About
Office hours for Fall 2019: TBD
Fall 2019 I'm teaching CS376: HCI and CS103: Electronic Textiles.
Spring 2020 I'm teaching CS134: Introduction to Computer Science.
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I am a human-computer interaction researcher and learning scientist focusing on enabling learners to overcome obstacles to effective participation in their learning process. Currently, I am an Assistant Professor of Computer Science at Williams College. I have also spent some time as a postdoctoral research fellow in Stanford working with the LINK Research Lab and the Lytics Lab.
My research combines human-computer interaction methodologies with an awareness of education research theory. To inform the design of educational technology for learners and instructors I perform user studies to understand human behavior and learning-processes in digital learning environments, develop approaches for refining and displaying relevant student data, and generate design recommendations by analyzing human behavioral responses and learning with these new approaches.
Publications
OARS: exploring instructor analytics for online learning
Jonathan Bassen, Iris Howley, Ethan Fast, John Mitchell, Candace Thille
l s, Learning at Scale, 2018 May 25
Assessment of Discussion in Learning Contexts
Carolyn Penstein Rosé, Iris Howley, Miaomiao Wen, Diyi Yang, Oliver Ferschke
2016 Nov 31, pp. 81-94
Student agency to participate in dialogic science discussions
Sherice N. Clarke, Iris Howley, Lauren Resnick, Carolyn Penstein Rosé
Learning, Culture and Social Interaction, vol. 10, 2016 Jul 31, pp. 27-39
Towards Careful Practices for Automated Linguistic Analysis of Group Learning
Iris K Howley, Carolyn Penstein Rose
Journal of learning Analytics, vol. 3(3), 2015 Nov 31, pp. 239-262
Can a Social Robot Stimulate Science Curiosity in Classrooms
Masahiro Shiomi, Takayuki Kanda, Iris K. Howley, Kotaro Hayashi, Norihiro Hagita
International Journal of Social Robotics, vol. 7(5), 2015 Sep 31, pp. 641-652
View all
Projects
Explaining Algorithmic Systems to End Users
Users rely on algorithmic systems to assist in decision-making without understanding potential biases and flaws of those algorithms. This [project investigates algorithmic understanding and how it influences teacher and learner decision making.
Identifying Critical Reading Skills at Scale
Applying machine learning techniques to digital annotations to automatically identify student reading strategies.
Courses
Human-Computer Interaction
This course provides an introduction to the field of human-computer interaction, through a user-centered approach to designing and evaluating interactive systems.
Electronic Textiles
This course involves a series of projects to gain practice in necessary skills such as programming and sewing. Then, students will design their own eTextiles projects, implementing them with Lilypad Arduino components.
