Jennifer Kay, Ph.D.

Jennifer Kay, Ph.D.

Jennifer Kay, Ph.D.
Professor

Jennifer Kay, Ph.D.
Computer Science & Research

Contact Info
856-256-4500 ext. 64593
Robinson 328S

Biography

Dr. Kay received her B.S. in Mathematics and B.S.E in Computer Science & Engineering from University of Pennsylvania, and both her M.S and Ph.D. in Computer Science from Carnegie Mellon University. Her research interests are Computer Science Education, Educational Robotics, Effective Systems for Learning at Scale (MOOCs), Intelligent Software Agents, Robotics (Especially Mobile Robots), Vehicle Teleoperation, Human-Computer Interaction, User Interfaces, Computers and the Elderly, Cryptography, Computer Vision, and Artificial Intelligence.

She has taught the following courses at Rowan: Computer Science & Programming, Data Structures, Design and Analysis of Algorithms, Robotics, Foundations of Computer Science, Introduction to Programming, Introduction to Scientific Programming, Introduction to Programming Using Robots, and Introduction to Object Oriented Programming.

Education:
BSE (Computer Science and Engineering), University of Pennsylvania
BA (Mathematics), University of Pennsylvania
MS (Computer Science), Carnegie Mellon University
PhD (Computer Science), Carnegie Mellon University

Research Expertise:
Educational Robotics | Computer Science Education | Effective Systems for Learning at Scale (MOOCs) | Artificial Intelligence | Robotics | Human-Computer Interaction | Intelligent Software Agents

My most recent work is in two areas: the development and evaluation of methods to introduce novices to Computer Science & Computational Thinking using Robotics and Effective Systems for Learning at Scale (MOOCs). I have received grants to pursue this work from a wide variety of sources including Google, iRobot, the National Science Foundation, and the Institute for Personal Robots in Education.

Honors and Awards:
Rowan University Academic Advising Wall of Fame 2016
Lindback Award for Distinguished Teaching, Rowan University 2013
Best Paper Award, CCSCE 2009

Member of:
ACM (Senior Member)
IEEE (Senior Member)
UPE CS Honor Society

Recent Publications:

  • Kay JS, Nolan TJ, Grello TM (2016) The Distributed Esteemed Endorser Review: A Novel Approach to Participant Assessment in MOOCs, in Proceedings of the Third Annual ACM Conference on Learning@Scale, 157-160.
  • Kay JS, Moss JG, Engelman S, McKlin T (2014) Sneaking In Through The Back Door: Introducing K-12 Teachers to Robot Programming, in Proceedings of the 45th ACM Technical Symposium on Computer Science Education, SIGCSE pp 499-504.
  • Kay JS, McKlin T (2014) The Challenges of Using a MOOC to Introduce ‘Absolute Beginners’ to Programming on Specialized Hardware, in Proceedings of the first ACM Conference on Learning @ Scale, pp 211-212.