****New **** Closing song by Jack Mostow lyrics video

****New **** Break-out working group sessions: task description
TASK1: Design an improved annotation scheme for intrinsic human evaluation of QG
TASK2: Design an extrinsic task-based evaluation scenario (a game or a task) for QG

Group1: Vasile Rus, Wei Chen, Pascal Kuyten, Ron Artstein, Elnaz Nouri (slides task1) (slides task2)
Group2: Jack Mostow, Lee Becker, Julius Goth, Claire McConnell, Itziar Aldabe (slides task1) (slides task2 - winners of TASK2 by popular vote!)
Group3: Aravind Joshi, Donna Gates, Sandra Williams, Xuchen Yao, Sarah Luger (slides - winners of TASK1 by popular vote)


Asking questions is a fundamental cognitive process that underlies higher-level cognitive abilities such as comprehension and reasoning. Ultimately, question generation allows humans, and in many cases artificial intelligence systems, to understand their environment and each other. Research on question generation (QG) has a long history in artificial intelligence, psychology, education, and natural language processing. One thread of research has been theoretical, with attempts to understand and specify the triggers (e.g., knowledge discrepancies) and mechanisms (e.g., association between type of knowledge discrepancy and question type) underlying QG. The other thread of research has focused on automated QG, which has far-reaching applications in intelligent technologies, such as dialogue systems, question answering systems, web search, intelligent tutoring systems, automated assessment systems, inquiry-based environments, adaptive intelligent agents and game-based learning environments.

This symposium will foster theoretical and applied research on computational and cognitive aspects of QG bringing together participants from diverse disciplines including, but not limited to, Natural Language Processing, Artificial Intelligence, Linguistics, Psychology, and Education.

For the previous events on Question Generation, please see Question Generation homepage

Resources from the Question Generation challenge are available from the CODA project page

Invited Speakers:

Dr. Patricia Alexander, Department of Human Development, University of Maryland


Dr. Patricia Alexander is the Jean Mullan Professor of Literacy and Distinguished Scholar- Teacher in the Department of Human Development at the University of Maryland. She has served as President of Division 15 (Educational Psychology) of the American Psychological Association, Vice-President of Division C (Learning and Instruction) of the American Educational Research Association, and Past-President of the Southwest Educational Research Association. A former middle-school teacher, Dr. Alexander received her reading specialist degree from James Madison University (1979) and her Ph.D. in reading from the University of Maryland (1981). Since receiving her Ph.D., Dr. Alexander has published over 270 articles, books, or chapters in the area of learning and instruction. She has also presented over 400 papers or invited addresses at national and international conferences. She currently serves as the senior editor of Contemporary Educational Psychology, was past editor of Instructional Science and Associate Editor of American Educational Research Journal-Teaching, Learning, and Human Development, and presently serves on over 10 editorial boards including those for Journal of Literacy Research, Educational Psychologist, and the Journal of Educational Psychology.

Dr. Alexander is a Fellow of the American Psychological Association and the American Educational Research Association, and was a Spencer Fellow of the National Academy of Education. She was recently named the second most productive scholar in Educational Psychology. Her honors include the Oscar S. Causey Award for outstanding contributions to literacy research from the National Reading Conference (2001), the E. L. Thorndike Award for Career Achievement in Educational Psychology from APA Division 15 (2006), and the Sylvia Scribner Career Award from AERA Division C (2007). In addition, she has received various national, university, and college awards for teaching and mentoring.

Dr. Jack Mostow, School of Computer Science, Carnegie Melon University

TITLE: Questions and answers about questions and answers: Lessons from generating, scoring, and analyzing questions in a reading tutor for children (Abstract)

Jack Mostow is a Research Professor at Carnegie Mellon University in Robotics, Machine Learning, Language Technologies, and Human-Computer Interaction, and serves on the Steering Committee for CMU's doctoral Program in Interdisciplinary Educational Research. In 1992 he founded Project LISTEN to develop an automated Reading Tutor that listens to children read aloud. Project LISTEN won the Outstanding Paper Award at the Twelfth National Conference on Artificial Intelligence in August 1994, a United States patent in 1998, inclusion in the National Science Foundation's "Nifty Fifty" research projects in 2000, and the Allen Newell Medal of Research Excellence in 2003.

After earning his A.B. cum laude in Applied Mathematics at Harvard and his Ph.D. in Computer Science at Carnegie Mellon, Dr. Mostow held faculty positions at Stanford, University of Southern California's Information Sciences Institute, and Rutgers. He has served as an Editor of Machine Learning Journal and of IEEE Transactions on Software Engineering, as Program Co-chair of the 1998 National Conference on Artificial Intelligence, as invited keynote speaker at the 2004 meeting of the Association for Computational Linguistics, and as Conference Chair of the 2010 International Conference on Intelligent Tutoring Systems. He is a Voting Member of the Society for the Scientific Study of Reading, at several of whose annual meetings he has presented his research. In 2010 he was elected President of the International Artificial Intelligence in Education Society.

Dr. Vasile Rus, Department of Computer Science, University of Memphis


Dr. Vasile Rus is an Associate Professor of Computer Science with a joint appointment in the Institute for Intelligent Systems. His primary research area is natural language processing with an emphasis on knowledge representations for deep understanding of human languages. Dr. Rus' ongoing projects span topics such as automated question generation (funded by NSF), semantic similarity (funded by NSF and IES), intelligent tutoring systems with natural language interaction (funded by IES), and mining large software repositories (funded by The University of Memphis' STEP program). Among other accomplishments, Dr. Rus has been recently named a Systems Testing Research Fellow of the Fedex Institute of Technology, appointed Associate Editor for the International Journal of Artificial Intelligence Tools, and served as Area Chair for the 49th Annual Meeting of the Association for Computational Linguistics, the leading conference on natural language processing/computational linguistics research.