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Automatic Identification of Student Misconceptions and Errors for Truss Analysis

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Conference

2012 ASEE Annual Conference & Exposition

Location

San Antonio, Texas

Publication Date

June 10, 2012

Start Date

June 10, 2012

End Date

June 13, 2012

ISSN

2153-5965

Conference Session

Mechanics Concepts II

Tagged Division

Mechanics

Page Count

13

Page Numbers

25.244.1 - 25.244.13

Permanent URL

https://peer.asee.org/21004

Download Count

42

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Paper Authors

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Olufunmilola Atilola Texas A&M University

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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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Julie S. Linsey Texas A&M University

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Tracy Anne Hammond Ph.D. Texas A&M University

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Abstract

Automatic Identification of Student Misconcepts and Errors for Truss AnalysisMechanix is a sketch recognition tool that tutors students on drawing free-body diagrams (FBDs)and solving truss problems. It is being developed at {name of university}. Students sketch theiranswers on tablet computers as they would normally on paper. A mouse can also be used forregular computer monitors. This provides a system with a low learning curve. Mechanix is ableto provide immediate and intelligent feedback to the students; it tells them if they are missingany components of the FBD. The program is also able to tell students whether their solvedreaction forces or member forces are correct or not without actually providing the answers. SinceMechanix captures the students answers in real-time, their errors and misconcepts can easily beidentified. This paper presents results from an evaluation comparing students using Mechanix totraditional paper and pencil methods. The errors that students make when using Method ofJoints are identified and the most difficult concepts are noted. Future versions of Mechanix willautomatically provide instructions with a description of the errors their students are making andthe concepts they may be having difficulty with. This will be provide in an easy to use interfacewhere professors can quickly obtain a real-time update on their students’ performance and thenadjust their teaching approach and examples as needed. Current results from this paper provideinstructors with a list of difficulties that students typically have so that better teachingapproaches may be developed.

Atilola, O., & Vides, F., & McTigue, E. M., & Linsey, J. S., & Hammond, T. A. (2012, June), Automatic Identification of Student Misconceptions and Errors for Truss Analysis Paper presented at 2012 ASEE Annual Conference & Exposition, San Antonio, Texas. https://peer.asee.org/21004

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