Julie P. Martin, Isabel Miller, Karin J. Jensen, Deepthi E. Suresh
{"title":"A Social Network Analysis of Faculty Mentees Funded by the Research Initiation in Engineering Formation (RIEF) Program","authors":"Julie P. Martin, Isabel Miller, Karin J. Jensen, Deepthi E. Suresh","doi":"10.1109/te.2024.3436560","DOIUrl":"https://doi.org/10.1109/te.2024.3436560","url":null,"abstract":"","PeriodicalId":55011,"journal":{"name":"IEEE Transactions on Education","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2024-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142218942","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Contribution: This study synthesizes insights into the thematic focuses and linguistic attributes that resonate most in engineering faculty collaborations aimed at fostering entrepreneurial mindsets (EMs). It provides a roadmap for educators and institutions to effectively communicate and encourage entrepreneurial thinking in engineering. Background: Amid the heightened emphasis on entrepreneurial thinking in engineering education, understanding the factors that resonate with faculty is pivotal for informing curriculum development, aligning with global trends, and optimizing the preparedness of engineering graduates. Research Questions: 1) What elements of the EM are most frequently emphasized by faculty in their shared educational content? 2) What aspects of the EM resonate most with academic faculty? and 3) How do these relations differ in the electrical or computer engineering disciplines compared to other engineering fields? Methodology: A comprehensive analysis of educational resources shared by faculty on EM was conducted. The study used text analytics to assess engagement metrics, such as views, shares, favorites, and downloads. The data were analyzed using Stata. Findings: Faculty engagement strongly resonates with the three core components of the EM: Curiosity, Connections, and Creating Value, often emphasized in their shared educational content. Specifically, the “Creating Value” component emerged as the most significant across most engagement measures, with nuanced variations in the electrical and computer engineering disciplines.
贡献：本研究综述了旨在培养创业思维（EMs）的工程学教师合作中最能引起共鸣的主题重点和语言属性。它为教育工作者和机构提供了一个路线图，以便在工程学领域有效交流和鼓励创业思维。背景：在工程学教育越来越重视创业思维的背景下，了解与教师产生共鸣的因素，对于指导课程开发、与全球趋势接轨以及优化工程学毕业生的培养至关重要。研究问题1) 在共同的教学内容中，教师们最常强调哪些创业元素？2) 教育管理的哪些方面最能引起学术教师的共鸣？ 3) 与其他工程领域相比，电子或计算机工程学科的这些关系有何不同？研究方法：对教师在 EM 上共享的教育资源进行了全面分析。该研究使用文本分析来评估参与度指标，如浏览量、分享量、收藏量和下载量。数据使用 Stata 进行分析。研究结果教师的参与与教育网络的三个核心要素产生了强烈共鸣：好奇心、联系和创造价值，这三个要素在他们分享的教育内容中经常得到强调。具体而言，"创造价值 "是大多数参与度测量中最重要的组成部分，在电气和计算机工程学科中存在细微差别。
{"title":"Words That Resonate: Synthesizing Insights From Engineering Faculty Collaboration on Entrepreneurial Mindset","authors":"Agnieszka Kwapisz;Brock J. LaMeres","doi":"10.1109/TE.2024.3416866","DOIUrl":"10.1109/TE.2024.3416866","url":null,"abstract":"Contribution: This study synthesizes insights into the thematic focuses and linguistic attributes that resonate most in engineering faculty collaborations aimed at fostering entrepreneurial mindsets (EMs). It provides a roadmap for educators and institutions to effectively communicate and encourage entrepreneurial thinking in engineering. Background: Amid the heightened emphasis on entrepreneurial thinking in engineering education, understanding the factors that resonate with faculty is pivotal for informing curriculum development, aligning with global trends, and optimizing the preparedness of engineering graduates. Research Questions: 1) What elements of the EM are most frequently emphasized by faculty in their shared educational content? 2) What aspects of the EM resonate most with academic faculty? and 3) How do these relations differ in the electrical or computer engineering disciplines compared to other engineering fields? Methodology: A comprehensive analysis of educational resources shared by faculty on EM was conducted. The study used text analytics to assess engagement metrics, such as views, shares, favorites, and downloads. The data were analyzed using Stata. Findings: Faculty engagement strongly resonates with the three core components of the EM: Curiosity, Connections, and Creating Value, often emphasized in their shared educational content. Specifically, the “Creating Value” component emerged as the most significant across most engagement measures, with nuanced variations in the electrical and computer engineering disciplines.","PeriodicalId":55011,"journal":{"name":"IEEE Transactions on Education","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142218943","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Contribution: This article provides an examination of changes in first-year engineering students’ perceptions of the role of an engineer after completing the Engineers Without Borders Challenge. Background: Essential pre- and post-comparisons missing in existing studies on the Challenge are provided, as well as comparison to other first-year project types across two universities. Research Question: Do students who participate in service-learning versus traditional project-based learning gain different understandings of the role of an engineer? Methodology: This work implements the questionnaire variant of convergent mixed methods design. A survey containing a mix of Likert-scale, open-ended short answer, and closed card sorting questions was administered to students enrolled in first-year engineering (FYE) courses across two institutions. Limitations of this work include potential bias due to the pre/post survey design and participant course self-selection. Findings: Students’ perceptions of the roles of engineers did not significantly differ by project type. However, changes in their perceptions of technical skills as important to the role of engineers did indicate the beginning of a transition from discipline level thinking to process level thinking. Additionally, course learning objectives influenced students’ perceptions of the role of engineers—with an increase in awareness of the importance of problem solving, communication, design process, and teamwork and a decreasing sense of importance of items missing from course objectives, such as creativity and helping people. Engineers’ professional responsibility to diversity, equity, and inclusion were absent from both the course syllabi and student perceptions of the role of an engineer.
{"title":"First-Year Design Projects and Student Perceptions of the Role of an Engineer","authors":"Amanda Singer;Stacie Aguirre-Jaimes;Antonique White;Margot Vigeant;Michelle Jarvie-Eggart","doi":"10.1109/TE.2024.3406221","DOIUrl":"10.1109/TE.2024.3406221","url":null,"abstract":"Contribution: This article provides an examination of changes in first-year engineering students’ perceptions of the role of an engineer after completing the Engineers Without Borders Challenge. Background: Essential pre- and post-comparisons missing in existing studies on the Challenge are provided, as well as comparison to other first-year project types across two universities. Research Question: Do students who participate in service-learning versus traditional project-based learning gain different understandings of the role of an engineer? Methodology: This work implements the questionnaire variant of convergent mixed methods design. A survey containing a mix of Likert-scale, open-ended short answer, and closed card sorting questions was administered to students enrolled in first-year engineering (FYE) courses across two institutions. Limitations of this work include potential bias due to the pre/post survey design and participant course self-selection. Findings: Students’ perceptions of the roles of engineers did not significantly differ by project type. However, changes in their perceptions of technical skills as important to the role of engineers did indicate the beginning of a transition from discipline level thinking to process level thinking. Additionally, course learning objectives influenced students’ perceptions of the role of engineers—with an increase in awareness of the importance of problem solving, communication, design process, and teamwork and a decreasing sense of importance of items missing from course objectives, such as creativity and helping people. Engineers’ professional responsibility to diversity, equity, and inclusion were absent from both the course syllabi and student perceptions of the role of an engineer.","PeriodicalId":55011,"journal":{"name":"IEEE Transactions on Education","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10633790","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142218944","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"IEEE Transactions on Education Information for Authors","authors":"","doi":"10.1109/TE.2024.3426182","DOIUrl":"10.1109/TE.2024.3426182","url":null,"abstract":"","PeriodicalId":55011,"journal":{"name":"IEEE Transactions on Education","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10631815","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141937425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"IEEE Transactions on Education Publication Information","authors":"","doi":"10.1109/TE.2024.3426180","DOIUrl":"10.1109/TE.2024.3426180","url":null,"abstract":"","PeriodicalId":55011,"journal":{"name":"IEEE Transactions on Education","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10631813","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141937433","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Shannon Chance;Farrah Fayyaz;Anita L. Campbell;Nicole P. Pitterson;Sadia Nawaz
Understanding mathematics is essential for learning many concepts in engineering. Conceptual learning of engineering requires students to successfully connect abstract and concrete concepts to achieve a cohesive understanding of the content, and doing so goes beyond memorizing facts and applying formulas. Educators can observe that conceptual learning “has happened” once a student is able to successfully explain the concept, use the concept, and create new knowledge from the learned concept [1] . Moreover, a student’s ability to understand, both qualitatively and quantitatively, the mathematical equations and computations that describe various engineering processes and phenomena is necessary for the conceptual learning of many courses in engineering.
{"title":"Guest Editorial Special Issue on Conceptual Learning of Mathematics-Intensive Concepts in Engineering","authors":"Shannon Chance;Farrah Fayyaz;Anita L. Campbell;Nicole P. Pitterson;Sadia Nawaz","doi":"10.1109/TE.2024.3416649","DOIUrl":"10.1109/TE.2024.3416649","url":null,"abstract":"Understanding mathematics is essential for learning many concepts in engineering. Conceptual learning of engineering requires students to successfully connect abstract and concrete concepts to achieve a cohesive understanding of the content, and doing so goes beyond memorizing facts and applying formulas. Educators can observe that conceptual learning “has happened” once a student is able to successfully explain the concept, use the concept, and create new knowledge from the learned concept \u0000<xref>[1]</xref>\u0000. Moreover, a student’s ability to understand, both qualitatively and quantitatively, the mathematical equations and computations that describe various engineering processes and phenomena is necessary for the conceptual learning of many courses in engineering.","PeriodicalId":55011,"journal":{"name":"IEEE Transactions on Education","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10631814","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141937427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Contributions: An adoption framework to include generative artificial intelligence (GenAI) in the university curriculum. It identifies and highlights the role of different stakeholders (university management, students, staff, etc.) during the adoption process. It also proposes an objective approach based upon an evaluation matrix to assess the success and outcome of the GenAI adoption. Background: Universities worldwide are debating and struggling with the adoption of GenAI in their curriculum. GenAI has impacted our perspective on traditional methods of academic integrity and the scholarship of teaching, learning, and research. Both the faculty and students are unsure about the approach in the absence of clear guidelines through the administration and regulators. This requires an established framework to define a process and articulate the roles and responsibilities of each stakeholder involved. Research Questions: Whether the academic ecosystem requires a methodology to adopt GenAI into its curriculum? A systematic approach for the academic staff to ensure the students’ learning outcomes are met with the adoption of GenAI. How to measure and communicate the adoption of GenAI in the university setup? Methodology: The methodology employed in this study focuses on examining the university education system and assessing the opportunities and challenges related to incorporating GenAI in teaching and learning. Additionally, it identifies a gap and the absence of a comprehensive framework that obstructs the effective integration of GenAI within the academic environment. Findings: The literature survey results indicate the limited or no adoption of GenAI by the university, which further reflects the dilemma in the minds of different stakeholders. For the successful adoption of GenAI, a standard framework is proposed 1) for effective redesign of the course curriculum; 2) for enabling staff and students; and 3) to define an evaluation matrix to measure the effectiveness and success of the adoption process.
{"title":"Framework for Adoption of Generative Artificial Intelligence (GenAI) in Education","authors":"Samar Shailendra;Rajan Kadel;Aakanksha Sharma","doi":"10.1109/TE.2024.3432101","DOIUrl":"10.1109/TE.2024.3432101","url":null,"abstract":"Contributions: An adoption framework to include generative artificial intelligence (GenAI) in the university curriculum. It identifies and highlights the role of different stakeholders (university management, students, staff, etc.) during the adoption process. It also proposes an objective approach based upon an evaluation matrix to assess the success and outcome of the GenAI adoption. Background: Universities worldwide are debating and struggling with the adoption of GenAI in their curriculum. GenAI has impacted our perspective on traditional methods of academic integrity and the scholarship of teaching, learning, and research. Both the faculty and students are unsure about the approach in the absence of clear guidelines through the administration and regulators. This requires an established framework to define a process and articulate the roles and responsibilities of each stakeholder involved. Research Questions: Whether the academic ecosystem requires a methodology to adopt GenAI into its curriculum? A systematic approach for the academic staff to ensure the students’ learning outcomes are met with the adoption of GenAI. How to measure and communicate the adoption of GenAI in the university setup? Methodology: The methodology employed in this study focuses on examining the university education system and assessing the opportunities and challenges related to incorporating GenAI in teaching and learning. Additionally, it identifies a gap and the absence of a comprehensive framework that obstructs the effective integration of GenAI within the academic environment. Findings: The literature survey results indicate the limited or no adoption of GenAI by the university, which further reflects the dilemma in the minds of different stakeholders. For the successful adoption of GenAI, a standard framework is proposed 1) for effective redesign of the course curriculum; 2) for enabling staff and students; and 3) to define an evaluation matrix to measure the effectiveness and success of the adoption process.","PeriodicalId":55011,"journal":{"name":"IEEE Transactions on Education","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141937428","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Contributions: In this article, a generative artificial intelligence (AI)-based Q&A system has been developed by integrating information retrieval and natural language processing techniques, using course materials as a knowledge base and facilitating real-time student interaction through a chat interface. Background: The rise of advanced AI exemplified by ChatGPT developed by OpenAI, has sparked interest in its application within higher education. AI has the potential to reshape education delivery through chatbots and related tools, improving remote learning and mitigating challenges, such as student isolation and educator administrative burdens. Yet, ChatGPT’s practical applications in education remain uncertain, potentially due to its novel and enigmatic nature. Additionally, current e-learning chatbot systems often suffer from development complexity and a lack of input from key stakeholders, leading to developer-focused solutions rather than user-centered ones. Intended Outcomes: In this manuscript, we introduce a practical implementation of AI in education by creating a system called Q-Module-Bot that is accessible for both technical and nontechnical educators to harness e-learning benefits and demystify generative pretraining transformer (GPT). Application Design: The proposed Q-Module-Bot system has utilized pretrained large language models (LLMs) to build a Q&A system that helps students with their queries and supports education delivery using content extracted from a virtual learning environment (VLE). Findings: The prototype and system evaluation confirm the effectiveness of a scalable cross-departmental tool featuring source attribution and real-time responses. While successful in encouraging wider acceptance of GPT use cases in higher education, refinements are needed for full integration into the VLE and expansion to other modules/courses.
{"title":"Q-Module-Bot: A Generative AI-Based Question and Answer Bot for Module Teaching Support","authors":"Mia Allen;Usman Naeem;Sukhpal Singh Gill","doi":"10.1109/TE.2024.3435427","DOIUrl":"10.1109/TE.2024.3435427","url":null,"abstract":"Contributions: In this article, a generative artificial intelligence (AI)-based Q&A system has been developed by integrating information retrieval and natural language processing techniques, using course materials as a knowledge base and facilitating real-time student interaction through a chat interface. Background: The rise of advanced AI exemplified by ChatGPT developed by OpenAI, has sparked interest in its application within higher education. AI has the potential to reshape education delivery through chatbots and related tools, improving remote learning and mitigating challenges, such as student isolation and educator administrative burdens. Yet, ChatGPT’s practical applications in education remain uncertain, potentially due to its novel and enigmatic nature. Additionally, current e-learning chatbot systems often suffer from development complexity and a lack of input from key stakeholders, leading to developer-focused solutions rather than user-centered ones. Intended Outcomes: In this manuscript, we introduce a practical implementation of AI in education by creating a system called Q-Module-Bot that is accessible for both technical and nontechnical educators to harness e-learning benefits and demystify generative pretraining transformer (GPT). Application Design: The proposed Q-Module-Bot system has utilized pretrained large language models (LLMs) to build a Q&A system that helps students with their queries and supports education delivery using content extracted from a virtual learning environment (VLE). Findings: The prototype and system evaluation confirm the effectiveness of a scalable cross-departmental tool featuring source attribution and real-time responses. While successful in encouraging wider acceptance of GPT use cases in higher education, refinements are needed for full integration into the VLE and expansion to other modules/courses.","PeriodicalId":55011,"journal":{"name":"IEEE Transactions on Education","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141937429","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
José A. Ballesteros;Marcos D. Fernandez;José L. González-Geraldo
Contribution: A peer-mentoring plan designed to support engineering students during their transition from high school to university. This article addresses the adaptation challenges faced by first-year students in engineering programs. Background: The transition to university is a critical period for students, marked by significant lifestyle changes and the inherent difficulties of engineering degrees. This often results in high stress levels, with some students struggling to adapt and consequently dropping out. Previous efforts to support students have shown varying degrees of success, highlighting the need for effective peer support mechanisms. Intended Outcomes: A structured peer-mentoring environment aimed at reducing stress, improving first-year students’ adaptation to university life, and decreasing dropout rates. The program is designed to be well received by both mentors and mentees, thereby enhancing the academic experience for engineering students. Application Design: Drawing on existing teaching experiences and literature, the proposed peer-mentoring program involves senior students acting as mentors to first-year students. The program begins with a training session to equip mentors with necessary tools and to define their roles and boundaries. This is followed by an initial meeting during the welcome day, and continues with formal and informal interactions throughout the first semester, under the supervision of the degree coordinator. Findings: Surveys completed by both mentors and first-year students indicate a high level of acceptance and perceived usefulness of the peer-mentoring program. The results suggest that the program effectively supports first-year students in their transition to university life, with strong recommendations for its continuation in future academic years.
{"title":"Peer-Mentoring Program for the Individual Attention of Engineering Students","authors":"José A. Ballesteros;Marcos D. Fernandez;José L. González-Geraldo","doi":"10.1109/TE.2024.3432830","DOIUrl":"10.1109/TE.2024.3432830","url":null,"abstract":"Contribution: A peer-mentoring plan designed to support engineering students during their transition from high school to university. This article addresses the adaptation challenges faced by first-year students in engineering programs. Background: The transition to university is a critical period for students, marked by significant lifestyle changes and the inherent difficulties of engineering degrees. This often results in high stress levels, with some students struggling to adapt and consequently dropping out. Previous efforts to support students have shown varying degrees of success, highlighting the need for effective peer support mechanisms. Intended Outcomes: A structured peer-mentoring environment aimed at reducing stress, improving first-year students’ adaptation to university life, and decreasing dropout rates. The program is designed to be well received by both mentors and mentees, thereby enhancing the academic experience for engineering students. Application Design: Drawing on existing teaching experiences and literature, the proposed peer-mentoring program involves senior students acting as mentors to first-year students. The program begins with a training session to equip mentors with necessary tools and to define their roles and boundaries. This is followed by an initial meeting during the welcome day, and continues with formal and informal interactions throughout the first semester, under the supervision of the degree coordinator. Findings: Surveys completed by both mentors and first-year students indicate a high level of acceptance and perceived usefulness of the peer-mentoring program. The results suggest that the program effectively supports first-year students in their transition to university life, with strong recommendations for its continuation in future academic years.","PeriodicalId":55011,"journal":{"name":"IEEE Transactions on Education","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10620217","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141884396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Daniel Escanez-Exposito, Javier Correa-Marichal, Pino Caballero-Gil
{"title":"Using Game-Based Learning and Quantum Computing to Enhance STEAM Competencies in K-16 Education","authors":"Daniel Escanez-Exposito, Javier Correa-Marichal, Pino Caballero-Gil","doi":"10.1109/te.2024.3422315","DOIUrl":"https://doi.org/10.1109/te.2024.3422315","url":null,"abstract":"","PeriodicalId":55011,"journal":{"name":"IEEE Transactions on Education","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141871483","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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