Daniel G. Rees Lewis, Spencer E. Carlson, Christopher K. Riesbeck, Elizabeth M. Gerber, Matthew W. Easterday
{"title":"鼓励工程设计团队使用工具参与专家迭代实践,以支持基于问题的学习辅导","authors":"Daniel G. Rees Lewis, Spencer E. Carlson, Christopher K. Riesbeck, Elizabeth M. Gerber, Matthew W. Easterday","doi":"10.1002/jee.20554","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Background</h3>\n \n <p>To create design solutions experienced engineering designers engage in expert iterative practice. Researchers find that students struggle to learn this critical engineering design practice, particularly when tackling real-world engineering design problems.</p>\n </section>\n \n <section>\n \n <h3> Purpose/Hypothesis</h3>\n \n <p>To improve our ability to teach iteration, this study contributes (i) a new teaching approach to improve student teams' expert iterative practices, and (ii) provides support to existing frameworks—chiefly the Design Risk Framework—that predict the key metacognitive processes we should support to help students to engage in expert iterative practices in real-world engineering design.</p>\n </section>\n \n <section>\n \n <h3> Design/Method</h3>\n \n <p>In a 3-year design-based research study, we developed a novel approach to teaching students to take on real-world engineering design projects with real clients, users, and contexts to engage in expert iterative practices.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>Study 1 confirms that student teams struggle to engage in expert iterative practices, even when supported by problem-based learning (PBL) coaching. Study 2 tests our novel approach, Planning-to-Iterate, which uses (i) templates, (ii) guiding questions to help students to define problem and solution elements, and (iii) risk checklists to help student teams to identify risks. We found that student teams using Planning-to-Iterate engaged in more expert iterative practices while receiving less PBL coaching.</p>\n </section>\n \n <section>\n \n <h3> Conclusions</h3>\n \n <p>This work empirically tests a design argument—a theory for a novel teaching approach—that augments PBL coaching and helps students to identify risks and engage in expert iterative practices in engineering design projects.</p>\n </section>\n </div>","PeriodicalId":50206,"journal":{"name":"Journal of Engineering Education","volume":"112 4","pages":"1012-1031"},"PeriodicalIF":3.9000,"publicationDate":"2023-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Encouraging engineering design teams to engage in expert iterative practices with tools to support coaching in problem-based learning\",\"authors\":\"Daniel G. Rees Lewis, Spencer E. Carlson, Christopher K. Riesbeck, Elizabeth M. 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Encouraging engineering design teams to engage in expert iterative practices with tools to support coaching in problem-based learning
Background
To create design solutions experienced engineering designers engage in expert iterative practice. Researchers find that students struggle to learn this critical engineering design practice, particularly when tackling real-world engineering design problems.
Purpose/Hypothesis
To improve our ability to teach iteration, this study contributes (i) a new teaching approach to improve student teams' expert iterative practices, and (ii) provides support to existing frameworks—chiefly the Design Risk Framework—that predict the key metacognitive processes we should support to help students to engage in expert iterative practices in real-world engineering design.
Design/Method
In a 3-year design-based research study, we developed a novel approach to teaching students to take on real-world engineering design projects with real clients, users, and contexts to engage in expert iterative practices.
Results
Study 1 confirms that student teams struggle to engage in expert iterative practices, even when supported by problem-based learning (PBL) coaching. Study 2 tests our novel approach, Planning-to-Iterate, which uses (i) templates, (ii) guiding questions to help students to define problem and solution elements, and (iii) risk checklists to help student teams to identify risks. We found that student teams using Planning-to-Iterate engaged in more expert iterative practices while receiving less PBL coaching.
Conclusions
This work empirically tests a design argument—a theory for a novel teaching approach—that augments PBL coaching and helps students to identify risks and engage in expert iterative practices in engineering design projects.