Hostname: page-component-78c5997874-j824f Total loading time: 0 Render date: 2024-11-04T21:31:49.280Z Has data issue: false hasContentIssue false
  • English
  • Français

Mechanix: A natural sketch interface tool for teaching truss analysis and free-body diagrams

Published online by Cambridge University Press:  16 May 2014

Olufunmilola Atilola ,
Stephanie Valentine ,
Hong-Hoe Kim ,
David Turner ,
Erin McTigue ,
Tracy Hammond  and
Julie Linsey
Olufunmilola Atilola
Affiliation:
Department of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA
Stephanie Valentine
Affiliation:
Department of Computer Science and Engineering, Texas A&M University, College Station, Texas, USA
Hong-Hoe Kim
Affiliation:
Department of Computer Science and Engineering, Texas A&M University, College Station, Texas, USA
David Turner
Affiliation:
Department of Computer Science and Engineering, Texas A&M University, College Station, Texas, USA
Erin McTigue
Affiliation:
Department of Education and Human Development, Texas A&M University, College Station, Texas, USA
Tracy Hammond
Affiliation:
Department of Computer Science and Engineering, Texas A&M University, College Station, Texas, USA
Julie Linsey*
Affiliation:
Department of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA
*
Reprint requests to: Julie Linsey, Department of Mechanical Engineering, Georgia Institute of Technology, 801 Ferst Drive NW, Atlanta, GA 30332-0405, USA. E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Massive open online courses, online tutoring systems, and other computer homework systems are rapidly changing engineering education by providing increased student feedback and capitalizing upon online systems' scalability. While online homework systems provide great benefits, a growing concern among engineering educators is that students are losing both the critical art of sketching and the ability to take a real system and reduce it to an accurate but simplified free-body diagram (FBD). For example, some online systems allow the drag and drop of forces onto FBDs, but they do not allow the user to sketch the FBDs, which is a vital part of the learning process. In this paper, we discuss Mechanix, a sketch recognition tool that provides an efficient means for engineering students to learn how to draw truss FBDs and solve truss problems. The system allows students to sketch FBDs into a tablet computer or by using a mouse and a standard computer monitor. Using artificial intelligence, Mechanix can determine not only the component shapes and features of the diagram but also the relationships between those shapes and features. Because Mechanix is domain specific, it can use those relationships to determine not only whether a student's work is correct but also why it is incorrect. Mechanix is then able to provide immediate, constructive feedback to students without providing final answers. Within this manuscript, we document the inner workings of Mechanix, including the artificial intelligence behind the scenes, and present studies of the effects on student learning. The evaluations have shown that Mechanix is as effective as paper-and-pencil-based homework for teaching method of joints truss analysis; focus groups with students who used the program have revealed that they believe Mechanix enhances their learning and that they are highly engaged while using it.

Keywords

Engineering CoursewareEngineering EducationEngineering Statics
Type
Special Issue Articles
Information
AI EDAM , Volume 28 , Issue 2: Design Computing and Cognition (DCC'12) , May 2014 , pp. 169 - 192
Copyright
Copyright © Cambridge University Press 2014 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Anderson, E. (2011). M-MODEL8. Accessed October 26, 2011, at http://aln.coe.ttu.edu/anderson/premier/Default.htmlGoogle Scholar
Anoto. (2013). Anoto—digitial writing solutions. Accessed July 9, 2013, at http://www.anoto.comGoogle Scholar
Atilola, O., Field, M., Linsey, J., Hammond, T., & McTigue, E. (2011). Mechanix: a sketch recognition truss tutoring system. Proc. ASME Int. Design Engineering Technical Conf., Computers and Information in Engineering Conf., pp. 645–654.Google Scholar
Atilola, O., Field, M., Linsey, J., McTigue, E., & Hammond, T. (2011). Evaluation of a natural sketch interface for truss FBDs and analysis. Proc. Frontiers in Education Conf., pp. S2E-1–S2E-6.Google Scholar
Atilola, O., McTigue, E., Hammond, T., & Linsey, J. (2013). Mechanix: evaluating the effectiveness of a sketch recognition truss tutoring program against other truss programs. Proc. ASEE Annual Conf. Exposition. Atlanta, GA, June 23–26.CrossRefGoogle Scholar
Atilola, O., Osterman, C., Vides, F., McTigue, E., Linsey, J., & Hammond, T. (2012). Mechanix: the development of a sketch recognition truss tutoring system. Proc. ASEE Annual Conf. Exposition. San Antonio, TX, June 10–13.CrossRefGoogle Scholar
Baddeley, A.D. (1986). Working Memory. Oxford: Oxford University Press.Google Scholar
Bera, S.J., & Robinson, D.H. (2004). Exploring the boundary conditions of the delay hypothesis with adjunct displays. Journal of Educational Psychology 96(2), 381–388.CrossRefGoogle Scholar
Black, P., & Wiliam, D. (1998). Assessment and classroom learning. Assessment in Education 5(1), 67–74.Google Scholar
Brooke, J. (1996). SUS—a quick and dirty usability scale. In Usability Evaluation in Industry (Jordan, P. W., Thomas, B., McClelland, I.L., & Weerdmeester, B., Eds.). London: Taylor & Francis.Google Scholar
Buchanan, S., Ochs, B., & LaViola, JJ. Jr. (2012). CSTutor: a pen-based tutor for data structure visualization. Proc. 43rd ACM Technical Symp. Computer Science Education, pp. 565–570. New York: ACM.Google Scholar
Cheema, S., & LaViola, J. (2012). PhysicsBook: a sketch-based interface for animating physics diagrams. Proc. 2012 ACM Int. Conf. Intelligent User Interfaces, pp. 51–60. New York: ACM.CrossRefGoogle Scholar
CMU. (2001). Open Learning Initiative. Accessed February 6, 2011, at http://oli.web.cmu.edu/openlearning/Google Scholar
Cossairt, T.J., & LaViola, J.J. Jr. (2012). SetPad: a sketch-based tool for exploring discrete math set problems. Proc. Int. Symp. Sketch-Based Interfaces and Modeling, pp. 47–56.Google Scholar
Dixon, D., Prasad, M., & Hammond, T. (2010). iCanDraw: using sketch recognition and corrective feedback to assist a user in drawing human faces. Proc. 28th Int. Conf. Human Factors in Computing Systems, pp. 897–906. New York: ACM.Google Scholar
DST. (2013). Interactive physics: Physics simulation software for the classroom. Accessed May 21, 2013, at http://www.design-simulation.com/ip/Google Scholar
Ferguson, E.S. (1977). The mind's eye: nonverbal thought in technology. Science 197(4306), 827–836.Google Scholar
Field, M., Valentine, S., Linsey, J., & Hammond, T. (2011). Sketch recognition algorithms for comparing complex and unpredictable shapes. Proc. 22nd Int. Joint Conf. Artificial Intelligence, Vol. 3, pp. 2436–2441. Menlo Park, CA: AAAI Press.Google Scholar
Forbus, K., Lockwood, K., Klenk, M., Tomai, E., & Usher, J. (2004). Open-domain sketch understanding: the nuSketch approach. Proc. AAAI Fall Symp. Making Pen-Based Interaction Intelligent and Natural, pp. 58–63.Google Scholar
Forbus, K., Usher, J., Lovett, A., Lockwood, K., & Wetzel, J. (2008). CogSketch: open-domain sketch understanding for cognitive science research and for education. Proc. 5th Eurographics Workshop on Sketch-Based Interfaces and Modeling.Google Scholar
Fuccella, V., Isokoski, P., & Martin, B. (2013). Gestures and widgets: performance in text editing on multi-touch capable mobile devices. Proc. SIGCHI Conf. Human Factors in Computing Systems, pp. 2785–2794. New York: ACM.Google Scholar
Goldman, S.R. (2003). Learning in complex domains: when and why do multiple representations help? Learning and Instruction 13(2), 239–244.Google Scholar
Hammond, T., & Davis, R. (2005). LADDER, a sketching language for user interface developers. Computers & Graphics 29(4), 518–532.Google Scholar
Kang, B., & LaViola, J. (2012). LogicPad: a pen-based application for visualization and verification of boolean algebra. Proc. 2012 ACM Int. Conf. Intelligent User Interfaces, pp. 265–268. New York: ACM.Google Scholar
Kara, L.B., & Stahovich, T.F. (2005). An image-based, trainable symbol recognizer for hand-drawn sketches. Computers & Graphics 29(4), 501–517.Google Scholar
Kebodeaux, K., Field, M., & Hammond, T. (2011). Defining precise measurements with sketched annotations. Proc. 8th Eurographics Symp. Sketch-Based Interfaces and Modeling, Vol. 11, pp. 79–86. New York: ACM.CrossRefGoogle Scholar
Kozma, R.B. (1994). Will media influence learning? Reframing the debate. Educational Technology Research and Development 42(2), 7–19.Google Scholar
LaViola, J.J. Jr., & Zeleznik, R.C. (2007). MathPad∧2: a system for the creation and exploration of mathematical sketches. Proc. ACM SIGGRAPH 2007 Courses, p. 46. New York: ACM.Google Scholar
Lee, W.S., de Silva, R., Peterson, E.J., Calfee, R.C., & Stahovich, T.F. (2008). Newton's pen: a pen-based tutoring system for statics. Computers & Graphics 32(5), 511–524.Google Scholar
Mathewson, J.H. (1999). Visual–spatial thinking: an aspect of science overlooked by educators. Science Education 83(1), 33–54.Google Scholar
Mayer, R.E. (1996). Learning strategies for making sense out of expository text: the SOI model for guiding three cognitive processes in knowledge construction. Educational Psychology Review 8(4), 357–371.Google Scholar
Mestre, J.P. (2005). Facts and myths about pedagogies of engagement in science learning. Peer Review 7(2), 24–27.Google Scholar
Nicol, D.J., & Macfarlane, D.D. (2006). Formative assessment and self-regulated learning: a model and seven principles of good feedback practice. Studies in Higher Education 31(2), 199–218.Google Scholar
Ouyang, T.Y., & Davis, R. (2011). ChemInk: a natural real-time recognition system for chemical drawings. Proc. 16th Int. Conf. Intelligent user interfaces, pp. 267–276. New York: ACM.Google Scholar
Ouyang, T.Y., & Davis, R. (2009). A visual approach to sketched symbol recognition. Proc. 21st Int. Joint Conf. Artificial Intelligence, IJCAI, pp. 1463–1468. San Francisco, CA: Morgan Kaufmann.Google Scholar
Paulson, B., & Hammond, T. (2008). PaleoSketch: accurate primitive sketch recognition and beautification. Proc. 13th Int. Conf. Intelligent User Interfaces, pp. 1–10. New York: ACM.Google Scholar
Roselli, R.J. (2013). VaNTH ERC. Accessed February 5, 2013, at https://repo.vanth.org/portal/Members/rroselli/free-body-diagram-assistantGoogle Scholar
Rosser, S.V. (2007). InTEL: Interactive toolkit for engineering learning. Accessed February 24, 2010, at http://intel.gatech.edu/index.phpGoogle Scholar
Rubine, D. (1991). Specifying gestures by example. Proc. ACM SIGGRAPH 1991, pp. 329–337. Las Vegas, NV, July.Google Scholar
Sadoski, M. (2001). Resolving the effects of concreteness on interest, comprehension, and learning important ideas from text. Educational Psychology Review 13(3), 263–281.Google Scholar
Schnotz, W., & Bannert, M. (2003). Construction and interference in learning from multiple representation. Learning and Instruction 13(2), 141–156.Google Scholar
Steif, P.S., & Dantzler, J.A. (2005). A statics concept inventory: development and psychometric analysis. Journal of Engineering Education 33, 363–371.Google Scholar
Stern, E., Aprea, C., & Ebner, H.G. (2003). Improving cross-content transfer in text processing by means of active graphical representation. Learning and Instruction 13(2), 191–203.CrossRefGoogle Scholar
Sutherland, I.E. (1964). Sketch pad: a man–machine graphical communication system. Proc. SHARE Design Automation Workshop, pp. 6.329–6.332, 6.346. New York: ACM.Google Scholar
Sutton, M.G., & Jong, I.C. (2000). A truss analyzer for enriching the learning experience of students. Proc. ASEE Annual Conf., St. Louis, MS, June 18–21.Google Scholar
Sweller, J., & Chandler, P. (1994). Why some material is difficult to learn. Cognition and Instruction 12(3), 185–233.Google Scholar
Tversky, B. (1999). What does drawing reveal about thinking? In Visual and Spatial Reasoning in Design (Gero, J.S., & Tversky, B., Eds.). Sydney: University of Sydney, Key Centre of Design Computing and Cognition.Google Scholar
Ullman, D.G., Wood, S., & Craig, D. (1990). The importance of drawing in the mechanical design process. Computers & Graphics 14(2), 263–274.Google Scholar
Valentine, S., Vides, F., Lucchese, G., Turner, D., Kim, H.-H., Li, W., Linsey, J., & Hammond, T. (2012). Mechanix: a sketch-based tutoring system for statics courses. Proc. 24th Conf. Innovative Applications of Artificial Intelligence, Toronto.Google Scholar
Valentine, S., Vides, F., Lucchese, G., Turner, D., Kim, H.-h., Li, W., Linsey, J., & Hammond, T. (2013). Mechanix: a sketch-based tutoring and grading system for free-body diagrams. AI Magazine 34(1), 55.Google Scholar
Vanlehn, K., Lynch, C., Schulze, K., Shapiro, J.A., Shelby, R., Taylor, L., Treacy, D., Weinstein, A., & Wintersgill, M. (2005). The Andes physics tutoring system: lessons learned. International Journal of Artificial Intelligence in Education 15(3), 147–204.Google Scholar
Wobbrock, J.O., Wilson, A.D., & Yang, L. (2007). Gestures without libraries, toolkits or training: a $1 recognizer for user interface prototypes. Proc. 20th Annual ACM Symp. User Interface Software and Technology. New York: ACM.Google Scholar