Computer-Aided Personalized Education

The demand for education in STEM fields is exploding, and universities and colleges are straining to satisfy this demand. In the case of Computer Science, for example, the number of US students enrolled in introductory courses has grown three-fold in the past decade. Recently massive open online courses (MOOCs) have been promoted as a way to ease this strain, but scaling traditional models of teaching to MOOCs poses many of the same challenges observed in the overflowing classrooms, namely, assessment of students' knowledge and providing meaningful feedback to individual students. This motivates a new agenda for computing research: formalize tasks such as assessment and feedback as computational problems, develop algorithmic tools to solve resulting problems at scale, and incorporate these tools effectively in learning environments.

 

Automated tutoring has been studied at different times in different communities. Top-down approaches based on formal logical reasoning are rooted in research on formal verification and synthesis. The resulting tools for tasks such as automatic generation of problems, automatic grading, and automatic generation of hints have been developed for problems arising in a number of CS courses such as algorithms, automata theory, compilers, databases, and programming. At the opposite end of the spectrum of automated tutoring technology, bottom-up approaches based on machine learning mine data from learning experiences of students. Emerging applications of this approach range from learning analytics tools for students and instructors to track learning progress to personalized feedback tools that recommend the next best learning activity to a student based on past history.

 

The goal of this workshop is to bring together researchers developing educational tools based on technologies such as logical reasoning and machine learning with researchers in education, human-computer interaction, and psychology to articulate a long-term research agenda. The focus will be on college-level courses in computer science, mathematics, and physics. The workshop is expected to foster new collaborations among participants from diverse disciplines, suggest new research directions in computer-aided education, inspire other researchers to work on these problems, and ultimately result in technology for effective and personalized learning.

LOGISTICS

Date: November 12-13, 2015
Location: Washington, D.C.
Hotel: Marriott Wardman Park

The Computing Community Consortium (CCC) will cover travel expenses for all participants who desire it. The CCC will make hotel reservations at the workshop hotel.  Participants will be asked to make their own travel arrangements to get to the workshop, including purchasing airline tickets. Following the symposium, CCC will circulate a reimbursement form that participants will need to complete and submit, along with copies of receipts for amounts exceeding $75.

In general, standard Federal travel policies apply: CCC will reimburse for non-refundable economy airfare on U.S. Flag carriers; per diem amounts will be enforced; and no alcohol will be covered.

For more information on Federal reimbursement guidelines, please follow the links below: 

General Travel
International Travel

Additional questions about the reimbursement policy should be directed to Ann Drobnis, CCC Director (adrobnis [at] cra.org).

 
AGENDA

Will be posted closer to the workshop. 

 
ORGANIZING COMMITTEE

Rajeev Alur, University of Pennsylvania  
 
Rich Baraniuk, Rice University  
 
Rastislav Bodik, University of California, Berkeley  
 
Ann Drobnis, Director of the Computing Community Consoritum  
 
Sumit Gulwani, Microsoft
 
Bjoern Hartmann, University of California, Berkeley
 
Yasmin Kafai, University of Pennsylvania
 
Jeff Karpicke, Purdue University
 
 
Candace Thille, Stanford University 
 
Moshe Vardi, Rice University  
 
Debra Richardson, University of California, Irvine
 
Ran Libeskind-Hadas, Harvey Mudd College