Thursday, January 26, 2017

Week 17: 1/18/2017 - 1/25/2017

This week, we discussed the best way to approach the data analysis. I will be using Apache Spark and the command line and running my data projects in the IDE IntelliJ. We weighed the advantages and disadvantages of running Spark through a virtual box, and found using an IDE might be the best way to go. 

I helped to give a demonstration about our eye tracking equipment and software last Friday with one of the graduate CS students at YSU to several groups of high school students. We showed them the interesting aspects of eye tracking as well as the advantages it brings to our field. The students enjoyed the Asteroids game where each time a user starts the game, they have to pop incoming asteroids using only their gaze. We also demonstrated using dual screens how the eye tracker records fixations of any user, and we asked some of the students to find different values on the YSU website. 

I gathered two students in the CIS department to participate in our study. This Friday, my first volunteer will be coming in to the Empirical studies lab. I hope to gain at least 4-6 more students throughout the semester so that we can continue to analyze fresh data. 

Next week, I will be finishing up my poster for the Ohio Celebration of Women in Computing based on the analysis of our first set of data. I will be attending the conference on February 24-25 with Dr. Sharif, Dr. Lazar, Jenna and a few other students in the computer science department. I'm excited to attend the talks (as it's my first technical seminar that isn't local) and I can't wait to hear from women with experience in the software engineering field!  What an exciting time to be a woman!  I will be sure to post photos from the seminar upon my return. 

Weeks 16 & 17: 1/11/2017 - 1/25/2017

These past two initial weeks back to school have been hectic, so I decided to combine the posts for the last two weeks together. In addition to beginning data analysis on our Stack Overflow project, I have been working on a separate data analysis to expand upon our expertise prediction analysis from CREU 15-16.  This analysis looks at the ABB eye-tracking data we collected in a different fashion than machine learning prediction algorithms. I used sequential analysis techniques from an R package to look at the data as sequences, so the order of what participants looked at is taken into consideration. Initial results show significant difference in the gaze patterns of novices versus expert. The most challenging part of my analyses was dealing with how large the sequence data is for eye-tracking data. I had to manipulate the R package I was working with to make some of the analyses work with such large data.

We intend to submit these results to a journal and to the Mining Software Engineering Repositories conference (MSR). So, this past two weeks I created and presented a presentation about the analyses I performed to get an idea of what to submit to MSR. I also moved the beginnings of our journal paper to Overleaf in order to write the paper collaboratively.

This past weekend I participated in a 4 day mathematical modeling competition called COMAP. I worked with two other students to model the merging of cars following a toll booth barrier. We wrote and submitted a report detailing our model.

Thursday, January 19, 2017

Week 16: 1/11/2017 - 1/18/2017

It's the start of the Spring semester and we are working on the second half of our project. We are continuing to collect data. This week, we discussed our upcoming trip in February to present at the conference for Ohio Celebration of Women in Computing in Huron, OH. I'm working on creating a poster about the results of our eye tracking data in reference to participant tag scores. I reviewed the results with Jenna, Dr. Sharif and Dr. Lazar, and I am working on a short presentation about the goal of our project. 

I am going to run the data from the research paper 'Predict Closed Questions on Stack Overflow' into Apache Spark and compare the results of the original to what I find. This will be my first time using Apache Spark with the command line and I'm looking forward to learning more about machine learning algorithms.