Meet Chinmay Kulkarni, who joined the Human-Computer Interaction Institute (HCII) faculty last year. Kulkarni shares his background, research motivation and what students can expect from his classes.
What was your background before joining the HCII?
It's not everyday that a Human-Computer Interaction Institute (HCII) capstone project brings you to the White House to present your work, but that's what happened for Masters of Educational Technology and Applied Learning Science (METALS) student Kathy Yu.
Technology use continues to rise in schools as an important means for teachers to create a more personalized learning experience for students. Schools are increasingly dedicating significant budgets to apply educational technology to classrooms, as much as 6.6 billion in the U.S. alone.
Mark Potter is a 2014 graduate from the Masters of Educational Technologies and Applied Learning Science (METALS) at Carnegie Mellon University. Though he originally was pursuing a career in accounting, his time spent tutoring students helped him realize his passion for improving educational outcomes.
What was your background before you entered the METALS program?
Can past learning activities predict differences in individual student success? A recent project with researchers from the Human-Computer Interaction Institute (HCII) set out to answer just that, and picked up a Best Paper award along the way.
First authored by postdoctoral fellow Michael Eagle, the paper "Predicating Individual Differences for Learner Modeling in Intelligent Tutors from Previous Learner Activities" was awarded Best Paper during the User Modeling Adaption and Personalization (UMAP 2016) conference.
Carnegie Mellon University, like other colleges and universities, is able to create smaller learning cohorts from large lectures by using teaching assistants. These TAs often have varied backgrounds and levels of familiarity with the U.S. educational system, which can make learning experience and outcomes differ from section to section.
Amy Ogan, an assistant professor in the HCII and an educational technologist, is fascinated by researching ways to make learning more engaging, effective and enjoyable. Ogan is also a recent recipient of the Jacobs Foundation Research Fellowship, a global fellowship program for the research on child and youth development.
Our Connection Machines project investigates nonverbal and verbal behaviors of two partners in a conversation setting in the context of rapport. We have collected data on teenagers conducting a peer tutoring task in linear algebra. We are currently investigating nonverbal behaviors, such as smile, gaze, prosody and pitch, and verbal content, such as second person pronoun use, of the participants in the dialogue.
The AdaptErrEx project, funded by the U.S. Department of Education, has developed materials to support learning of decimals through erroneous examples. The main goals are to support deeper, more robust learning and to improve error-detection skills. All the materials developed on the AdaptErrEx project will eventually be freely available through MathTutor, a website that helps middle school students learn math.
In this project, we aim to address the systematically-reduced standardized test scores of African American students compared to their Euro-American peers by using virtual peer technology to understand the role of dialect, and more broadly, cultural congruence, on students's performance, and to help students achieve in the classroom.
