Finally, we suggest several directions for future enhancements to the feedback interface.ģ Turning Up the Heat!: Using Fault-Localizing Heat Maps to Help Students Improve Their Code Kenneth R. We also evaluated the performance of two semesters of students and discovered that having the heat maps led to more frequent incremental improvements in their code, as well as reaching their highest correctness score on instructor-provided tests more quickly than students that did not have access to the heat maps. #ASTEROIDS SCREEN WRAP GREENFOOT HOW TO#After using this tool suite in the Fall 2017 semester, we surveyed the students about their perceptions of the utility of the visualization for helping them understand how to find and correct the defects in their code, versus not having access to the heat map. Additionally, we developed a heat map visualization to show the results of the SFL evaluation in context to the student s source code. We then developed an automated process to apply the GZoltar SFL analysis to student submissions in the Web-CAT automated grading system. #ASTEROIDS SCREEN WRAP GREENFOOT MANUAL#A manual inspection of the student code demonstrated that the SFL technique identifies the defective method in the first three most suspicious methods in the student s code 90% of the time. Using the GZoltar toolset, we applied this technique to a set of previously-submitted student assignments gathered from students in our introductory CS course. Drawing on the experiences of the software engineering community, we apply a technique called statistical fault location (SFL) to student program assignments. These tools will provide indications of test case failures or runtime errors, but without debugging skills, students often become frustrated when they don t know where to start. (ABSTRACT) Automated grading systems provide feedback to computer science students in a variety of ways, but often focus on incorrect program behaviors. Edmison, Jr.Ģ Turning Up the Heat!: Using Fault-Localizing Heat Maps to Help Students Improve Their Code Kenneth R. Pérez-Quiñones Na Meng Francisco Servant Rui Abreu NovemBlacksburg, Virginia Keywords: Computer Science Education, Spectrum-based Fault Localization, Adaptive Feedback, Heat Map, Visualization, Debugging Copyright 2019, Kenneth R. Dissertation submitted to the Faculty of the Virginia Polytechnic Institute and State University in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Computer Science and Applications Stephen H. 1 Turning Up the Heat!: Using Fault-Localizing Heat Maps to Help Students Improve Their Code Kenneth R.
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