Clare Boothe Luce Assistant Professor of Computer Science
- I will be speaking about the MaGE peer mentoring program on two panels at SIGCSE 2017
- Th 3/9 3:45pm: New Tools and Solutions to Address the CS Capacity Crunch
- Fri 3/10 3:45pm: Scaling Introductory Courses Using Undergraduate Teaching Assistants
- Received a NSF National Robotics Initiative grant: Understanding the Influence of a Teachable Robot on STEM Skills and Attitudes
- We made a website to share the MaGE peer mentor training curriculum materials!
Megas and Gigas Educate
At Mount Holyoke College, we are developing a new technical peer mentoring program: Megas and Gigas Educate (MaGE). The goals of MaGE are to grow enrollment capacity in introductory computer science courses while maintaining close interaction and quality feedback, to increase enrollment and retention for women and other underrepresented groups, and to train students to educate, mentor, and support others in inclusive ways.
As part of the Megas and Gigas Educate program, the MaGE Training Course prepares students for the task of educating, mentoring, and supporting others in inclusive ways. This training course raises awareness of the role of social identity in learning, emphasizes active learning within computer science, and provides preparation for being technical peer mentors. We are excited to share our curriculum materials with the community, in hopes that other educators and students might consider adopting similar peer mentor training at their institutions.
Research interests: spoken language processing, human-robot interaction, and computer science education. I am the director of the Interactive Computing Research Lab at Mount Holyoke College where we are studying spoken language processing in the context of human-robot interaction.
While speech is a natural way to communicate with robots, most robots are not able to recognize or respond to the subtleties of spoken language. Our spoken interactions with robots, dialogue systems (e.g., Siri), and other devices are not as natural as conversing with another human.
Sometimes, it's not what you say, but how you say it: in everyday communication, people use intonation, loudness, and timing to convey emphasis and emotion — a layer of meaning beyond the semantic content of the words that are spoken. For example, questions are frequently signaled by rising intonation. Affective and cognitive states such as annoyance, engagement, confidence and uncertainty might conveyed through a combination of signals.
In the Interactive Computing Research Lab, we address basic scientific questions about how humans use spoken natural language when communicating (i) with other humans, (ii) with computers, and (iii) with robots. We study human-human conversation to understand phenomena such as acoustic-prosodic entrainment. We develop algorithms to automatically find patterns in speech data, which enable affect recognition. And we explore how these methods can inform the design of intelligent, adaptive human-robot interactions.
Watch the video below to see some of the recent projects with Nico, a humanoid robot. We are in the process of creating a physical testbed for conducting human-robot natural language interaction experiments.
Take a look at my publications page to see past projects I have worked on in spoken dialogue systems, intelligent tutoring systems, recognition of uncertainty in speech, and analysis of acoustic-prosodic entrainment.
Undergraduate Research Students
- Tricia Chaffey
- Ranjini Das
- Mahima Ghale
- Hyeji Kim
- Rebecca Kim
- Raeesa Mehjabeen
- Emilia Nobrega
- Nichola Lubold (ASU, Ph.D. student, co-advised with Erin Walker)
- Arun Reddy Nelakurthi (ASU, M.S. 2014)
Links For Students
|Chart of MHC Computer Science Courses|
|Instructions for requesting letters of recommendation|
|Map of Clapp Laboratory/where to park|
- 4/11/17, MHC News, Computing for social impact
- 2/16/17, Google Research Blog, The CS Capacity Program - New Tools and SIGCSE 2017
- 3/11/15, MHC News, Google funds new computer science initiative
- 2/12/15, MHC News, MassMutual partnership propels women in data science
- 10/17/14, MHC News, "Gigas and Megas" mentor program launched
- 10/5/14, Mount Hoyloke News, Faculty Profile: Professor Heather Pon-Barry and College collaborate to bring robots to life
Other Activities and Affiliations
I'm a member of Mount Holyoke's Committee on Data Science.
I'm an Adjunct Assistant Professor in the College of Information and Computer Sciences at UMass Amherst.
Computer Science Department
Mount Holyoke College
50 College Street
South Hadley, MA 01075