This past week I wrote the Analysis and Data sections of the paper we are submitting to the Mining Software Repositories conference about mining eye-tracking data for software tasks (an extension of last year's CREU project). I wrote about the within sequence turbulence and entropy analyses I am still gathering results for, and I wrote about the sequence similarity k-means clustering analyses I am also still gather results for. I also prepared and practiced a presentation for the 2017 Nebraska Conference for Undergraduate Women in Mathematics.
Goal
Weekly goal - In the next week, I plan to finish gathering results for the sequential analyses I am performing and write the Results and Discussion sections of the paper. I am also leaving for NCUWM 2017 this weekend to present the sequence similarity analyses.
Long-term goal - To perform many more (roughly 8) sequential analyses on the ABB eye-tracking data we collected three years ago. From this we hope to gain insights into developer gaze patterns and differences among novice and expert programmers. This analysis considers the order in which developers looked at source code elements, so in this way it is different from last year's machine learning analyses.
Outcome(s)
- Large portions of our MSR paper are complete; we are on time to submit by Feb. 10
- R scripts implemented to perform entropy and turbulence sequential analyses using TraMineR
- Partial implementation of R scripts to perform the similarity analyses using TraMineR
- Learned more about the mathematics of the analysis techniques for my presentation
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