Connecting Curriculum to Problem-Solving Through Distributed Intelligent Tutoring Sharon J. Derry Dept. of Educational Psychology Wisconsin Center for Education Research University of Wisconsin-Madison

Contributors  Mary Leonard  Donald Wortham  Alan Hackbarth  Margaret Wilsman  Michael Peterson

In Nintendo's "The Legend of Zelda™," Link must travel through many rooms arranged in a coordinate maze to find the silver arrow. From the entry room, he goes right 3 rooms, up 4 rooms, left 5 rooms, down 2 rooms, left 1 room, up 3 rooms, and right 4 rooms to find the chamber that has the silver arrow. If the entry room has coordinates (0,0) and all directions are as you view the maze, find the coordinates of the room with the arrow.

Making School Curricula Useful and Interesting to Students  Curricular domains –Statistics, Algebra, Earth Systems Science  Cognitive Theoretical Approach –“Authentic” problem contexts for learning –Relevant, knowledge-appropriate problems  Instructional strategies allowing choices in problem framing and selection

Projects  TiPS Intelligent Tutor –Adult basic skills math  Situated Simulations for Statistics –Middle school math, sci, social studies –Pre-service teachers  “The Learning Sciences” through Instructional Design –Pre-service teachers  Studies of Inquiry Science Classrooms –Middle schools

Results/Findings  Moderate to Good Learning Gains  Desired Performance Improvements Over Comparison Classrooms  Resource Intensive  Mixed Reviews  Conclusion: – Teaching and learning curriculum in the context of authentic problem solving requiring self-directed problem framing and learning presents tough instructional design challenges.

The Trojan Horse

Challenges I.Problem Finding II.Domain “Disorganization” III.The Modeling Problem

Design Challenges in ITS Terms  Modeling Domain Knowledge  Modeling Students’ Domain Knowledge  Problem Modeling With Domain Concepts  Real-Time Modeling of Students’ Evolving Solutions  Modeling Students’ Affective States  Scaffolding Student Problem Solving  Selecting Tutorial Digressions  Machine Learning

I. Problem Finding 1.No constraints on students’ problem choice. 2.Full constraints on students’ problem choice. 3.Guided/mentored problem framing.

Full Constraints on Choice  Examples: –Math problems matching goals are assigned.  Advantages: –Problems match student needs, curriculum. –It's expected, accepted, desired. –Arguably appropriate for early learning. –Does not “reorganize“ domain.  Challenges: –Students do not learn to find/frame problems. –Problems do not arise from interests. –Problems often contrived, trivial.

Guided Problem Finding  Examples –Practice-based professional development –Project-based learning  Advantages –Learners find personally relevant problems  Dilemmas –Finding curriculum-appropriate problem without prior knowledge of curriculum? –How model problem framing? –Important problems “disorganize” curriculum.

II. The Domain “Disorganization Problem” PROB 2 PROB 3 COGNITIVE THEORY X-THEORY IDEAS SOCIO COGNI TIVE IP VIEW SOCIO CULTURAL THEORY PROB 1 LEARNING SCIENCES

Challenges I.Problem Finding II.Domain “Disorganization” III.The Modeling Problem

The Modeling Problem: A Story  The authentic context: Building balloon Cars (LBD™)  A curriculum goal: Newton’s Third Law

Summary of Teacher’s Modeling  Makes tutorial digression  Models operation of car with abstract physics concepts –Develops intermediate representation making tradeoffs on what “not” to model  Exhibits in-depth knowledge of physics  Engages in critical reflective practice regarding representational system and success of her lecture

ITS’s  Intelligent Learning Communities  New 21 st Century Goals for Learners: –Participate in interdisciplinary learning communities that use subject knowledge to frame and solve real problems. –Acquire mindsets and skills for lifelong learning, including ability to use human and technology resources to acquire knowledge during problem solving. –Develop concern for real-world needs and willingness to become engaged citizens.

Hands-On Environmentalism Evolving Case Library Project Collaborations ESS Web Resources Collaborative Tools Community Standards seed sets ESS Project Case Templates (epistemological commitments) Continuing Community: Scientists, Teachers, Facilitators, Env. Groups, K-12 Students Enrolled Learners

Distributed Intelligent Tutoring  Problem Framing  Domain Reorganization  Modeling “the Trojan Horse”

Hands-On Environmentalism Evolving Case Library Project Collaborations ESS Web Resources Collaborative Tools Community Standards seed sets ESS Project Case Templates (epistemological commitments) Continuing Community: Scientists, Teachers, Facilitators, Env. Groups, K-12 Students Enrolled Learners

Everything is vague to a degree you do not realize till you have tried to make it precise. Bertrand Russell