The Vertically-Integrated Projects (VIP) Program is an undergraduate education program that operates in a research and development context. Undergraduate students who join VIP teams earn academic credit for their participation in design and discovery efforts that assist faculty and graduate students with research and development issues in their areas of technical expertise.
C21U faculty leads VIP teams each semester in research areas applicable to educational technology and innovation.
Current C21U VIP Team: Data-Driven Education
TEAM ADVISORS: Michael Schatz (Physics), Yakut Gazi (GTPE), Stephen Harmon (C21U/GTPE), Rob Kadel (C21U)
GOALS: This team focuses on the effects that data are having in shaping education, on how new, rich, educational data sources can be used to improve content, instruction, and learning. Specifically, we look to the vast array of data that can be collected around educational opportunities at Georgia Tech and how those data shape educational practice.
METHODS & TECHNOLOGIES: Big data, learning analytics, educational research, learning science, social statistics, hypothesis testing.
RESEARCH/DESIGN ISSUES: Georgia Tech utilizes a variety of digital platforms to foster education from our learning management systems to Piazza discussion forums to MOOC platforms such as Coursera and edX. These platforms generate myriad data points about the trajectory of learning, ranging from content and video consumption to forum participation to assessments of learning to background characteristics of the learners. However, much of this information goes unused both in terms of research for understanding learners and research for improving instruction.
MEETING TIME: Tues, 12:00-12:50
PARTNERS & SPONSORS: TBD
MAJORS, PREPARATION AND INTERESTS:
CmpE, CS, CM – Background/interest in systems, databases, information security, networking. Database and server configuration experience would be helpful but is not required.
STC, HSTS – Background/Interest in statistical methods for hypothesis testing using behavioral data. R, SPSS, SAS experience helpful but not required.
MGMT, Analytics – Background/interest acquisition and management of large data streams, creation and interpretation of mathematical models.
PHYS – Background/interest in improving/enhancing physics instruction..
CONTACT: Dr. Rob Kadel