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Perspective sketching is a skill that is required for a variety of jobs including, but not limited to, architectural design, graphic design, and engineering. Sketching however, is a difficult skill to grasp for people early and can take a while to learn. Recently, there have been many intelligent tutoring systems (ITSs) designed to help improve people’s drawing skills. The feedback system for the perspective drawing lessons in SketchTivity, one such ITS, is currently limited to smoothness, speed, and accuracy of the lines. Our team plans to improve upon this feedback system so that the feedback provided to a user is now more nuanced as well as more actionable to reaffirm future learning. To evaluate our system we will conduct a user study with 40 students that involves going through several sketching lessons and then sketching a street corner in 2-D perspective. We plan to run a between-subjects user study with our participants to determine if our adjustment has any effect on the improvement of sketching skills and the usability of the application. We hope to determine that providing the user with data for their smoothness, speed, and accuracy after four sketching prompts can cause an overall improvement in the students’ scores in comparison to at the end of their sketching session. The algorithm that we created to identify a student’s potential issue we hope will be able to provide accurate, actionable feedback in most situations. The visual alterations we made to SketchTivity we expect to have a positive impact on the perspective feedback system and alter the students sketching performance. In future iterations the algorithm should be further refined and the data collected from the students sketches should be further developed to provide more data to create more actionable recommendations for improved sketching performance and retention.