AUTOMATED GENERATION OF DETAILED PROGRAMMING ASSIGNMENT FEEDBACK

When teaching students computer programming, instructors often teach specific techniques that students should follow. Students are told to program in these ways, but instructors never really know if the techniques are used; and if they are used, then how effective they are. This project produced a Programming Analysis Plug-In (PAPI) to analyze student academic computer programming course work to measure when and how students are working on programming assignments. These measurements include examining the final assignment submitted by a student as well as the steps a student used to get to the final product. To make sure that this data capture is being performed in the most user-friendly way, potential users, both instructors and students, were interviewed for their opinions on how the software should work. It was determined both students and instructors prefer auto-grading software, but it currently lacks formative feedback. It was also postulated that if a teacher can access and easily understand how a student gets to a final result, they can help support struggling students, find class pain points, and discover bad practices on projects. Having an instructor sit down with every student to ask how they programmed an assignment is not feasible in the large classes found in computer science. By automating this process, students can get the feedback that they need to excel. PAPI delivers this feedback by analyzing assignment creation date, last edit date, number of saves, number of character insertions and deletions, and number of comments. This thesis describes the PAPI software, its testing in a computer science course, and the results that indicated starting an assignment early, commenting code, and having lower numbers of text insertions and deletions trend to higher assignment grades. PAPI will have a broad impact because of its compatibility with current technologies and its intuitive ease of use