Optimizing Worked‐Example Instruction in Electrical Engineering: The Role of Fading and Feedback during Problem‐Solving Practice |
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| Authors: | Roxana Moreno Martin Reisslein Gamze Ozogul |
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| Affiliation: | 1. Educational Psychology Program University of New Mexico;2. Roxana Moreno is an associate professor in Educational Psychology at the University of New Mexico, Albuquerque. She earned her Ph.D. in psychology with an emphasis in cognitive science from the University of California, Santa Barbara, CA, and her J.D. in law from the University of Buenos Aires, Argentina. Her research interests are in human memory, learning, and higher‐order cognition with special interest in applying cognitive theories to educational technology and individual differences in learning. Before accepting a teaching position at the University of New Mexico, Dr. Moreno was awarded a Postdoctoral Fellowship in Science, Engineering, Mathematics, and Technology Education by the National Science Foundation to investigate the interaction of rich experiential and reflective interactions mediated by software pedagogical agents in virtual reality environments. Dr. Moreno was awarded the Presidential Early Career Award in Science and Engineering (PECASE), to honor the extraordinary achievements of young professionals at the outset of their independent research careers in the fields of science and technology. Currently, she is the principal investigator for two National Science Foundation grants and serves as an editorial board member for Educational Psychologist, Educational Psychology Review, and Educational Researcher.;3. Department of Electrical Engineering Arizona State University;4. Martin Reisslein is an associate professor in the Department of Electrical Engineering at Arizona State University (ASU), Tempe. He received the Dipl.‐Ing. (FH) degree from the Fachhochschule Dieburg, Germany, in 1994, and the M.S.E. degree from the University of Pennsylvania, Philadelphia, in 1996;5. both in electrical engineering. He received his Ph.D. in systems engineering from the University of Pennsylvania in 1998. During the academic year 1994–1995 he visited the University of Pennsylvania as a Fulbright scholar. From July 1998 through October 2000 he was a scientist with the German National Research Center for Information Technology (GMD FOKUS), Berlin and lecturer at the Technical University Berlin. From October 2000 through August 2005 he was an assistant professor at ASU. From January 2003 through February 2007, he was editor‐in‐chief of the IEEE Communications Surveys and Tutorials. He maintains an extensive library of video traces for network performance evaluation, including frame size traces of MPEG‐4 and H.263 encoded video, at http:trace.eas.asu.edu. He is a member of the ASEE and a senior member of the ACM and the IEEE.;6. Gamze Ozogul is a postdoctoral research associate in the Department of Electrical Engineering at Arizona State University (ASU), Tempe. She received her Masters of Science degree in Computer Education and Instructional Technology in 2002 from Middle East Technical University, Ankara, Turkey, and she earned her Ph.D. in Educational Technology in 2006 from Arizona State University. Her research interests include evaluation, instructional design, pre‐service teacher technology training, and engineering education. She has more than six years of college‐level teaching experience, and has served as an evaluator on many large‐scale funded evaluation projects. |
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| Abstract: | How can we help college students develop problem‐solving skills in engineering? To answer this question, we asked a group of engineering freshmen to learn about electrical circuit analysis with an instructional program that presented different problem‐solving practice and feedback methods. Three findings are of interest. First, students who practiced by solving all problem steps and those who practiced by solving a gradually increasing number of steps starting with the first step first (forward‐fading practice) produced higher near‐transfer scores than those who were asked to solve a gradually increasing number of steps but starting with the last step first (backward‐fading practice). Second, students who received feedback immediately after attempting each problem‐solving step outperformed those who received total feedback on near transfer. Finally, students who learned with backward‐fading practice produced higher near‐ and far‐transfer scores when feedback included the solution of a similar worked‐out problem. The theoretical and practical implications for engineering education are discussed. |
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| Keywords: | fading feedback worked examples |
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