Although participating in this REU has taught me an incredible amount about coding in a team, using python's pandas and sklearn libraries, and academia as a whole, the largest lesson I've learned so far is how iterative the research process can be.

Despite the fact that our broad topic has not changed, over the past few weeks our approach to our problem has transformed many times. With each new piece of knowledge about our data, we are confronted with new paths forward; with each preliminary result, we gain insights as to what is meaningful in the context of our field. The REU lasts only 10 weeks, but the cyclic process I've experienced with just this project helps me understand why some research projects can last for years. Although Anlan and I are working with a fairly narrow scope--CS student success in college and how it relates to specific courses taken--there are so many avenues to explore each week as we continue to work with our data. I look forward to both following the trails we've yet to explore and learning about the final steps in the research cycle at the end of this summer.