Fostering Learners’ Collaborative
Problem Solving with RiverWeb
Roger Azevedo
University of Maryland
Mary Ellen Verona
Maryland Virtual High School
Jennifer G. Cromley
University of Maryland
Acknowledgements
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Maryland Virtual High School (MVHS)
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National Center for Supercomputing Applications
(NCSA)
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Susan Ragan, Stacey Pitrech, Marylin Leong
David Curtis
National Science Foundation (NSF)
University of Maryland
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Myriam Tron
Overview
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Introduction
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Present Study
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Context - MVHS - NCSA - UMCP
RiverWeb
Framework and Curriculum Design Principles
Research Questions
Method
Results
Summary
Future Directions
RiverWeb - Water Quality Web-based Simulation
RiverWeb
RiverWeb Notebook
RiverWeb - Scatterplots & Help
Framework & Curriculum Design Principles
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Context
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Standards based
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Meaningful problem space that provides intellectual
challenges and sustains engagement
 Driving Q’s, sub-questions, anchoring event
Larger community of experts that defines the language
and methods of the larger community
 AAAS benchmarks, State & county science objectives
Inquiry
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The accepted method of the scientific community for
solving problems
 Asking Qs, data collection, organization, and data
analysis, sharing and communicating data
Framework & Curriculum Design Principles
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Collaboration
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Learning tools
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Tools that support students in intellectually challenging tasks
 Data collection, communication, modeling
Artifacts
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Interaction among students, teachers, and community
members to share information and negotiate meaning
 e.g., small-group meetings
Representations of ideas and concepts that can be shared,
critiqued, and revised to enhance learning
 e.g., concept maps, scientific models
Scaffolds
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Methods provided by teachers, peers, and on-line resources
Research Questions
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How do students use multiple representations (e.g., graphs,
scatterplots) during scientific reasoning?
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How do students use math, biology, and chemistry concepts to
reason about watershed problems?
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What is the nature of students’ misconceptions about dynamic
systems?
What is the nature of students’ discourse during scientific
reasoning? (e.g., observations, explanations, use of supporting
evidence)
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How does RiverWeb support collaborative scientific reasoning
and argumentation?
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How and when do students utilize scaffolding provided by the
teacher, peers and/or digital resources?
Method
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Students
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16 9th grade students, 2 Honors biology classes
Introduction to the interdependence of living organisms
Procedure
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Students audio- and videotaped on 2 separate
occasions over a 1 week period
1 environmental science teacher - complete participant
Regular classroom teacher and visiting teacher
2 researchers acted as complete observers
10 hrs of video and audio (2 student-pairs x 2 x 75 min)
Method (2)
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In-depth examination of students’ emerging
understanding of science phenomena
Data sources
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10 hrs of video and audio (8 student-pairs x 2 x 75 min)
notebook entries, prediction statements, pretest and
posttests
Data Analyses
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Quantitative (pre- and posttests, quality of notebook
answers)
Nature of collaborative problem solving (e.g.,
reasoning chains)
Nature of teachers’ scaffolding during science activities
Results
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Overall, students exhibited the following difficulties:
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inability to establish whether the differences observed are due to
cause-and-effect or are based on a relationship between variables
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lack of understanding of definitions and concepts (e.g., runoff)
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difficulty reading and comparing multiple representations
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incomplete co-construction of knowledge
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Students engage in long reasoning chains as they jointly solve
problems presented in the work sheets and notebook by accessing
multiple representations and other WQS features.
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Teachers provide individualized levels of scaffolding.
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Students create incorrect analogies and/or use incorrect visual
representations of complex concepts.
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Engaged students are metacognitively aware of their performance
and will address deficiencies by deploying various strategies.
Summary
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“Flexible” application of educational research
Theoretically-based and empirically-driven
approach
Evolution and scaling-up of “computers as cognitive
tools” theme
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Self-regulation learning model
Role of modeling and visualization tools for science
Teachers’ professional development
Future Directions
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Investigate the role of self-regulated learning (SRL)
during students’ complex science learning with RiverWeb
examine effects of teacher-set goals vs. learner-generated
sub-goals on students’ emerging understanding of scientific
phenomena
Understand the nature and role of classroom discourse
during science inquiry activities
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Build additional RiverWeb features
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Content assistants
Hypothesis-testing area
Explore the use of AI techniques
 model SRL and explanation-based coach