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Mechanix: The Development of a Sketch Recognition Truss Tutoring System

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2012 ASEE Annual Conference & Exposition


San Antonio, Texas

Publication Date

June 10, 2012

Start Date

June 10, 2012

End Date

June 13, 2012



Conference Session

NSF Grantees' Poster Session

Tagged Topic

NSF Grantees Poster Session

Page Count


Page Numbers

25.927.1 - 25.927.14



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Paper Authors


Olufunmilola Atilola Texas A&M University

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Olufunmilola Atilola is currently a doctoral student in the department of mechanical engineering at Texas A&M University. She obtained her master’s degree from the University of South Carolina, Columbia and her bachelor’s degree from Georgia Institute of Technology, both in mechanical engineering. At Texas A&M, her research areas include representations in engineering design and innovations in engineering education.

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Cheryl Osterman


Francisco Vides Texas A&M University

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Francisco Vides is a Graduate Researcher at the Sketch Recognition Lab at Texas A&M University. He received a double major from Los Andes University in Bogota, Colombia in electrical engineering and computer science. He is now finishing his master’s degree in computer science at Texas A&M University. His research interests are in computer-human interaction (CHI), artificial intelligence (AI), computer-assisted instructional (CAI) software, and intelligent tutoring systems (ITS).

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Erin M. McTigue Texas A&M University

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Erin McTigue is an Assistant Professor in the Department of Teaching, Learning, and Culture in the College of Education and Human Development at TAMU.

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Julie S. Linsey Texas A&M University

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Tracy Hammond Texas A&M University Orcid 16x16

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Mechanix: The Development of a Sketch Recognition Truss Tutoring SystemMechanix is a sketch recognition tool that provides an efficient means for engineering students tolearn how to draw truss free-body diagrams (FBDs) and solve truss problems. The system allowsfor students to sketch these FBDs, as they normally would by hand, into a tablet computer; amouse can also be used for regular computer monitors. Mechanix is able to provide immediateand intelligent feedback to the students; it tells them if they are missing any components of theFBD. The program is also able to tell students whether their solved reaction forces or memberforces are correct or not without actually providing the answers. Mechanix also has a checklistfeature which appears in the same window as the program, it guides the students through theproblem and automatically updates as the student progresses and solves each part of the trussproblem.This paper presents a study to evaluate the effectiveness and advantages of using Mechanix inthe classroom as a supplement to traditional teaching and learning methods. Freshmanengineering classes were recruited for this experiment and were divided into an experimentalgroup (students who used Mechanix in class and for their assignments) and a control group(students who were not exposed to Mechanix). The learning gains between these two groupswere evaluated using a series of quantitative formal assessments which include conceptinventories and homework, quiz, and exam grades. Qualitative data was also collected throughfocus groups for both groups to gather the students’ impressions of the programs for theexperimental group and general teaching styles for the control group.Results from past evaluations show that students believe that Mechanix enhances their learningand are highly engaged when using it. This current evaluation and the ensuing results will becompared with those from past evaluations. Future work on the refinement of the Mechanixprogram is also discussed.

Atilola, O., & Osterman, C., & Vides, F., & McTigue, E. M., & Linsey, J. S., & Hammond, T. (2012, June), Mechanix: The Development of a Sketch Recognition Truss Tutoring System Paper presented at 2012 ASEE Annual Conference & Exposition, San Antonio, Texas. 10.18260/1-2--21684

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