ksteph [at] cs.berkeley.edu
Computer Science PhD Student
360 Hearst Memorial Mining Bldg
UC Berkeley, 94720-1776
I am a Computer Science PhD candidate at UC Berkeley. My Master's research work is in computer networking with Vern Paxson. My PhD research interest lies at the intersection of education and computer science focusing on using data available in large classrooms (both local and MOOCs), and I am advised by Armando Fox. I sit in the Berkeley institute of Design (BiD) lab.
My specific research interest is on looking at the data from machine-gradeable assessments, with the goal to find interpretable data-driven insights that help instructors find ways to improve their course material. I currently perform a qualitative analysis on constructed response wrong answers from "What would Python display?" question sets. Then use quantitative approaches to identify common student errors and deliver guidance based on these errors to students in situ.
I am the founder and former CS-coordinator of EECS Peers. A group dedicated to supporting fellow graduate students with grad school life. At the end of Fall 2016, I finished running an EECS Peers small group as an experiment with first year students in education research. We read 57 Ways to Screw Up in Grad School: Perverse Professional Lessons for Graduate Students, which I highly recommend. I hope to expand this idea to create more small groups, given the positive impact it had on the first years and myself.
In 2012-2013 I served as the computer science co-president for Women In Computer Science and Electrical engineering (WICSE). And I have volunteered as a role model at Techbridge, an after school program to inspire girls in technology, science, and engineering.
I am currently mentoring four undergraduate researchers and have mentored six others. I participate in the WICSE Graduate Little Sisters program; mentoring five graduate women over the past four years. Finally, I have participated in the WICSE Undergraduate Little Sisters program for three years, mentoring four undergrad women. One went on to graduate school at John Hopkins and the other three to industry.
I have served as a teaching assistant for six semesters for a total of five courses. Two of the courses were for introductory computer science, one for computer science majors (CS61A) and the other for non-majors (CMSC198K). Two of the courses were for upper division, covering networking (EE122) and software engineering (CS169). The final course was an undergraduate seminar that I co-instructed and created a large portion of the material for (CS194-25). CS169 and EE122 involved over 100 students and CS61A included over 1,000 in Fall 2015 and over 800 in Spring 2016. As an undergraduate, I served as a reader, who graded assignments and held office hours.
Undergraduate at University of Maryland, College Park
I graduated summa cum laude from University of Maryland, College Park (UMD) receiving my B.S. in Computer Science. I worked in a variety of research areas while at Maryland including: software engineering with FindBugs, artificial intelligence by applying genetic algorithms to swarm intelligence, and computer networking.
- Kristin Stephens-Martinez, An Ju, Krishna Parashar, Regina
Ongowarsito, Nikunj Jain, Sreesha Venkat, Armando Fox. 2017. Taking
Advantage of Scale by Analyzing Frequent Constructed-Response, Code
Tracing Wrong Answers ACM International Computing Education Research 2017. ACM ICER
- Kristin Stephens-Martinez, An Ju, Colin Schoen, John DeNero,
Armando Fox. Identifying Student Misunderstandings using Constructed
Responses. Extended Abstract at Learning At Scale 2016. ACM L@S '16.
[extended abstract pdf]
- Kristin Stephens-Martinez, Marti A. Hearst, and Armando
Fox. 2014. Monitoring MOOCs: Which Information Sources Do Instructors
Value? ACM Learning At Scale 2014. ACM L@S
- Kristin Stephens, Shaddi Hasan, and Yahel
Ben-David. 2012. MultiWAN: WAN Aggregation for Developing Regions.
In Proceedings of the 2nd ACM Symposium on Computing for Development. ACM
DEV '12. (poster) [pdf]
- Brian Cole, Dan Hakim, Dave Hovemeyer, Reuven Lazarus, William Pugh, and Kristin Stephens. 2006. Improving your software using static analysis to find bugs. In Companion To the 21st ACM SIGPLAN Symposium on Object-Oriented Programming Systems, Languages, and Applications. OOPSLA '06. [pdf]
- (Master's report) Kristin Stephens. 2013. Towards Sound HTTP Request Causation Inference. EECS Department, University of California, Berkeley. UCB/EECS-2013-141
- University of CA, Berkeley
- CS169 Software Engineering (Fall 2016, Teaching Assistant, Armando Fox)
- CS61A The Structure and Interpretation of Computer Programs (Spring 2016, Teaching Assistant, Paul Hilfinger)
- CS61A The Structure and Interpretation of Computer Programs (Fall 2015, Teaching Assistant, John DeNero)
- CS194-25 Special topics: Building Your Next Generation Education Technologies (Fall 2012, Teaching Assistant/Co-Instructor, Dawn Song)
- EE122 Introduction to Communication Networks (Fall 2011, Teaching Assistant, Scott Shenker)
- University of MD, College Park
- Association for Computing Machinery
Honors and Awards
- Outstanding Graduate Student Instructor - UC Berkeley
- National Science Foundation Graduate Research Fellowship
- UC Berkeley Chancellor's fellowship
- Outstanding Undergraduate of 2009 for The College of Computational, Mathematical, and Physical Sciences (UMD)
- UMD CS Department Teaching Excellence Award for an Undergraduate Teaching Assistant
I post articles and interesting stuff I find on the Internet to my Google plus account.
My arts and craft hobbies can also be seen on my blog Hobby Sanity.