The design and development of the dragoon intelligent tutoring system for model construction: lessons learned

ABSTRACT This paper describes Dragoon, a simple intelligent tutoring system which teaches the construction of models of dynamic systems. Modelling is one of seven practices dictated in two new sets of educational standards in the U.S.A., and Dragoon is one of the first systems for teaching model construction for dynamic systems. Dragoon can be classified as a step-based tutoring system that uses example-tracing, an explicit pedagogical policy and an open learner model. Dragoon can also be used for computer-supported collaborative learning, and provides tools for classroom orchestration. This paper describes the features, user interfaces, and architecture of Dragoon; compares and contrasts Dragoon with other intelligent tutoring systems; and presents a brief overview of formative and summative evaluations of Dragoon in both high school and college classes. Of four summative evaluations, three found that students who used Dragoon learned more about the target system than students who did equivalent work without Dragoon.

[1]  Michelene T. H. Chi,et al.  Active-Constructive-Interactive: A Conceptual Framework for Differentiating Learning Activities , 2009, Top. Cogn. Sci..

[2]  Kurt VanLehn,et al.  Using HCI Task Modeling Techniques to Measure How Deeply Students Model , 2013, AIED Workshops.

[3]  Kurt VanLehn,et al.  Using HCI Task Modeling Techniques to Measure How Deeply Students Model , 2013, AIED 2013.

[4]  Kurt VanLehn,et al.  Studying, Teaching and Applying Sustainability Visions Using Systems Modeling , 2014 .

[5]  Barbara A. Crawford,et al.  Supporting prospective teachers' conceptions of modelling in science , 2004 .

[6]  Judy Kay,et al.  Student Models that Invite the Learner In: The SMILI: () Open Learner Modelling Framework , 2007, Int. J. Artif. Intell. Educ..

[7]  Pierre Dillenbourg,et al.  Technology for Classroom Orchestration , 2010 .

[8]  Mahmoud Abdulwahed,et al.  Orchestrating technology enhanced learning: a literature review and a conceptual framework , 2011 .

[9]  Timothy Teo,et al.  The role of model building in problem solving and conceptual change , 2011, Interact. Learn. Environ..

[10]  Sandra Katz,et al.  Out of the Lab and into the Classroom: An Evaluation of Reflective Dialogue in Andes , 2007, AIED.

[11]  Gordon I. McCalla,et al.  "Open Learner Models: Future Research Directions" Special Issue of the IJAIED (Part 2) , 2007, Int. J. Artif. Intell. Educ..

[12]  Sandra Katz,et al.  Going Beyond the Problem Given: How Human Tutors Use Post-Solution Discussions to Support Transfer , 2003, Int. J. Artif. Intell. Educ..

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

[14]  Issa M. Saleh,et al.  NEW SCIENCE OF LEARNING: COGNITION, COMPUTERS AND COLLABORATION IN EDUCATION , 2010 .

[15]  Joel A. Shapiro.  An Algebra Subsystem for Diagnosing Students' Input in a Physics Tutoring System , 2005, Int. J. Artif. Intell. Educ..

[16]  Vincent Aleven,et al.  Educational Software Features that Encourage and Discourage "Gaming the System" , 2009, AIED.

[17]  Allen Newell,et al.  Human Problem Solving. , 1973 .

[18]  Y. Z. Ider,et al.  Quantitative estimation of insulin sensitivity. , 1979, The American journal of physiology.

[19]  Garrison W. Cottrell,et al.  A stochastic optimal control perspective on affect- sensitive teaching , 2012 .

[20]  Judy Kay,et al.  Visualisations for longitudinal participation, contribution and progress of a collaborative task at the tabletop , 2011, CSCL.

[21]  K. Koedinger,et al.  Improving students’ help-seeking skills using metacognitive feedback in an intelligent tutoring system , 2011, Learning and Instruction.

[22]  Kasia Muldner,et al.  An analysis of students’ gaming behaviors in an intelligent tutoring system: predictors and impacts , 2011, User Modeling and User-Adapted Interaction.

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

[24]  Peter Brusilovsky,et al.  The role of community feedback in the student example authoring process: An evaluation of AnnotEx , 2011 .

[25]  Kurt VanLehn,et al.  Learning How to Construct Models of Dynamic Systems: An Initial Evaluation of the Dragoon Intelligent Tutoring System , 2017, IEEE Transactions on Learning Technologies.

[26]  Joel A. Shapiro.  Algebra Subsystem for an Intelligent Tutoring System , 2002 .

[27]  Richard N Bergman,et al.  The minimal model of glucose regulation: a biography. , 2003, Advances in experimental medicine and biology.

[28]  Kurt VanLehn,et al.  Accelerated Future Learning via Explicit Instruction of a Problem Solving Strategy , 2007, AIED.

[29]  Min Chi,et al.  The Impact of Explicit Strategy Instruction on Problem-solving Behaviors across Intelligent Tutoring Systems , 2007 .

[30]  Carl Erickson,et al.  Presenter First: organizing complex GUI applications for test-driven development , 2006, AGILE 2006 (AGILE'06).

[31]  Harold Pashler,et al.  Optimizing Instructional Policies , 2013, NIPS.

[32]  Helen R. Quinn,et al.  A Framework for K-12 Science Education: Practices, Crosscutting Concepts, and Core Ideas , 2013 .

[33]  Pierre Dillenbourg,et al.  The Evolution of Research on Computer-Supported Collaborative Learning , 2009 .

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

[35]  Erik Duval,et al.  Learning dashboards: an overview and future research opportunities , 2013, Personal and Ubiquitous Computing.

[36]  DIMITRIOS PIERRAKOS,et al.  User Modeling and User-Adapted Interaction , 1994, User Modeling and User-Adapted Interaction.

[37]  Thomas L. Griffiths,et al.  Faster Teaching by POMDP Planning , 2011, AIED.

[38]  Kurt VanLehn,et al.  Model construction as a learning activity: a design space and review , 2013, Interact. Learn. Environ..

[39]  Yang Zhang,et al.  An architecture and implement model for Model-View-Presenter pattern , 2010, 2010 3rd International Conference on Computer Science and Information Technology.

[40]  Kurt VanLehn,et al.  The Affective Meta-Tutoring Project: How to motivate students to use effective meta-cognitive strategies , 2011, ICCE 2011.

[41]  Kurt VanLehn,et al.  From behavioral description to a pattern-based model for intelligent tutoring systems , 2011, PLoP '11.

[42]  Ton de Jong,et al.  Using Co-Lab to build System Dynamics models: Students' actions and on-line tutorial advice , 2009, Comput. Educ..

[43]  Kurt VanLehn,et al.  Defining the Behavior of an Affective Learning Companion in the Affective Meta-tutor Project , 2013, AIED.

[44]  Kurt VanLehn,et al.  Meta-Cognitive Strategy Instruction in Intelligent Tutoring Systems: How, When, and Why , 2010, J. Educ. Technol. Soc..

[45]  David A. Gillam,et al.  A Framework for K-12 Science Education: Practices, Crosscutting Concepts, and Core Ideas , 2012 .

[46]  Kurt VanLehn,et al.  Empirically evaluating the application of reinforcement learning to the induction of effective and adaptive pedagogical strategies , 2011, User Modeling and User-Adapted Interaction.

[47]  Judy Kay,et al.  Learner Control , 2001, User Modeling and User-Adapted Interaction.

[48]  Murat Akkuş.  The Common Core State Standards for Mathematics , 2015 .

[49]  E. Aronson.  The Jigsaw Classroom , 1978 .

[50]  Judy Kay,et al.  Open Learner Models as Drivers for Metacognitive Processes , 2013 .

[51]  Kurt VanLehn,et al.  Evaluation of a meta-tutor for constructing models of dynamic systems , 2013, AIED Workshops.

[52]  Helen M. Doerr,et al.  Stella ten years later: A review of the literature , 1996, Int. J. Comput. Math. Learn..

[53]  David Allbritton,et al.  Squeezing Out Gaming Behavior in a Dialog-Based ITS , 2010, Intelligent Tutoring Systems.

[54]  Pierre-Yves Oudeyer,et al.  Multi-Armed Bandits for Intelligent Tutoring Systems , 2013, EDM.