Volume 7: Engineering Education and Professional Development 2007
DOI: 10.1115/imece2007-41665
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Promoting Active Learning in Teaching the Course of Design of Machine Elements

Abstract: For certain topics in the curriculum the pendulum of engineering education is swinging from a full focus on pure theory to a balance between theoretical analysis and solid experiences. Undergraduate students are required to obtain both theoretical knowledge and hands-on experiences to meet the need of job markets. Active learning/teaching has become a commonly-used instructional approach in response to this change of the balance. In the authors’ institute, the Design of Machine Elements (DOME) course has been … Show more

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Cited by 3 publications
(7 citation statements)
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“…Given the interconnected nature of variables in manufacturing, data quality profoundly affects the performance and reliability of ML models (Freiesleben et al, 2020), emphasising the need for effective data-gathering methodologies. While reliable, traditional datagathering methods, such as the Design of Experiments (DOE), often struggle with scalability and efficiency in Supervised ML models, which require vast and varied datasets (Duan & Ries, 2007). Active Learning (AL), an emerging paradigm in ML, offers a promising solution by selectively targeting informative data points, potentially reducing the required data volume (Duan & Ries, 2007).…”
Section: Introductionmentioning
confidence: 99%
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“…Given the interconnected nature of variables in manufacturing, data quality profoundly affects the performance and reliability of ML models (Freiesleben et al, 2020), emphasising the need for effective data-gathering methodologies. While reliable, traditional datagathering methods, such as the Design of Experiments (DOE), often struggle with scalability and efficiency in Supervised ML models, which require vast and varied datasets (Duan & Ries, 2007). Active Learning (AL), an emerging paradigm in ML, offers a promising solution by selectively targeting informative data points, potentially reducing the required data volume (Duan & Ries, 2007).…”
Section: Introductionmentioning
confidence: 99%
“…While reliable, traditional datagathering methods, such as the Design of Experiments (DOE), often struggle with scalability and efficiency in Supervised ML models, which require vast and varied datasets (Duan & Ries, 2007). Active Learning (AL), an emerging paradigm in ML, offers a promising solution by selectively targeting informative data points, potentially reducing the required data volume (Duan & Ries, 2007). However, the practical application and effectiveness of AL compared to conventional DOE methods in industrial settings remain under-researched (Gubernatis & Lookman, 2018).…”
Section: Introductionmentioning
confidence: 99%
“…Two student's comments are listed here: (1) "This course needs a project to tie together everything we learn into something practical, something we can apply the knowledge we gained"; and (2) "The project allow us to directly apply classroom knowledge to a real world application while reinforces our understanding of the lecture materials". Other student comments regarding the requirement of project can be summarized as follows: (1) can implement what they learn; (2) have better understanding what they learn, (3) help them for future job and (4) help to build leadership and communication skills in a team environment.…”
Section: The Students' Survey and The Results Analysismentioning
confidence: 99%
“…The trend in engineering education is swinging from an emphasis on theory to a balance between theory and applied design activities [1][2][3][4]. There are certainly some gaps or differences between the academic settings and the industrial settings for mechanical engineering programs.…”
Section: Introductionmentioning
confidence: 99%
“…As a core course in any accredited mechanical engineering undergraduate program, "Machine Design" is frequently relied upon to meet an oversized load of learning objectives that range from reinforcement of classical mechanics principles to empirical design of specific machine components, advanced CAD modeling, and project management [1][2][3]. In addition to the sheer volume and breadth of expected learning objectives for the course, Machine Design is challenged by a lack of consensus among engineering educators as to the conceptual approach to the core technical content and the pedagogical techniques used to balance theory versus practice of machine design [2,[4][5][6]. There is a general consensus that theoretical content in Machine Design should be supplemented with application to design of machine components or systems [3,6].…”
Section: Introductionmentioning
confidence: 99%