill levels can be predicted by programming language self-efficacy and design thinking skill through hierarchical regression analysis. The data of 571 computer science students from two types of faculties in Turkish universities were analysed. The findings revealed that engineering students had superior computational thinking skills to their nonengineering counterparts, as well as a slightly higher predictive power of programming self-efficacy and design thinking on computational thinking. These results offer valuable insights and strategies for developing instructional practices that address the disadvantages faced by nonengineering disciplines.</p>\u0000 </div>","PeriodicalId":50643,"journal":{"name":"Computer Applications in Engineering Education","volume":"33 5","pages":""},"PeriodicalIF":2.2,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144751448","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":"Development and Evaluation of an Educational Environment for Designing Hardware Architectures of Support Vector Machines-Based Classifiers","authors":"Enrique Guzmán-Ramírez,&nbsp;Ivan Garcia,&nbsp;Carla Pacheco,&nbsp;Esteban Guerrero-Ramírez","doi":"10.1002/cae.70068","DOIUrl":"https://doi.org/10.1002/cae.70068","url":null,"abstract":"<div>\u0000 \u0000 <p>In an increasingly complex world where increased interactions between users and systems are taking place and a greater amount of information must be processed, Machine Learning techniques are becoming increasingly relevant as they help researchers to generalize how the different variables in a process are related and, consequently, reduce the margin of error in the estimation of results. One of these techniques is Support Vector Machines (SVM), which are characterized for being simple, flexible, and computationally efficient. They are also useful for classifying and analyzing data for regression tasks in multiple areas such as natural language processing, image classification, bioinformatics, signal processing, as well as robotic systems. In this regard, several current studies have optimized performance and cost by implementing SVM in hardware, particularly on Field-Programmable Gate Array (FPGA) as they are suitable for dealing with challenging embedded system constraints. Consequently, undergraduates must be familiarized with this approach to be more competitive when entering the labor market in the real industry. Therefore, it is imperative to create teaching alternatives that provide practical knowledge about SVM, not only from a software perspective, but also on the design and modeling of hardware architectures that describe their structure and can be implemented in a specific device. With this aim in mind, this study presents a <i>learning-by-doing</i> educational approach for teaching the principles of SVM by promoting their modeling, implementation, and evaluation on FPGAs. Furthermore, the results derived from an empirical evaluation on 55 undergraduates from the Universidad Tecnológica de la Mixteca, México, provided evidence that the proposed approach can stimulate the development of skills required in the labor market related to the design and modeling of hardware architectures and, at the same time, allows students to undertake design challenges involving SVM and reconfigurable logic.</p>\u0000 </div>","PeriodicalId":50643,"journal":{"name":"Computer Applications in Engineering Education","volume":"33 5","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144716878","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 Impact and Pathways of Digital Game-Based Learning on STEM Undergraduates' Engineering Concepts: Integrating Self-Determination Theory and Flow Theory","authors":"Yuqing Chen,&nbsp;Qing Guo,&nbsp;Qihan Qiu,&nbsp;Cuilan Qiao,&nbsp;Jingying Wang","doi":"10.1002/cae.70066","DOIUrl":"https://doi.org/10.1002/cae.70066","url":null,"abstract":"<div>\u0000 \u0000 <p>Game-based learning (GBL) has demonstrated effectiveness across various disciplines, yet its application in engineering education remains limited. Understanding engineering concepts is essential not only for engineering students but for all STEM undergraduates. This study investigates the potential of GBL to enhance STEM students' comprehension of engineering concepts, and explores the underlying influence pathways by integrating self-determination theory (SDT), flow theory (FT), and personal gaming history. Structural equation modeling was employed to analyze the relationships among these variables. Results indicate that completing game tasks significantly improves students' understanding of engineering concepts. Among the influence pathways, need frustration emerged as a major barrier (path coefficient = −0.355), while need satisfaction strongly promoted both flow experience (0.779) and game motivation (0.703). Additionally, personal gaming experience, flow experience, and game motivation positively influenced game satisfaction (path coefficients = 0.114, 0.559, and 0.329, respectively). These findings support the effectiveness of GBL in engineering education. To optimize learning outcomes, game design and use should address students' basic psychological needs, minimize need frustration, and foster flow and motivation, thereby enhancing engagement and conceptual understanding.</p></div>","PeriodicalId":50643,"journal":{"name":"Computer Applications in Engineering Education","volume":"33 4","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144688098","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":"Application of Visual Teaching in Engineering Geology","authors":"Junyi Gao,&nbsp;Zhiqiang Zhou","doi":"10.1002/cae.70067","DOIUrl":"https://doi.org/10.1002/cae.70067","url":null,"abstract":"<div>\u0000 \u0000 <p>Engineering Geology is a mandatory course for undergraduates majoring in civil engineering at colleges and universities, where much of the knowledge is inherently abstract. The teaching methods employed by instructors play a crucial role in helping students understand the course material. This study highlighted several effective visual teaching methods that facilitate students' comprehension of abstract geological concepts. It specifically discussed various visual teaching methods, including classroom object diagrams, classroom video playback, and field geological practices. Visual teaching methods for different slope models, tunnel models, and fractured rock mass models were developed using numerical software. An online questionnaire survey was conducted to assess the acceptance of these methods among second-year undergraduates. The results indicated that the combined effect of these methods was most favorable. Therefore, this visual teaching strategy holds promise for broader application in engineering geology education.</p>\u0000 </div>","PeriodicalId":50643,"journal":{"name":"Computer Applications in Engineering Education","volume":"33 4","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144666209","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":"Study on the Benefits of Virtual Reality as a Support for STEM Learning","authors":"Riccardo Giussani,&nbsp;Nicolò Dozio,&nbsp;Niccolò Becattini,&nbsp;Gaetano Cascini,&nbsp;Francesco Ferrise,&nbsp;Federico Morosi","doi":"10.1002/cae.70065","DOIUrl":"https://doi.org/10.1002/cae.70065","url":null,"abstract":"<div>\u0000 \u0000 <p>The use of virtual reality (VR) in higher education and training has been widely explored in various fields, with divergent results. This study examines whether VR is a suitable learning support tool compared to traditional methods, such as 2D static slides or physical models, focusing on usability, workload, and learning effectiveness in an engineering education context. A total of 184 first-year BSc engineering students voluntarily participated in an experimental activity. Participants were divided into three groups, each experiencing a different learning condition: slides-based, VR-based, and physical model-based. The study design ensured comparability across conditions using 3 out of 4 levels provided by the ICAP (Interactive, Constructive, Active, Passive) framework. Usability was assessed using the System Usability Scale, workload via the NASA Task Load Index, and learning outcomes through a task-based test. The study found no significant differences in test scores across the three conditions. However, participants in the VR-based and physical model-based conditions reported significantly higher usability and lower perceived workload compared to the slides-based condition. The VR-based condition provided an immersive environment while maintaining comparability in cognitive engagement. The findings demonstrate that VR can serve as an effective alternative to traditional learning methods, particularly for enhancing usability and reducing cognitive workload. However, its integration must be carefully designed to ensure cognitive engagement and optimize learning outcomes. This study highlights VR's potential in engineering education and underscores the importance of aligning tools with pedagogical goals.</p>\u0000 </div>","PeriodicalId":50643,"journal":{"name":"Computer Applications in Engineering Education","volume":"33 4","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144635566","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":"Evaluating the Success of AI Tools in Supporting Student Performance in Mathematical Kangaroo Competition","authors":"Marina Svičević,&nbsp;Aleksandar Milenković,&nbsp;Nemanja Vučićević,&nbsp;Marko Stanković","doi":"10.1002/cae.70063","DOIUrl":"https://doi.org/10.1002/cae.70063","url":null,"abstract":"<div>\u0000 \u0000 <p>This study explores the potential of generative artificial intelligence (AI) tools in supporting students preparing for mathematical competitions, focusing on the Mathematical Kangaroo competition in the context of the Serbian-speaking region. The research analyzed tools such as ChatGPT-free, ChatGPT-paid, AI Math Solver, Math Mentor, and o1-preview, assessing their accuracy and efficiency in solving tasks of varying difficulty levels and domains (algebra, geometry, logic, and numbers), as well as different formats (text and image-based). Testing included tasks in both Serbian and English, allowing for the evaluation of language barriers in tool performance. The results indicate that tools perform better with text-based task formats, with o1-preview standing out for its exceptionally high accuracy in this format. All tools achieve the highest precision in numbers and algebra, while results are significantly lower in geometry and logic, highlighting challenges in processing visual information and logical reasoning. The conclusions of this study emphasize the importance of generative AI in improving mathematics education but highlight the need for further development of tools that can better handle visual tasks, support local languages, and be more specialized in solving mathematical problems in general.</p>\u0000 </div>","PeriodicalId":50643,"journal":{"name":"Computer Applications in Engineering Education","volume":"33 4","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144582378","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":"Engineering Students' Perceptions and Use of Generative Artificial Intelligence","authors":"Johannes L. Jooste,&nbsp;Karin E. Wolff,&nbsp;Jan G. Joubert","doi":"10.1002/cae.70064","DOIUrl":"https://doi.org/10.1002/cae.70064","url":null,"abstract":"<p>This study explores the evolving landscape of generative artificial intelligence (GAI) in engineering education. With technologies like ChatGPT transforming academic practices, universities are experiencing related challenges with integration, ethics and academic integrity. This study was conducted at a South African university to gain insights into how engineering students use GAI applications and their perceptions of these applications in their academic study. Using a survey based on previous studies, data were collected from undergraduate and postgraduate engineering students. The results reveal widespread adoption of GAI applications, with preferences regarding appropriate use and regulation approaches. Students generally support GAI as a learning aid while also expressing concerns about its use in formal assessments. They prefer discipline-specific guidance over institutional policies, with only 1% supporting a complete ban on GAI use. The findings indicate significant interest in structured education about ethical GAI use, with many students planning to continue using these technologies in their future careers. This study provides insights for engineering educators working to balance innovation with academic integrity, highlighting the need for collaborative approaches between students and educators in engineering education to maximise GAI benefits while mitigating limitations. Future research should explore effective integration strategies and discipline-specific best practices as GAI capabilities continue to evolve.</p>","PeriodicalId":50643,"journal":{"name":"Computer Applications in Engineering Education","volume":"33 4","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cae.70064","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144582379","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":"Improving University Students' Learning of Programming Using Customised Pseudocode","authors":"Antonio López-García,&nbsp;Jaime Urquiza-Fuentes,&nbsp;António José Mendes,&nbsp;Manuel Caeiro-Rodríguez","doi":"10.1002/cae.70061","DOIUrl":"https://doi.org/10.1002/cae.70061","url":null,"abstract":"<p>Pseudocode is a well-known tool for introducing students to the basics of programming. The aim of pseudocode is to make algorithmic constructs easy to write and to understand. In this study, we propose the design of a ‘natural’ pseudocode, with keywords frequently used in the mother tongue, referring to basic computational instructions and execution flow control. The core premise underlying this study is that students will better develop their algorithmic skills if they use their own pseudocode, using their preferred keywords. This international study includes a sample of a total of 405 first-year university students from different university degree programmes related to computer science, 60 Portuguese students, 58 Galician students and 287 students from Madrid. The same study is carried out in the corresponding mother tongue (Portuguese, Galician and Spanish) and divided into two phases. In the first, students answered a seven-question survey on the design of the pseudocode language. The results of this phase indicate that most of the keywords generally used in traditional pseudocode are not among the students' preferences. In the second phase, a six-question comprehension questionnaire was used to assess the students' understanding of algorithmic constructions by comparing three alternatives: the natural pseudocode in the mother tongue that they had chosen in the previous phase, the frequently used classical or standard pseudocode (also in the mother tongue) and pseudocode in English. The results show higher levels of understanding when using natural pseudocode.</p>","PeriodicalId":50643,"journal":{"name":"Computer Applications in Engineering Education","volume":"33 4","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cae.70061","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144525058","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":"Navigating ChatGPT in ASEAN Higher Education: Ethical and Pedagogical Perspectives","authors":"Dipima Buragohain,&nbsp;Sushank Chaudhary","doi":"10.1002/cae.70062","DOIUrl":"https://doi.org/10.1002/cae.70062","url":null,"abstract":"<div>\u0000 \u0000 <p>The integration of generative artificial intelligence (AI) technologies, such as large language models like ChatGPT, in higher education has introduced innovative ways to enhance personalized learning, assist students, and support educators. However, these advancements come with significant ethical implications, particularly concerning privacy, bias, and pedagogy from a socio-technical perspective. This study explores the ethical dimensions of employing ChatGPT in higher educational systems across ASEAN countries. Employing a systematic literature review and thematic analysis of data from news articles, university policies, and journal papers, the research identifies key ethical concerns related to data privacy, algorithmic bias, and the impact on educational practices. Findings highlight the need for responsible generative AI usage and propose recommendations to ensure that ChatGPT and similar AI tools positively contribute to higher education while upholding academic integrity and equity from a socio-technical viewpoint.</p>\u0000 </div>","PeriodicalId":50643,"journal":{"name":"Computer Applications in Engineering Education","volume":"33 4","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144524964","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":"Advancing Civil Engineering Education: Implications of Using Augmented Reality in Teaching Structural Analysis","authors":"Nathan Miner,&nbsp;Aliye Karabulut-Ilgu,&nbsp;Charles Jahren,&nbsp;Alice Alipour","doi":"10.1002/cae.70059","DOIUrl":"https://doi.org/10.1002/cae.70059","url":null,"abstract":"<p>As technological advances appear, it is desirable to integrate them into new engineering education teaching methods, aiming to enhance students' comprehension and engagement with complex subjects. Augmented reality (AR) emerges as a promising tool in this effort, offering students opportunities to visualize and conceptualize challenging topics that are otherwise too abstract or difficult to grasp. Within civil engineering curriculums, structural analysis, a junior-level course forming the foundation of many other courses, poses challenges in visualization and understanding. This paper investigates the development of a mobile AR application intended to improve the conceptual understanding of structural analysis material. This application is designed to overlay schematic representations of structural components (i.e., beams, columns, frames, and trusses) onto images of iconic local campus buildings, allowing students to interactively explore exaggerated deflections and internal and external forces under various loading conditions. By contextualizing structural analysis calculations within familiar settings, the goal is to leverage a sense of relevance and place-based attachments in students' learning. Furthermore, the paper examines the development process and usability of the AR application, providing insights into its implementation in educational settings. Experimental results, including comparisons with a control group, are analyzed to assess the efficacy of the AR application in improving students' understanding of structural analysis concepts. Furthermore, the paper examines the development process and usability of the AR application, providing insights into its implementation in educational settings. Perspectives from structural analysis faculty members are also discussed, shedding light on the potential benefits and challenges associated with integrating AR technology into engineering education. In addition, the study highlights the value of place-based learning, wherein students engage with real-world structures in their immediate environment, fostering deeper connections between theoretical concepts and practical applications. Overall, this research contributes to the growing body of literature on innovative teaching approaches in engineering education and highlights the potential of AR as a valuable tool for enhancing student learning experiences in structural analysis and related disciplines.</p>","PeriodicalId":50643,"journal":{"name":"Computer Applications in Engineering Education","volume":"33 4","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cae.70059","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144482078","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}