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Mechanix: A Sketch-Based Tutoring and Grading System for Free-Body Diagrams
Journal Title AI Magazine
Journal Abbreviation aimagazine
Publisher Group Association for the Advancement of Artificial Intelligence (AAAI)
Website http://aaai.org/ojs
   
Title Mechanix: A Sketch-Based Tutoring and Grading System for Free-Body Diagrams
Authors Hammond, Tracy; Linsey, Julie; Li, Wenzhe; Turner, David; Kim, Hong-hoe; Vides, Francisco; Lucchese, George; Valentine, Stephanie
Abstract Introductory engineering courses within large universities often have annual enrollments which can reach up to a thousand students. It is very challenging to achieve differentiated instruction in classrooms with class sizes and student diversity of such great magnitude. Professors can only assess whether students have mastered a concept by using multiple choice questions, while detailed homework assignments, such as planar truss diagrams, are rarely assigned because professors and teaching assistants would be too overburdened with grading to return assignments with valuable feedback in a timely manner. In this paper, we introduce Mechanix, a sketch-based deployed tutoring system for engineering students enrolled in statics courses. Our system not only allows students to enter planar truss and free body diagrams into the system just as they would with pencil and paper, but our system checks the students work against a hand-drawn answer entered by the instructor, and then returns immediate and detailed feedback to the student. Students are allowed to correct any errors in their work and resubmit until the entire content is correct and thus all of the objectives are learned. Since Mechanix facilitates the grading and feedback processes, instructors are now able to assign free response questions, increasing teachers knowledge of student comprehension. Furthermore, the iterative correction process allows students to learn during a test, rather than simply displaying memorized information.
Publisher Association for the Advancement of Artificial Intelligence
Date 2013-04-03
Source AI Magazine Vol 34, No 1: Spring Issue
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