Massachusetts Institute of Technology, Computer Science and Artificial Intelligence Lab,
I am incredibly grateful for the opportunity to intern at MIT’s Computer Science and Artificial Intelligence Lab (CSAIL). I worked with the Anyscale Learning for All (ALFA), a research group focused on scalable machine learning technology and data mining for fields including education and cybersecurity. I was focused on their educational research, and spent the summer working with a data set from MIT 6.00.1x, a Massively Open Online Course (MOOC) teaching students introductory coding. MOOCs have become a hot topic for research because of their scalability and accessibility to anyone with internet access. Our focus was on reflective learning in MOOCs, as it may be more difficult or less common to reflect on learned material in an online course with little instructor feedback. Our goal was to develop tools to analyze these reflections, which consisted of free text responses to various questions, and gather information that might be used to improve the course in the future. This was done using Natural Language Processing (NLP), a subfield of artificial intelligence dedicated to analyzing human language. We have presented our results to the instructor of the course and others within the CSAIL organization, and I have written a paper which is being prepared for submission to the 2021 International Conference on Learning Analytics and Knowledge.
Working with ALFA has helped me develop many skills which extend beyond their specific field of work. Working with another undergraduate intern, and some of the other researchers, provided valuable experience in collaborating and exchanging ideas. There was also a strong emphasis on presentation, and we communicated our results to many different audiences, including our peers and the instructor of the course. The process of writing a research paper has also been both difficult and worthwhile. Gaining practice in conveying complex ideas and methodologies is something which will be useful in the future in almost any field. And, of course, I gained many technical skills, specifically in machine learning and data science, which will be essential for any future work involving coding.
I really enjoyed the research process and hope to engage in more similar work in the future. Its unstructured and exploratory nature made it really enjoyable, and producing original results was very rewarding. I’ve liked coding since I first learned it years ago, and this summer has further solidified those feelings. I found that the applications to the real world, including presenting our results to the course instructor, added another element of meaning to the work which made it more engaging. I would be very interested in continuing to work in a STEM field with a focus on accessible education or another equity-related initiative. However, I did sometimes find myself wishing that the work was more abstract, as I often have an easier time wrapping my head around theoretical concepts like in mathematics. Overall, my time at ALFA has made me more inclined to continue learning and doing research by attending graduate school in a technical STEM field such as math or computer science.
Finding internships during the coronavirus pandemic was very difficult; I want to thank the ’68 Center and the Kraft Family for this incredible experience.