Contribution: This study qualitatively uncovered meaning for why and what was motivating to undergraduates participating in an educational human—robot interaction (HRI) experience. A data corpus of four documents (groups) was evaluated from a quasi-experimental, nonequivalent control ( ${n},,=$ 23) and treatment ( ${n},,=$ 61) research design revealing three themes attributing meaning for why and what was motivating to students. Background: Engineering education literature has indicated a positive impact on student motivation and academic success from HRIs. However, rigorous research that attributes meaning for why and what are motivating to students in these HRI experiences is not readily available. Intended Outcomes: Results of this study represent substantial findings that answer questions of why and what are motivating in HRI experiences. However, future research is needed to further understand the nuanced dynamics and multidimensional aspects of motivation in HRIs. Application Design: To analyze the qualitative open-ended survey responses from students, structured term frequency (tf), tf – inverse document frequency (tf-idf), latent Dirichlet allocation (LDA) modeling, and content analysis were used, as these approaches are typical in computational text mining. Findings: When describing motivation toward the HRI, students were found to form a common lexicon to attribute why and what was motivating (e.g., “…[being] abl[e]” [to] see [the] robot follow [the line]…”). This suggests that the tangible, visual, immediate feedback experienced by students was why and what motivated them.
{"title":"Toward Uncovering Meaning in Human-Robot Interactions","authors":"John R. Haughery","doi":"10.1109/TE.2024.3384255","DOIUrl":"10.1109/TE.2024.3384255","url":null,"abstract":"Contribution: This study qualitatively uncovered meaning for why and what was motivating to undergraduates participating in an educational human—robot interaction (HRI) experience. A data corpus of four documents (groups) was evaluated from a quasi-experimental, nonequivalent control (\u0000<inline-formula> <tex-math>${n},,=$ </tex-math></inline-formula>\u0000 23) and treatment (\u0000<inline-formula> <tex-math>${n},,=$ </tex-math></inline-formula>\u0000 61) research design revealing three themes attributing meaning for why and what was motivating to students. Background: Engineering education literature has indicated a positive impact on student motivation and academic success from HRIs. However, rigorous research that attributes meaning for why and what are motivating to students in these HRI experiences is not readily available. Intended Outcomes: Results of this study represent substantial findings that answer questions of why and what are motivating in HRI experiences. However, future research is needed to further understand the nuanced dynamics and multidimensional aspects of motivation in HRIs. Application Design: To analyze the qualitative open-ended survey responses from students, structured term frequency (tf), tf – inverse document frequency (tf-idf), latent Dirichlet allocation (LDA) modeling, and content analysis were used, as these approaches are typical in computational text mining. Findings: When describing motivation toward the HRI, students were found to form a common lexicon to attribute why and what was motivating (e.g., “…[being] abl[e]” [to] see [the] robot follow [the line]…”). This suggests that the tangible, visual, immediate feedback experienced by students was why and what motivated them.","PeriodicalId":55011,"journal":{"name":"IEEE Transactions on Education","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140799326","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}
Marilena Bratu;Cristina Hava Muntean;Cristian Buică-Belciu;Sabina Stan;Gabriel-Miro Muntean
Contributions: This article presents the results of a study carried out as part of two large-scale pilots and analyzes the impact of the use of modern technologies in education in term of knowledge acquisition in case of students with hearing disabilities. Background: Teaching topics from STEM area is a challenging task for all teachers who have students with hearing disabilities in their class. On the one hand, because of the high degree of difficulty of the information in this field and on the other hand, because of the difficulties that students with hearing disabilities face in understanding this information. In this context, the use of modern technologies in education, but especially the way they are used together with traditional ones, can provide great support for teachers of students with special needs. Intended Outcomes: A set of modern technologies, i.e., virtual lab, virtual reality (VR), in the game-based learning context of the EU-funded NEWTON project, were employed in education as part of the Earth Course. The goal was to increase the accessibility of STEM information in the area of natural sciences for the benefit of students, especially those with hearing disabilities. Application Design: The study targeted secondary school students with hearing disabilities. Content related to natural sciences (i.e., wildlife and sealife) was presented as part of the Earth Course via innovative applications that included virtual laboratories and VR. Avatars were used to support the students with special needs (sign-language translation). Findings: The results of this study demonstrate that the use of modern technologies, combined with game-based learning in science lessons for students with hearing disabilities, contribute to increasing their knowledge level. The best results were obtained when these technologies were used in mixed lessons, alongside the traditional teaching methods.
贡献：本文介绍了作为两个大型试点项目的一部分而开展的一项研究的结果，并分析了在教育中使用现代技术对听力残疾学生获取知识的影响。研究背景对于班上有听力残疾学生的所有教师来说，STEM 领域的教学课题都是一项具有挑战性的任务。一方面是因为该领域的信息难度很大，另一方面是因为听力残疾学生在理解这些信息时面临困难。在这种情况下，在教育中使用现代技术，特别是将现代技术与传统技术结合起来使用的方式，可以为有特殊需要的学生的教师提供极大的支持。预期成果：在欧盟资助的 NEWTON 项目的游戏式学习背景下，一套现代技术，即虚拟实验室、虚拟现实 （VR），被应用于教育中，作为地球课程的一部分。其目的是提高自然科学领域 STEM 信息的可及性，使学生，尤其是听力有障碍的学生受益。应用设计：研究对象是有听力障碍的中学生。与自然科学（即野生动物和海豹）相关的内容作为地球课程的一部分，通过包括虚拟实验室和 VR 在内的创新应用进行展示。使用头像为有特殊需要的学生提供支持（手语翻译）。研究结果本研究的结果表明，在为听力残疾学生开设的科学课中使用现代技术，结合游戏式学习，有助于提高他们的知识水平。当这些技术与传统教学方法一起在混合课程中使用时，效果最好。
{"title":"Impact of NEWTON Technology-Enhanced Learning Solutions on Knowledge Acquisition in Pilots Involving Students With Hearing Impairments","authors":"Marilena Bratu;Cristina Hava Muntean;Cristian Buică-Belciu;Sabina Stan;Gabriel-Miro Muntean","doi":"10.1109/TE.2024.3378103","DOIUrl":"10.1109/TE.2024.3378103","url":null,"abstract":"Contributions: This article presents the results of a study carried out as part of two large-scale pilots and analyzes the impact of the use of modern technologies in education in term of knowledge acquisition in case of students with hearing disabilities. Background: Teaching topics from STEM area is a challenging task for all teachers who have students with hearing disabilities in their class. On the one hand, because of the high degree of difficulty of the information in this field and on the other hand, because of the difficulties that students with hearing disabilities face in understanding this information. In this context, the use of modern technologies in education, but especially the way they are used together with traditional ones, can provide great support for teachers of students with special needs. Intended Outcomes: A set of modern technologies, i.e., virtual lab, virtual reality (VR), in the game-based learning context of the EU-funded NEWTON project, were employed in education as part of the Earth Course. The goal was to increase the accessibility of STEM information in the area of natural sciences for the benefit of students, especially those with hearing disabilities. Application Design: The study targeted secondary school students with hearing disabilities. Content related to natural sciences (i.e., wildlife and sealife) was presented as part of the Earth Course via innovative applications that included virtual laboratories and VR. Avatars were used to support the students with special needs (sign-language translation). Findings: The results of this study demonstrate that the use of modern technologies, combined with game-based learning in science lessons for students with hearing disabilities, contribute to increasing their knowledge level. The best results were obtained when these technologies were used in mixed lessons, alongside the traditional teaching methods.","PeriodicalId":55011,"journal":{"name":"IEEE Transactions on Education","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2024-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140629200","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}
Fabiano Fruett;Fernanda Pereira Barbosa;Samuel Cardoso Zampolli Fraga;Pedro Ivo Aragão Guimarães
Open-source hardware and software platforms have played an important role in democratizing access to technology and education in computer science and engineering. Recent advancements in tools, such as KiCad, MicroPython, and Thonny, integrated development environment potentially accelerate low-budget educational applications, providing a smooth and consistent learning curve for users. The BitDogLab, utilizing these platforms, is designed and developed for Science, Technology, Engineering, Arts, and Mathematics activities based on the Raspberry Pi Pico Board, featuring artificial intelligence (AI)-supported programming via the GPT model. BitDogLab is an open-source hardware solution with a flexible design for continuous expansion in both software and hardware areas. Its functionality, based on open-source code, can be enhanced by integrating various software resources. Additionally, BitDogLab’s adaptability to sophisticated hardware like robotic systems or advanced sensors expands its educational applications. An evaluation of BitDogLab, conducted through a hands-on workshop at the Latin America Open Technology Conference—Latinoware 2023, revealed unanimous interest among 36 respondents, mainly for teaching programming (58%), and valuing its low cost, diverse components, and ease of AI-assisted programming. 75% of respondents expressed a strong desire to use BitDogLab, despite 19% preferring familiar boards like Arduino or Micro:bit. The project’s open distribution encourages community contributions, promoting collaborative learning and innovation from children to preuniversity students.
{"title":"Empowering STEAM Activities With Artificial Intelligence and Open Hardware: The BitDogLab","authors":"Fabiano Fruett;Fernanda Pereira Barbosa;Samuel Cardoso Zampolli Fraga;Pedro Ivo Aragão Guimarães","doi":"10.1109/TE.2024.3377555","DOIUrl":"10.1109/TE.2024.3377555","url":null,"abstract":"Open-source hardware and software platforms have played an important role in democratizing access to technology and education in computer science and engineering. Recent advancements in tools, such as KiCad, MicroPython, and Thonny, integrated development environment potentially accelerate low-budget educational applications, providing a smooth and consistent learning curve for users. The BitDogLab, utilizing these platforms, is designed and developed for Science, Technology, Engineering, Arts, and Mathematics activities based on the Raspberry Pi Pico Board, featuring artificial intelligence (AI)-supported programming via the GPT model. BitDogLab is an open-source hardware solution with a flexible design for continuous expansion in both software and hardware areas. Its functionality, based on open-source code, can be enhanced by integrating various software resources. Additionally, BitDogLab’s adaptability to sophisticated hardware like robotic systems or advanced sensors expands its educational applications. An evaluation of BitDogLab, conducted through a hands-on workshop at the Latin America Open Technology Conference—Latinoware 2023, revealed unanimous interest among 36 respondents, mainly for teaching programming (58%), and valuing its low cost, diverse components, and ease of AI-assisted programming. 75% of respondents expressed a strong desire to use BitDogLab, despite 19% preferring familiar boards like Arduino or Micro:bit. The project’s open distribution encourages community contributions, promoting collaborative learning and innovation from children to preuniversity students.","PeriodicalId":55011,"journal":{"name":"IEEE Transactions on Education","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140563898","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}
The sample mean in statistics is a concept of great importance, with its properties being extensively utilized in other areas, such as computer science. This research centers on the concept of the sample mean and its characteristics in a cohort of computer engineering students undertaking a required course in statistics at a university in the Netherlands. The objective of this study was to analyze students’ comprehension of the fundamental structure, properties, and applications of the sample mean. A digital mini-course on sample mean was developed and employed with 97 students, who had the option to apply the concepts at their own pace. The action-process-object-schema (APOS) theoretical framework was utilized to analyze the interview responses of seven participants. The majority of participants were able to demonstrate an understanding of the Process conception of the sample mean, with only a minority demonstrating an understanding of the Object conception. The lack of comprehension of the sample mean hindered students’ capacity to effectively utilize the associated applications and properties. These findings imply that educators should strive to ensure that students have a sound comprehension of the sample mean so that they are better equipped to work with related applications. Suggestions of this study and further research ideas are indicated.
{"title":"Conceptualizing the Sample Mean: Insights for Computer Engineering Students in the Learning Process","authors":"Fulya Kula;Nelly Litvak;Tracy S. Craig","doi":"10.1109/TE.2024.3376795","DOIUrl":"10.1109/TE.2024.3376795","url":null,"abstract":"The sample mean in statistics is a concept of great importance, with its properties being extensively utilized in other areas, such as computer science. This research centers on the concept of the sample mean and its characteristics in a cohort of computer engineering students undertaking a required course in statistics at a university in the Netherlands. The objective of this study was to analyze students’ comprehension of the fundamental structure, properties, and applications of the sample mean. A digital mini-course on sample mean was developed and employed with 97 students, who had the option to apply the concepts at their own pace. The action-process-object-schema (APOS) theoretical framework was utilized to analyze the interview responses of seven participants. The majority of participants were able to demonstrate an understanding of the Process conception of the sample mean, with only a minority demonstrating an understanding of the Object conception. The lack of comprehension of the sample mean hindered students’ capacity to effectively utilize the associated applications and properties. These findings imply that educators should strive to ensure that students have a sound comprehension of the sample mean so that they are better equipped to work with related applications. Suggestions of this study and further research ideas are indicated.","PeriodicalId":55011,"journal":{"name":"IEEE Transactions on Education","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140563340","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}
Roee Peretz;Natali Levi-Soskin;Dov Dori;Yehudit Judy Dori
Contribution: Model-based learning improves systems thinking (ST) based on students’ prior knowledge and gender. Relations were found between textual, visual, and mixed question types and student achievements. Background: ST is essential to judicious decision-making and problem-solving. Undergraduate students can be taught to apply better ST, and analysis of their online systems modeling processes can improve their ST. Research Questions: 1) What is the effect, if any, of online learning on the ST and conceptual modeling skill levels of undergraduate engineering students? 2) What differences are there, if any, between students’ ST, conceptual modeling, and scores in textual, visual, and mixed question types based on their prior knowledge levels? and 3) Are there any gender differences in student performance, and if so, what are they? Methodology: The research participants were 157 undergraduate engineering students who took part in a mandatory second-year course, during which data were collected and analyzed quantitatively. Findings: Students with disparate prior knowledge differed significantly from each other in their overall ST mean score and in the mean scores of the various question types. Gender differences in ST and its relative improvement were also found.
贡献：基于模型的学习能根据学生的已有知识和性别改善系统思维（ST）。发现文本、视觉和混合问题类型与学生成绩之间存在关系。背景：系统思维对明智决策和解决问题至关重要。可以教本科生更好地运用系统思维，而对他们的在线系统建模过程进行分析则可以提高他们的系统思维能力。研究问题1) 在线学习对工科学生的 ST 和概念建模技能水平有何影响？2) 学生的 ST、概念建模以及文本、视觉和混合问题类型的得分之间是否存在差异？研究方法：研究对象为参加二年级必修课程的 157 名工科本科生，在此期间收集数据并进行定量分析。研究结果具有不同先验知识的学生在ST总平均分和各种问题类型的平均分上存在显著差异。此外，还发现了 ST 及其相对提高方面的性别差异。
{"title":"Assessing Engineering Students’ Systems Thinking and Modeling Based on Their Online Learning","authors":"Roee Peretz;Natali Levi-Soskin;Dov Dori;Yehudit Judy Dori","doi":"10.1109/TE.2024.3379218","DOIUrl":"10.1109/TE.2024.3379218","url":null,"abstract":"Contribution: Model-based learning improves systems thinking (ST) based on students’ prior knowledge and gender. Relations were found between textual, visual, and mixed question types and student achievements. Background: ST is essential to judicious decision-making and problem-solving. Undergraduate students can be taught to apply better ST, and analysis of their online systems modeling processes can improve their ST. Research Questions: 1) What is the effect, if any, of online learning on the ST and conceptual modeling skill levels of undergraduate engineering students? 2) What differences are there, if any, between students’ ST, conceptual modeling, and scores in textual, visual, and mixed question types based on their prior knowledge levels? and 3) Are there any gender differences in student performance, and if so, what are they? Methodology: The research participants were 157 undergraduate engineering students who took part in a mandatory second-year course, during which data were collected and analyzed quantitatively. Findings: Students with disparate prior knowledge differed significantly from each other in their overall ST mean score and in the mean scores of the various question types. Gender differences in ST and its relative improvement were also found.","PeriodicalId":55011,"journal":{"name":"IEEE Transactions on Education","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2024-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140563333","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}
The IEEE Education Society seeks annual nominations for student and professional awards that recognize our members for outstanding contributions in engineering education. Notable contributions to the scholarship of teaching and learning, the use of evidence-based practices in the classroom, and service to the engineering education profession all unite to enrich the way engineers are trained for their professional careers. We congratulate the winners of the 2023 awards.
{"title":"2023 IEEE Education Society Awards","authors":"","doi":"10.1109/TE.2024.3379716","DOIUrl":"https://doi.org/10.1109/TE.2024.3379716","url":null,"abstract":"The IEEE Education Society seeks annual nominations for student and professional awards that recognize our members for outstanding contributions in engineering education. Notable contributions to the scholarship of teaching and learning, the use of evidence-based practices in the classroom, and service to the engineering education profession all unite to enrich the way engineers are trained for their professional careers. We congratulate the winners of the 2023 awards.","PeriodicalId":55011,"journal":{"name":"IEEE Transactions on Education","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2024-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10495375","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140540919","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.2024.3375233","DOIUrl":"https://doi.org/10.1109/TE.2024.3375233","url":null,"abstract":"","PeriodicalId":55011,"journal":{"name":"IEEE Transactions on Education","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2024-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10495377","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140540968","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.2024.3375231","DOIUrl":"https://doi.org/10.1109/TE.2024.3375231","url":null,"abstract":"","PeriodicalId":55011,"journal":{"name":"IEEE Transactions on Education","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2024-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10495362","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140540967","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}
The 2023 IEEE Educational Activities Board (EAB), chaired by IEEE Educational Activities Vice President Rabab Ward, upon the recommendation of the EAB Awards and Recognition Committee (ARC) has named the recipients of the 2023 IEEE EAB Awards. EAB Awards recognize and honor individuals and organizations for major contributions to engineering and technical education. Awards are given for meritorious activities in accreditation, continuing education, educational innovation, pre-university education, service to the IEEE EAB, employee professional development, and informal education systems, as well as related achievements that advance the practice of engineering and engineering education.
{"title":"2023 IEEE Educational Activities Board Awards","authors":"","doi":"10.1109/TE.2024.3351028","DOIUrl":"https://doi.org/10.1109/TE.2024.3351028","url":null,"abstract":"The 2023 IEEE Educational Activities Board (EAB), chaired by IEEE Educational Activities Vice President Rabab Ward, upon the recommendation of the EAB Awards and Recognition Committee (ARC) has named the recipients of the 2023 IEEE EAB Awards. EAB Awards recognize and honor individuals and organizations for major contributions to engineering and technical education. Awards are given for meritorious activities in accreditation, continuing education, educational innovation, pre-university education, service to the IEEE EAB, employee professional development, and informal education systems, as well as related achievements that advance the practice of engineering and engineering education.","PeriodicalId":55011,"journal":{"name":"IEEE Transactions on Education","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2024-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10495376","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140540920","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}
Nurul Hazlina Noordin, Kamil Khalili Bin Haji Abdullah, Phuah Soon Eu
{"title":"Assessing the Effectiveness of UMP STEM Cube as a Tool for Developing Digital Making Skill Sets","authors":"Nurul Hazlina Noordin, Kamil Khalili Bin Haji Abdullah, Phuah Soon Eu","doi":"10.1109/te.2024.3376448","DOIUrl":"https://doi.org/10.1109/te.2024.3376448","url":null,"abstract":"","PeriodicalId":55011,"journal":{"name":"IEEE Transactions on Education","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2024-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140563337","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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