AI Grand Challenges for Education

This article focuses on contributions that AI can make to address long-term educational goals. It describes five challenges that would support: (1) mentors for every learner; (2) learning twenty-first century skills; (3) interaction data to support learning; (4) universal access to global classrooms; and (5) lifelong and life-wide learning. A vision and brief research agenda are described for each challenge along with goals that lead to access to global educational resources and the reuse and sharing of digital educational resources. Instructional systems with AI technology are described that currently support richer experiences for learners and supply researchers with new opportunities to analyze vast data sets of instructional behavior from big databases, containing elements of learning, affect, motivation, and social interaction. Personalized learning is described using computational tools that enhance student and group experience, reflection, and analysis, and supply data for development of novel theory development.

[1]  Kasia Muldner,et al.  The Impact of Animated Pedagogical Agents on Girls' and Boys' Emotions, Attitudes, Behaviors and Learning , 2011, 2011 IEEE 11th International Conference on Advanced Learning Technologies.

[2]  D. Suthers,et al.  Belvedere: Engaging students in critical discussion of science and public policy issues. , 1995 .

[3]  Geoffrey I. Webb,et al.  # 2001 Kluwer Academic Publishers. Printed in the Netherlands. Machine Learning for User Modeling , 1999 .

[4]  Beverly Park Woolf,et al.  Recognizing Dialogue Content in Student Collaborative Conversation , 2010, Intelligent Tutoring Systems.

[5]  Ryan Shaun Joazeiro de Baker,et al.  Modeling and understanding students' off-task behavior in intelligent tutoring systems , 2007, CHI.

[6]  Kurt VanLehn,et al.  The Andes Physics Tutoring System: Lessons Learned , 2005, Int. J. Artif. Intell. Educ..

[7]  D. Suthers.  Representational guidance for collaborative inquiry. , 2003 .

[8]  Beverly Park Woolf,et al.  Inferring learning and attitudes from a Bayesian Network of log file data , 2005, AIED.

[9]  Beverly Park Woolf,et al.  A Roadmap for Education Technology , 2011 .

[10]  Alfred Kobsa,et al.  The Adaptive Web, Methods and Strategies of Web Personalization , 2007, The Adaptive Web.

[11]  Kasia Muldner,et al.  Emotion Sensors Go To School , 2009, AIED.

[12]  Daniel L. Schwartz,et al.  Inventing to Prepare for Future Learning: The Hidden Efficiency of Encouraging Original Student Production in Statistics Instruction , 2004 .

[13]  D. Mackeracher.  Making Sense of Adult Learning , 1993 .

[14]  Beverly Park Woolf,et al.  Improving the Efficiency of Automatic Knowledge Generation through Games and Simulations , 2013, AIED.

[15]  อนิรุธ สืบสิงห์,et al.  Data Mining Practical Machine Learning Tools and Techniques , 2014 .

[16]  Kurt VanLehn,et al.  The Behavior of Tutoring Systems , 2006, Int. J. Artif. Intell. Educ..

[17]  Stuart Hannabuss,et al.  Understanding Careers: The Metaphors of Working Lives , 2008 .

[18]  Beverly Park Woolf,et al.  Critical Thinking Environments for Science Education , 2005, AIED.

[19]  Stephen Brand,et al.  Creating Small Learning Communities: Lessons From the Project on High-Performing Learning Communities About “What Works” in Creating Productive, Developmentally Enhancing, Learning Contexts , 2007 .

[20]  Cristina Conati,et al.  Student Modeling: Supporting Personalized Instruction, from Problem Solving to Exploratory Open Ended Activities , 2013, AI Mag..

[21]  D. Laurillard.  Digital Technologies and Their Role in Achieving Our Ambitions for Education , 2008 .

[22]  Vincent Aleven,et al.  Improving Contextual Models of Guessing and Slipping with a Trucated Training Set , 2008, EDM.

[23]  Eric Wargo,et al.  Psychological Science in the Public Interest , 2006 .

[24]  Ryan Shaun Joazeiro de Baker,et al.  Developing a generalizable detector of when students game the system , 2008, User Modeling and User-Adapted Interaction.

[25]  Tom Murray,et al.  Authoring Intelligent Tutoring Systems: An analysis of the state of the art , 1999 .

[26]  Ryan Shaun Joazeiro de Baker,et al.  New Potentials for Data-Driven Intelligent Tutoring System Development and Optimization , 2013, AI Mag..

[27]  Raymund Sison,et al.  Student Modeling and Machine Learning , 1998 .

[28]  Stuart Hall,et al.  Fast Facts , 2014 .

[29]  David W. Johnson,et al.  AN OVERVIEW OF COOPERATIVE LEARNING , 2002 .

[30]  Axel Bruns.  Beyond difference : reconfiguring education for the user-led age , 2007 .

[31]  V. Shute.  SteAlth ASSeSSment in computer-BASed GAmeS to Support leArninG , 2011 .

[32]  Beverly Park Woolf,et al.  A Dynamic Mixture Model to Detect Student Motivation and Proficiency , 2006, AAAI.

[33]  Neil T. Heffernan,et al.  Opening the Door to Non-programmers: Authoring Intelligent Tutor Behavior by Demonstration , 2004, Intelligent Tutoring Systems.

[34]  H. Chad Lane,et al.  The Effects of a Pedagogical Agent for Informal Science Education on Learner Behaviors and Self-efficacy , 2013, AIED.

[35]  Daniel D. Suthers,et al.  An Experimental Study of the Effects of Representational Guidance on Collaborative Learning Processes , 2003 .

[36]  Ashish Kapoor,et al.  Automatic prediction of frustration , 2007, Int. J. Hum. Comput. Stud..

[37]  H. Chad Lane,et al.  Virtual Humans for Learning , 2013, AI Mag..

[38]  Carole R. Beal,et al.  AnimalWatch: An Intelligent Tutoring System for Algebra Readiness , 2013 .

[39]  Tom P. Abeles,et al.  The Diamond Age: Or a Young Lady's Illustrated Primer , 2010 .

[40]  Beverly Park Woolf,et al.  Coaching Within a Domain Independent Inquiry Environment , 2006, Intelligent Tutoring Systems.

[41]  Michael Luck,et al.  Intelligent Virtual Environments , 2005 .

[42]  Wied Ruijssenaars,et al.  Encyclopedia of the Sciences of Learning , 2012 .

[43]  Arthur C. Graesser,et al.  Recent Advances in Conversational Intelligent Tutoring Systems , 2013, AI Mag..

[44]  Ingo Mierswa,et al.  YALE: rapid prototyping for complex data mining tasks , 2006, KDD '06.

[45]  Vincent Aleven,et al.  Scaling Up Programming by Demonstration for Intelligent Tutoring Systems Development: An Open-Access Web Site for Middle School Mathematics Learning , 2009, IEEE Transactions on Learning Technologies.

[46]  Albert T. Corbett,et al.  Human Classification of Low-Fidelity Replays of Student Actions , 2006 .

[47]  Manolis Mavrikis,et al.  Metafora: A Web-Based Platform for Learning to Learn Together in Science and Mathematics , 2013, IEEE Transactions on Learning Technologies.

[48]  Vincent Aleven,et al.  Intelligent Tutoring Goes To School in the Big City , 1997 .

[49]  Matthias Rehm,et al.  Handbook of Research on Culturally-Aware Information Technology : Perspectives and Models , 2010 .

[50]  Neil Selwyn,et al.  Learning through life: The role of technology , 2008 .

[51]  Judy Kay,et al.  Lifelong Learner Modeling for Lifelong Personalized Pervasive Learning , 2008, IEEE Transactions on Learning Technologies.

[52]  Chen-Lin C. Kulik,et al.  Educational Outcomes of Tutoring: A Meta-analysis of Findings , 1982 .

[53]  Beverly Park Woolf,et al.  Intelligent Coaching for Collaboration in Ill-Defined Domains , 2009, AIED.

[54]  Eric Holder,et al.  Remarks at the National Press Club , 2015 .

[55]  Albert T. Corbett,et al.  Why Students Engage in “Gaming the System” Behavior in Interactive Learning Environments , 2008 .

[56]  Arthur C. Graesser,et al.  Toward an Affect-Sensitive AutoTutor , 2007, IEEE Intelligent Systems.

[57]  Kurt VanLehn,et al.  The Andes Physics Tutoring System: Five Years of Evaluations , 2005, AIED.

[58]  Kenneth R. Koedinger,et al.  An Open Repository and analysis tools for fine-grained, longitudinal learner data , 2008, EDM.

[59]  Bruce James,et al.  Chapter 1 – The assessment of vision , 2007 .

[60]  Alfred Kobsa.  User Modeling and User-Adapted Interaction , 2005, User Modeling and User-Adapted Interaction.

[61]  Herbert A. Simon.  What We Know About Learning , 1998 .

[62]  Daniel D. Suthers,et al.  Representational support for collaborative inquiry , 1999, Proceedings of the 32nd Annual Hawaii International Conference on Systems Sciences. 1999. HICSS-32. Abstracts and CD-ROM of Full Papers.

[63]  Beverly Park Woolf,et al.  Building Intelligent Interactive Tutors: Student-centered Strategies for Revolutionizing E-learning , 2008 .

[64]  Matthew Crosby,et al.  Association for the Advancement of Artificial Intelligence , 2014 .

[65]  John R. Anderson,et al.  Cognitive Tutors: Lessons Learned , 1995 .

[66]  Victor Callaghan.  Intelligent Environments , 2014 .

[67]  David J. McArthur,et al.  The roles of artificial intelligence in education : current progress and future prospects: , 2005 .

[68]  Jeremy Roschelle,et al.  Eight Issues for Learning Scientists About Education and the Economy , 2011 .

[69]  John R. Anderson,et al.  Knowledge tracing: Modeling the acquisition of procedural knowledge , 2005, User Modeling and User-Adapted Interaction.

[70]  J. Kolodner.  Facilitating the Learning of Design Practices: Lessons Learned from an Inquiry into Science Education. , 2002 .

[71]  Erik Brynjolfsson,et al.  Race against the machine : how the digital revolution is accelerating innovation, driving productivity, and irreversibly transforming employment and the economy , 2011 .

[72]  Julita Vassileva,et al.  Goal-Based Autonomous Social Agents: Supporting Adaptation and Teaching in a Distributed Environment , 1998, Intelligent Tutoring Systems.

[73]  Stefane M. Kabene,et al.  Handbook of Research on Culturally-Aware Information Technology: Perspectives and Models , 2010 .

[74]  Beverly Park Woolf,et al.  Using an Intelligent Tutor and Math Fluency Training to Improve Math Performance , 2011, Int. J. Artif. Intell. Educ..

[75]  Jonathan P. Rowe,et al.  Goal Recognition with Markov Logic Networks for Player-Adaptive Games , 2011, AIIDE.

[76]  COVER SHEET.  Beyond Difference : Reconfiguring Education for the User-Led Age , 2007 .