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A proposal for using problem posing to connect learning of basic theory with engineering design

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Collection

2013 ASEE Annual Conference & Exposition

Location

Atlanta, Georgia

Publication Date

June 23, 2013

Start Date

June 23, 2013

End Date

June 26, 2013

ISSN

2153-5965

Conference Session

Improving course effectiveness

Tagged Divisions

Engineering Management, Engineering Economy, and Industrial Engineering

Page Count

11

Page Numbers

23.93.1 - 23.93.11

Permanent URL

https://peer.asee.org/19107

Download Count

38

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Paper Authors

biography

Richard L Marcellus Northern Illinois University

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Richard Marcellus is an Associate Professor in the Industrial and Systems Engineering Department at Northern Illinois University. His current research interest is definition and performance evaluation of statistical process control policies. He has taught numerous courses in applied probability, including stochastic operations research, reliability engineering, queueing methods, dynamic programming, and quality control.

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Abstract

Enhancing learning of applied probability through problem posingThere is a need for educational methods that enable transfer of academic content to engineeringpractice. Such methods appear frequently in freshman and senior design courses (cornerstoneand capstone courses), but not so often in basic knowledge courses, such as calculus, probability,and statistics. Connecting mastery of basic knowledge to engineering is challenging. This paperpresents a proposal for methods to achieve this connection, and the author’s experience with usingthe proposed methods in applied probability courses. . The essence of the proposal is that learnersshould be doing engineering while learning content. The methods are based on basic research abouthow people learn. The heart of engineering practice is design and problem solving, Thus learners should studythe nature of problems. They should be informed that there is a spectrum of problems, rangingfrom well-structured problems with definite answers and clear boundaries, such as are found intraditional textbooks, to open-ended, ill-structured problems, such as are found in the engineeringworkplace. Traditional interaction with well-structured textbook problems does not enable transfer of prob-lem solving skills to the future professional activities. But problem posing coupled with metacogni-tion does. Hence, well-structured problems should be accompanied by suggestions for challengingthem and modifying them to create new problems. Several strategies for problem creation are pre-sented and illustrated with examples. In addition, learners should be challenged with ill-structuredproblems and experience the way a working team of problem solvers might respond to them (notnecessarily completely solve them). Some of the ill-structured problems can be micro versionsof engineering design problems. Others can be related to broader issues such as contemporaryproblems of public policy. The problem structuring activities will encourage students to participatein design and construction of the learning environment. The essential point is that students shouldbe encouraged to pose, clarify, and define problems, not simply solve them, and that this activityshould be coupled with metacognition. Metacognition is deliberate self-consciousness about learning. It has been called “thinkingabout thinking”, “making thinking visible”, and “reflecting on learning and thinking”. There iswidespread agreement that developing metacognitive habits increases the ability to transfer learningin school to application in the workplace. Learning the mechanism of connecting the material toproblems in the classroom makes visible the mechanism of connecting the material to problemsin the workplace. This applies to engineering design problems as well as to operations researchproblems. Learners should be encouraged to identify and articulate metacognitive skills whileconstructing, clarifying, and solving problems. This should be done, in part, by accompanyingproblem statements with comments on the purposes of the problems, ways to personalize them, andtheir connections to applications. Also, questions that require metacognition should be built intothe problems themselves.

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