Toward "Hyper-Personalized" Cognitive Tutors: Non-Cognitive Personalization in the Generalized Intelligent Framework for Tutoring

We are starting to integrate Carnegie Learning’s Cognitive Tutor (CT) into the Army Research Laboratory’s Generalized Intelligent Framework for Tutoring (GIFT), with the aim of extending the tutoring systems to understand the impact of integrating non-cognitive factors into our tutoring. As part of this integration, we focus on ways in which non-cognitive factors can be assessed, measured, and/or “detected.” This research provides the groundwork for an Office of the Secretary of Defense (OSD) Advanced Distributed Learning (ADL)-funded project on developing a “Hyper-Personalized” Intelligent Tutor (HPIT). We discuss the integration of the HPIT project with GIFT, highlighting several important questions that such integration raises for the GIFT architecture and explore several possible resolutions.

[1]  Ryan Shaun Joazeiro de Baker,et al.  Labeling Student Behavior Faster and More Precisely with Text Replays , 2008, EDM.

[2]  Vincent Aleven,et al.  Limitations of Student Control: Do Students Know When They Need Help? , 2000, Intelligent Tutoring Systems.

[3]  A. Elliot,et al.  On the measurement of achievement goals: critique, illustration, and application , 2008 .

[4]  Angela L. Duckworth,et al.  Grit: perseverance and passion for long-term goals. , 2007, Journal of personality and social psychology.

[5]  Robert A. Sottilare,et al.  Passively Classifying Student Mood and Performance within Intelligent Tutors , 2012, J. Educ. Technol. Soc..

[6]  Albert T. Corbett,et al.  Cognitive Tutor: Applied research in mathematics education , 2007, Psychonomic bulletin & review.

[7]  Candace Walkington,et al.  Using Adaptive Learning Technologies to Personalize Instruction: The Impact of Interest-Based Scenarios on Performance in Algebra , 2012, ICLS.

[8]  Vincent Aleven,et al.  Fine-Grained Assessment of Motivation over Long Periods of Learning with an Intelligent Tutoring System: Methodology, Advantages, and Preliminary Results , 2013 .

[9]  Zachary A. Pardos,et al.  Affective states and state tests: investigating how affect throughout the school year predicts end of year learning outcomes , 2013, LAK '13.

[10]  Vincent Aleven,et al.  Sensor-free automated detection of affect in a Cognitive Tutor for Algebra , 2012, EDM.

[11]  Stephen Fancsali.  Variable Construction and Causal Discovery for Cognitive Tutor Log Data: Initial Results , 2012, EDM.

[12]  Ryan Shaun Joazeiro de Baker,et al.  Off-task behavior in the cognitive tutor classroom: when students "game the system" , 2004, CHI.

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

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

[15]  A. Elliot,et al.  A 2 X 2 achievement goal framework. , 2001, Journal of personality and social psychology.

[16]  Robert A. Sottilare,et al.  The Generalized Intelligent Framework for Tutoring (GIFT) , 2012 .

[17]  Angela L Duckworth,et al.  Unpacking grit: Motivational correlates of perseverance and passion for long-term goals , 2014, The journal of positive psychology.

[18]  Kenneth R. Koedinger,et al.  A Data Repository for the EDM Community: The PSLC DataShop , 2010 .

[19]  John R. Anderson,et al.  Rules of the Mind , 1993 .

[20]  Candace Walkington,et al.  Using adaptive learning technologies to personalize instruction to student interests: The impact of relevant contexts on performance and learning outcomes. , 2013 .

[21]  Arnon Hershkovitz,et al.  The Impact of Off-task and Gaming Behaviors on Learning: Immediate or Aggregate? , 2009, AIED.

[22]  Stephen Fancsali,et al.  Constructing Variables Th at Support Causal Inference , 2013 .

[23]  Neil T. Heffernan,et al.  Prevention of Off-Task Gaming Behavior in Intelligent Tutoring Systems , 2006, Intelligent Tutoring Systems.

[24]  Neil T. Heffernan,et al.  Detection and Analysis of Off-Task Gaming Behavior in Intelligent Tutoring Systems , 2006, Intelligent Tutoring Systems.

[25]  Angela L. Duckworth,et al.  Development and Validation of the Short Grit Scale (Grit–S) , 2009, Journal of personality assessment.