I am an Assistant Professor of the Practice at Duke University in the Computer Science Department. I received my Ph.D. in Computer Science at UC Berkeley. My Master's research work, also at UC Berkeley, is in computer networking with Vern Paxson. My 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 was advised by Armando Fox. I used to sit in the Berkeley institute of design (BiD) lab.
My specific research interest is on looking at the data from machine-gradable assessments, with the goal to find interpretable data-driven insights that help instructors find ways to improve their course material. I am, currently, performing a qualitative analysis on constructed response wrong answers from "What would Python display?" question sets. I then use quantitative approaches to identify common student errors and deliver guidance based on these errors to students in situ.
Below are highlights from the full version of my CV.
I am the founder and former CS-coordinator of EECS Peers at UC Berkeley. 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 graduate students in education research. We read 57 Ways to Screw Up in Grad School: Perverse Professional Lessons for Graduate Students, which I highly recommend.
In 2012-2013 I served as the computer science co-president for Women In Computer Science and Electrical engineering (WICSE). Moreover, I have volunteered as a role model at Techbridge, an after-school program to inspire girls in technology, science, and engineering.
At UC Berkeley I mentored ten undergraduate researchers. I, also, participated in the WICSE Graduate Little Sisters program; mentoring five graduate women over 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, UCB) and the other for non-majors (CMSC198K, UMD). Two of the courses were for third and fourth-year undergraduates, covering networking (EE122, UCB) and software engineering (CS169, UCB). The final course was an undergraduate seminar that I co-instructed and created a large portion of the material for (CS194-25, UCB). 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 The University of Maryland, College Park
I graduated summa cum laude from the 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, Armando
Fox. 2018. Giving Hints is Complicated: Understanding the
challenges of an automated hint system based on frequent
wrong answers. In Proceedings of the 23rd Annual ACM
Conference on Innovation and Technology in Computer Science
Education 2018. ACM ITiCSE
- Kristin Stephens-Martinez, Krishna Parashar,
Regina Ongowarsito, Nikunj Jain, Kavi Gupta, Armando
Fox. 2018. Giving Hints is Complicated: Understanding
the challenges of an automated hint system based on frequent
wrong answers. Bay Area Learning Analytics Conference
2018. BayLAN '18. (poster) [pdf]
- 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.
- 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]
- (Ph.D. Thesis) K. Stephens-Martinez, Serving CS Formative Feedback on Assessments Using Simple and Practical Teacher-Bootstrapped Error Models, EECS Department, University of California, Berkeley, Tech. Rep. UCB/EECS-2017-166, Nov. 2017.
- (Master's Report) Kristin Stephens. 2013. Towards Sound HTTP Request Causation Inference. EECS Department, University of California, Berkeley. UCB/EECS-2013-141
- Duke University
- CompSci 116 Foundations of Data Science (Fall 2019)
- CompSci 101 Introduction to Computer Science (Fall 2019)
- CompSci 101 Introduction to Computer Science (Spring 2019)
- CompSci 101 Introduction to Computer Science (Fall 2018)
- CompSci 101 Introduction to Computer Science (Spring 2018), Co-teaching with Owen Astrachan
- 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
- Master's Students
- Ji Yeon Kim (2019)
- 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 love arts and crafts, especially crochet, as well as making origami earrings, chocolates, and other crafts that catch my eye. In an attempt to keep a record of my creations I write about them on my blog Hobby Sanity.