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Reinforcing Learning in an Engineering Master’s Degree Program: The Relevance of Research Training
KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Mechatronics. KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Machine Design (Div.).ORCID iD: 0000-0001-5704-4504
KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Mechatronics. KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Machine Design (Div.).ORCID iD: 0000-0003-3699-5049
2019 (English)In: International journal of engineering education, ISSN 0949-149X, Vol. 35, no 2, p. 598-616Article in journal (Refereed) Published
Abstract [en]

Master students at our institute were graduating without acceptable research proficiency. We intervened by shifting our research training from teaching-centred to student-centred, and from research-related subject content to research-related processes. We performed a mixed methods study aimed to confirm there was improved research proficiency without a negative trade-off for our students’ engineering skills. Results indicated improvements to research proficiency, which our students were able to transfer to engineering-related learning activities to increase their ability to achieve engineering synthesis. This outcome was potentially supported by our courses including several perspectives on scientific knowledge production. This implies that research training, rather than having a negative effect on engineering skills, can be helpful in learning diametrically opposing aspects of thinking required by current engineering. As engineering education evolves towards more cross-disciplinary cooperation, this implies the need to pursue the increased opportunities for students to learn about different perspectives on knowledge production.

Place, publisher, year, edition, pages
2019. Vol. 35, no 2, p. 598-616
Keywords [en]
Engineering educationm Master’s education, Science education, Research-teaching nexus
National Category
Embedded Systems
Research subject
Machine Design
Identifiers
URN: urn:nbn:se:kth:diva-244040ISI: 000459427000014OAI: oai:DiVA.org:kth-244040DiVA, id: diva2:1288805
Note

QC 20190312

Available from: 2019-02-14 Created: 2019-02-14 Last updated: 2019-03-12Bibliographically approved

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fulltext(924 kB)64 downloads
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Grimheden, Martin

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