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Sketch Mechanix, an NSF-IUSE funded research project, launched a new feature with the Fall 2022 semester: an instructor interface. Sketch Mechanix’s development had previously focused upon converting to an html platform and then expanding problem types. The initial problem that was featured was truss analysis ( method of joints ). The second problem type was free body diagrams with point loads at any angle. The most recent sketch recognition feature was the addition of applied moments, using a curved arrow. For any of these problem types, Sketch Mechanix features sketch recognition and automatic feedback to students on their free body diagrams through an online homework platform. With this latest innovation, instructors adopting this novel homework system can now input their own problems, view student scores broken down by problem, and adjust assignment due dates. Prior to the launch of this interface, all of these features involved emailing the development team. For instance, the instructor previously had to email the desired problems, their solutions, and points awarded, as well as wait for the developer to email back student scores to be able to see how students were doing. While sketch recognition has long been the key draw to using Sketch Mechanix, the addition of the instructor interface will aid in the project’s sustainability as it nears the end of the grant period. This paper and poster describe the instructor interface, including screen shots, share feedback from instructors who tested the interface in classes, and detail the future of the program. 

Sketch Mechanix, an NSF-IUSE funded research project, launched a new feature with the Fall 2022 semester: an instructor interface. Sketch Mechanix’s development had previously focused upon converting to an html platform and then expanding problem types. The initial problem that was featured was truss analysis ( method of joints ). The second problem type was free body diagrams with point loads at any angle. The most recent sketch recognition feature was the addition of applied moments, using a curved arrow. For any of these problem types, Sketch Mechanix features sketch recognition and automatic feedback to students on their free body diagrams through an online homework platform. With this latest innovation, instructors adopting this novel homework system can now input their own problems, view student scores broken down by problem, and adjust assignment due dates. Prior to the launch of this interface, all of these features involved emailing the development team. For instance, the instructor previously had to email the desired problems, their solutions, and points awarded, as well as wait for the developer to email back student scores to be able to see how students were doing. While sketch recognition has long been the key draw to using Sketch Mechanix, the addition of the instructor interface will aid in the project’s sustainability as it nears the end of the grant period. This paper and poster describe the instructor interface, including screen shots, share feedback from instructors who tested the interface in classes, and detail the future of the program. 

It is challenging to effectively educate in large classes with students from a multitude of backgrounds. Many introductory engineering courses in universities have hundreds of students, and some online classes are even larger. Instructors in these circumstances often turn to online homework systems, which help greatly reduce the grading burden; however, they come at the cost of reducing the quality of feedback that students receive. Since online systems typically can only automatically grade multiple choice or numeric answer questions, students predominately do not receive feedback on the critical skill of sketching free-body diagrams (FBD). An online, sketch-recognition based tutoring system called Mechanix requires students to draw free-body diagrams for introductory statics courses in addition to grading their final answers. Students receive feedback about their diagrams that would otherwise be difficult for instructors to provide in large classes. Additionally, Mechanix can grade open-ended truss design problems with an indeterminate number of solutions. Mechanix has been in use for over six semesters at five different universities by over 1000 students to study its effectiveness. Students used Mechanix for one to three homework assignments covering free-body diagrams, static truss analysis, and truss design for an open-ended problem. Preliminary results suggest the system increases homework engagement and effort for students who are struggling and is as effective as other homework systems for teaching statics. Focus groups showed students enjoyed using Mechanix and that it helped their learning process. 

In online or large in-person course sections, instructors often adopt an online homework tool to alleviate the burden of grading. While these systems can quickly tell students whether they got a problem correct for a multiple-choice or numeric answer, they are unable to provide feedback on students’ free body diagrams. As the process of sketching a free body diagram correctly is a foundational skill to solving engineering problems, the loss of feedback to the students in this area is a detriment to students. To address the need for rapid feedback on students’ free body diagram sketching, the research team developed an online, sketch-recognition system called Mechanix. This system allows students to sketch free body diagrams, including for trusses, and receive instant feedback on their sketches. The sketching feedback is ungraded. After the students have a correct sketch, they are then able to enter in the numeric answers for the problem and submit those for a grade. Thereby, the platform offers the grading convenience of other online homework systems but also helps the students develop their free body diagram sketching skills. To assess the efficacy of this experimental system, standard concept inventories were administered pre- and post-semester for both experimental and control groups. The unfamiliarity or difficulty of some advanced problems in the Statics Concept Inventory, however, appeared to discourage students, and many would stop putting in any effort after a few problems that were especially challenging to solve. This effect was especially pronounced with the Construction majors versus the Mechanical Engineering majors in the test group. To address this tendency and therefore collect more complete pre- and post-semester concept inventory data, the research group worked on reordering the Statics Concept Inventory questions from more familiar to more challenging, based upon the past performance of the initial students taking the survey. This paper describes the process and results of the effort to reorder this instrument in order to increase Construction student participation and, therefore, the researchers’ ability to measure the impact of the Mechanix system. 

Sketching free body diagrams is an essential skill that students learn in introductory physics and engineering classes; however, university class sizes are growing and often have hundreds of students in a single class. This situation creates a grading challenge for instructors as there is simply not enough time nor resources to provide adequate feedback on every problem. We have developed a web-based application called Mechanix to provide automated real-time feedback on hand-drawn free body diagrams for students. The system is driven by novel sketch recognition algorithms developed for recognizing and comparing trusses, general shapes, and arrows in diagrams. We have discovered students perform as well as paper homework or other online homework systems which only check the final answer through deployment to five universities with 450 students completing homework on the system over the 2018 and 2019 school years. Mechanix has reduced the amount of manual grading required for instructors in those courses while ensuring students can correctly draw the free body diagram. 

Introductory engineering courses at large universities often number over a hundred students, while online classes can have even larger enrollments, significantly constraining instructors’ ability to provide feedback on homework, including the free-body diagrams (FBDs). Most online homework systems do not provide feedback on FBDs if the systems even allow the submission, and instructors often lack time or resources to provide this. A few systems have been developed that use a menu-based system allowing students to creative FBDs. There is a growing concern amongst engineering educators that student lacks critical sketching skills and the ability to idealize a real-world system as a free body diagram (FBD). A sketch-recognition based tutoring system, Mechanix, allows learners 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. 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. The current project implements Mechanix at five different universities obtaining Pre/Post Concept Inventory, homework, and exam scores. It is compared against either the university's current online system or paper-based homework. Focus groups provide further insight into the students’ perceptions about the impact of Mechanix on their learning. 

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