Board 65: Changing Homework Achievement with Mechanix Pedagogy
- Conference
- Location
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Tampa, Florida
- Publication Date
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June 15, 2019
- Start Date
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June 15, 2019
- End Date
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June 19, 2019
- Conference Session
- Tagged Topic
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NSF Grantees Poster Session
- Page Count
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8
- DOI
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10.18260/1-2--32398
- Permanent URL
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https://peer.asee.org/32398
- Download Count
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466
Paper Authors
Sonali J. Bante Texas State University
Ethan Hilton
Georgia Institute of Technology
orcid.org/0000-0003-1623-228X
Ethan is a PhD candidate in Mechanical Engineering at the Georgia Institute of Technology working with Dr. Julie Linsey as a part of the IDREEM Lab. He graduated with honors from Louisiana Tech University with his Bachelors of Science in Mechanical Engineering. Ethan's research area is design cognition and methods with a focus on prototyping and its utilization during the design process. In particular, Ethan has focused on hand-drawn sketches and how they are used as tools for generating ideas and visual communication, especially when it involves the skill to generate quick and realistic sketches of an object or idea. He has also conducted research on the impact involvement in academic makerspaces has on students in engineering programs.
Kimberly Grau Talley P.E.
Texas State University
orcid.org/0000-0002-6235-0706
Dr. Kimberly G. Talley is an assistant professor in the Department of Engineering Technology, Maker Space Co-Director and Senior Research Fellow for the LBJ Institute for STEM Education and Research at Texas State University, and a licensed Professional Engineer. She received her Ph.D. and M.S.E. from the University of Texas at Austin in Structural Engineering. Her undergraduate degrees in History and in Construction Engineering and Management are from North Carolina State University. Dr. Talley teaches courses in the Construction Science and Management Program, and her research focus is in student engagement and retention in engineering and engineering technology education. Contact: talley@txstate.edu
Kristi J. Shryock Texas A&M University
Dr. Kristi J. Shryock is the Frank and Jean Raymond Foundation Inc. Endowed Instructional Associate Professor and Associate Department Head in the Department of Aerospace Engineering in the College of Engineering at Texas A&M University. She also serves as Director of the Craig and Galen Brown Engineering Honors Program. She received her BS, MS, and PhD from the College of Engineering at Texas A&M. Kristi works to improve the undergraduate engineering experience through evaluating preparation in areas, such as mathematics and physics, evaluating engineering identity and its impact on retention, incorporating non-traditional teaching methods into the classroom, and engaging her students with interactive methods.
Julie S. Linsey Georgia Institute of Technology
Dr. Julie S. Linsey is an Associate Professor in the George W. Woodruff School of Mechanical Engineering at the Georgia Institute of Technological. Dr. Linsey received her Ph.D. in Mechanical Engineering at The University of Texas. Her research area is design cognition including systematic methods and tools for innovative design with a particular focus on concept generation and design-by-analogy. Her research seeks to understand designers’ cognitive processes with the goal of creating better tools and approaches to enhance engineering design. She has authored over 100 technical publications including twenty-three journal papers, five book chapters, and she holds two patents.
Tracy Anne Hammond Ph.D.
Texas A&M University
orcid.org/0000-0001-7272-0507
Director of the Sketch Recognition Lab and Professor in the Department of Computer Science and Engineering at Texas A&M University, Dr. Hammond is an international leader in sketch recognition, haptics, intelligent fabrics, SmartPhone development, and computer human interaction research. Dr. Hammond’s publications on the subjects are widely cited and have well over a thousand citations, with Dr. Hammond having an h-index of 23, an h10-index of 65, and multiple papers with over 200 citations each. Her research has been funded by NSF, DARPA, Google, and many others, totaling over 9 million dollars in peer reviewed funding. She holds a PhD in Computer Science and FTO (Finance Technology Option) from MIT, and four degrees from Columbia University: an M.S in Anthropology, an M.S. in Computer Science, a B.A. in Mathematics, and a B.S. in Applied Mathematics. Prior to joining the TAMU CSE faculty Dr. Hammond taught for five years at Columbia University and was a telecom analyst for four years at Goldman Sachs. Dr Hammond is the 2011-2012 recipient of the Charles H. Barclay, Jr. '45 Faculty Fellow Award. The Barclay Award is given to professors and associate professors who have been nominated for their overall contributions to the Engineering Program through classroom instruction, scholarly activities, and professional service.
Abstract
Introductory engineering courses within large universities often have annual enrollments exceeding several hundreds of students, while online classes have even larger enrollments. It is challenging to achieve differentiated instruction in classrooms with class sizes and student diversity of such great magnitude. In such classes, professors assess whether students have mastered a concept through multiple-choice questions, marking answers as right or wrong with little feedback, or using online text-only systems. However, in these scenarios the feedback is of a mostly binary nature (right or wrong) with limited constructive feedback to scaffold learning. A growing concern among engineering educators is that students are losing both the critical skill of sketched diagrams and the ability to take a real system and reduce it to an accurate but simplified free-body diagram (FBD). A sketch-recognition based tutoring system, called Mechanix, allows students to hand-draw solutions just as they would with pencil and paper, while also providing iterative real-time personalized feedback. Sketch recognition algorithms use artificial intelligence to identify the shapes, their relationships, and other features of the sketched student drawing. Other AI algorithms then determine if and why a student’s work is incorrect, enabling the tutoring system to return immediate and iterative personalized feedback facilitating student learning that is otherwise not possible in large classes. To observe the effectiveness of this system, it has been implemented into various courses at three universities, with two additional universities planning to use the system within the next year. Student knowledge is measured using Concept Inventories based in both Physics and Statics, common exam questions, and assignments turned in for class. Preliminary results using Mechanix, a sketch-based statics tutoring system built at Texas A&M University, suggest that a sketch-based tutoring system increases homework motivation in struggling students and is as effective as paper-and-pencil-based homework for teaching method of joints truss analysis. In focus groups, students believed the system enhanced their learning and increased engagement.
Keywords: sketch recognition; intelligent user interfaces; physics education; engineering education
Bante, S. J., & Hilton, E., & Talley, K. G., & Shryock, K. J., & Linsey, J. S., & Hammond, T. A. (2019, June), Board 65: Changing Homework Achievement with Mechanix Pedagogy Paper presented at 2019 ASEE Annual Conference & Exposition , Tampa, Florida. 10.18260/1-2--32398
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