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Efficacy of a Metacognitive Writing-to-Learn Exercise in Improving Student Understanding and Performance in an Engineering Statics Course

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2015 ASEE Annual Conference & Exposition


Seattle, Washington

Publication Date

June 14, 2015

Start Date

June 14, 2015

End Date

June 17, 2015





Conference Session

NSF Grantees’ Poster Session

Tagged Topic

NSF Grantees Poster Session

Page Count


Page Numbers

26.587.1 - 26.587.11



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Paper Authors


Saryn R Goldberg Hofstra University

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Dr. Saryn R. Goldberg is an Associate Professor of Mechanical Engineering in Hofstra University’s School of Engineering and Applied Sciences. Dr. Goldberg received her Sc.B. in Engineering with a focus on materials science from Brown University, her M.S. degree in Biomedical Engineering with a focus on biomaterials from Northwestern University, and her Ph.D. in Mechanical Engineering with a focus on biomechanics from Stanford University. At Hofstra she teaches courses in mechanical engineering, materials science and biomechanics. In addition to her research in engineering education, Dr. Goldberg studies the biomechanics of human movement, focusing on gait rehabilitation. She is a member of ASEE, the Society of Women Engineers and the American Society of Biomechanics.

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Jennifer Andrea Rich Hofstra University

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Jennifer A. Rich is Associate Professor of Writing Studies and Composition at Hofstra University. She has published widely in writing studies, film, Shakespeare, and popular culture. She has recently published a book-length guide to the philosophy of Theodore Adorno.

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Amy M. Masnick Hofstra University

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Dr. Amy Masnick is an Associate Professor of Psychology at Hofstra University. Dr. Masnick received both her B.S. and Ph.D. in Human Development at Cornell University. At Hofstra she teaches courses in introductory psychology, research methods, cognitive psychology, and child development. Dr. Masnick is interested in conceptual development, reasoning about science and number in children and adults, and in science and engineering education.

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Efficacy of a metacognitive writing-to-learn exercise in improving student understanding and performance in an engineering Statics courseOur current work is an extension of the preliminary results of a NSF-funded study thatinvestigates the use of metacognitive writing-to-learn prompts in an engineering Statics course toimprove student understanding and performance. Our methodology was determined by acomprehensive study of literature investigating the use of writing in the science classroom(Beall, 1998; Case & Gunstone, 2003; Case & Marshall, 2004; Driskill, et al., 1998; Hanson &Williams, 2008; Hübner et al., 2006; Jamison, 2000: Nokes et al., 2011).In the second year of the study (2013-2014), we developed a writing prompt that we are findingto be more successful than our previous iterations, both in efficacy for the students and ease ofimplementation for the professor. Specifically, after students solve selected engineeringproblems, they answer short-answer questions to describe any confusion they had about theconcepts or computations required to solve the problem. The professor then demonstrates theproblem solution in class as students correct their own work. Following this, students are askedto revisit and reexamine their conceptual and computational errors via writing in the classroom.We believe that students will gain a more lasting and deeper understanding of the staticsconcepts under examination if students are given an opportunity to reflect in writing on thereason for their mistakes after instructor feedback. Finally, the instructor provides additionalfeedback indicating whether students’ understanding of the reason for their error(s) was accurate.The inclusion of a revision-based writing step is consistent with current research showing thisapproach to be effective in improving student performance (Hübner, et al., 2006; Ionas, et al.,2012; Kagestan & Engelbrecht 2006; Porter & Masingla 2000).  The revision step allows studentsto clarify their new understanding of the problem under consideration and also to reassess thereasons for their initial confusion. In this way, it closes the loop for them metacognitively. Ourpreliminary data from this approach, presented at the ASEE 2014 meeting, suggestedimprovement in student performance as seen in their final exam scores, but the sample wassmall, and the effect did not reach signficance. We are therefore implementing the samemethodology during the Fall 2014 semester with a cohort of approximately 60 students in twosections of Statics, taught by the same professor as the previous semester, for a more robust testof the efficacy of the intervention. To rule out the possibility of cohort differences, we are alsocollecting GPA/SAT and prerequisite grades in math and physics for past and current Staticsstudents.For the ASEE 2015 conference, we plan to present the most recent findings of this study. BySpring 2015, we will have a clearer picture of the efficacy of our intervention. If appropriate, wewill then be ready to discuss ways that this writing intervention might be utilized effectively inother engineering education contexts. If we find that the intervention is not effective, we willpresent changes that we plan to implement to improve learning in Statics. ReferencesBeall, H. (1998). Expanding the scope of writing in chemical education. Journal of Science Education and Technology, 7(3), 259-270.Case, J. & Gunstone, R. F. (2003). Approaches to learning in a second year chemical engineering course. International Journal of Science Education, 25(7), 801-819.Case, J. & Marshall, D. (2004). Between deep and surface: procedural approaches to learning in engineering education contexts. Studies in Higher Education, 29(5), 605-615.Driskill, L, Lewis, K., Stearns, J., & Volz, T. (1998). Students’ reasoning and rhetorical knowledge in first-year chemistry. Language and Learning Across the Disciplines, 2(3), 3-24.Hanson, J. H. & Williams, J. M. (2008). Using writing assessments to improve students’ self assessment and communication in an Engineering statics course. Journal of Engineering Education. 97(4), 515-529.Hübner, S., Nückles, M., & Renki, A. (2006). Prompting cognitive and metacognitive processing in writing-to-learn enhances learning outcomes. In R. Sun (Ed.), Proceedings of the 28th Annual Conference of the Cognitive Science Society (pp. 357-362). Mahwah, NJ: Erlbaum.Ionas, I., Cernusca, D., & Collier, H. L. (2012). Prior knowledge influence on self-explanation effectiveness when solving problems: An exploratory study in science learning. International Journal Of Teaching And Learning In Higher Education, 24(3), 349-358.Jamison, R. (2000). Learning the language of mathematics. Learning and Language Across the Disciplines, 4(1), 45-54.Kagesten, O., & Engelbrecht, J. (2006). Supplementary explanations in undergraduate mathematics assessment: A forced formative writing activity. European Journal of Engineering Education, 31(6), 705-715.Nokes, T.J., Hausmann, R. G. M., VanLehn, K., Gershman, S. (2011). Testing the instructional fit hypothesis: The case for self-explanation prompts. Instructional Science 39: 645-666.Porter, M. & Masingla, J. O. (2000). Examining the effects of writing on conceptual and procedural knowledge in calculus. Educational Studies in Mathematics. 42, 165-177.

Goldberg, S. R., & Rich, J. A., & Masnick, A. M. (2015, June), Efficacy of a Metacognitive Writing-to-Learn Exercise in Improving Student Understanding and Performance in an Engineering Statics Course Paper presented at 2015 ASEE Annual Conference & Exposition, Seattle, Washington. 10.18260/p.23925

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