The Nifty Assignments special session is about sharing the ideas and ready-to-use materials of successful assignments.

Design sketching is an important skill for designers, engineers, and creative professionals, as it allows them to express their ideas and concepts in a visual medium. Being a critical and versatile skill for many different disciplines, courses on design sketching are often taught in universities. Courses today predominately rely on pen and paper; however, this traditional pedagogy is limited by the availability of human instructors, who can provide personalized feedback. Using a stylus-based intelligent tutoring system called SketchTivity , we aim to eventually mimic the feedback given by an instructor and assess student-drawn sketches to give students insight into areas for improvement. To provide effective feedback to users, it is important to identify what aspects of their sketches they should work on to improve their sketching ability. After consulting with several domain experts in sketching, we came up with several classes of features that could potentially differentiate expert and novice sketches. Because improvement on one metric, such as speed, may result in a decrease in another metric, such as accuracy, the creation of a single score may not mean much to the user. We attempted to create a single internal score that represents overall drawing skill so that the system can track improvement over time and found that this score correlates highly with expert rankings. We gathered over 2,000 sketches from 20 novices and four experts for analysis. We identified key metrics for quality assessment that were shown to significantly correlate with the quality of expert sketches and provide insight into providing intelligent user feedback in the future.

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 student’s 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 teacher’s knowledge of student comprehension. Furthermore, the iterative correction process allows students to learn during a test, rather than simply displaying memorized information.

In an introductory Engineering course with an annual enrollment of over 1000 students, a professor has little option but to rely on multiple choice exams for midterms and finals. Furthermore, the teaching assistants are too overloaded to give detailed feedback on submitted homework assignments. We introduce Mechanix, a computer-assisted tutoring system for engineering students. Mechanix uses recognition of freehand sketches to provide instant, detailed, and formative feedback as the student progresses through each homework assignment, quiz, or exam. Free sketch recognition techniques allow students to solve free-body diagram and static truss problems as if they were using a pen and paper. The same recognition algorithms enable professors to add new unique problems simply by sketching out the correct answer. Mechanix is able to ease the burden of grading so that instructors can assign more free response questions, which provide a better measure of student progress than multiple choice questions do.