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Explore how RiverWeb supports students in scientific reasoning, utilizing multiple representations and scaffolding to enhance learning. Results show difficulties faced, with strategies and future directions for improvement.
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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 • Maryland Virtual High School (MVHS) • Susan Ragan, Stacey Pitrech, Marylin Leong • National Center for Supercomputing Applications (NCSA) • David Curtis • National Science Foundation (NSF) • University of Maryland • Myriam Tron
Overview • Introduction • Context - MVHS - NCSA - UMCP • RiverWeb • Framework and Curriculum Design Principles • Research Questions • Present Study • Method • Results • Summary • Future Directions
Framework & Curriculum Design Principles • Context • Meaningful problem space that provides intellectual challenges and sustains engagement • Driving Q’s, sub-questions, anchoring event • Standards based • Larger community of experts that defines the language and methods of the larger community • AAAS benchmarks, State & county science objectives • Inquiry • 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 • Collaboration • Interaction among students, teachers, and community members to share information and negotiate meaning • e.g., small-group meetings • Learning tools • Tools that support students in intellectually challenging tasks • Data collection, communication, modeling • Artifacts • Representations of ideas and concepts that can be shared, critiqued, and revised to enhance learning • e.g., concept maps, scientific models • Scaffolds • Methods provided by teachers, peers, and on-line resources
Research Questions • How do students use multiple representations (e.g., graphs, scatterplots) during scientific reasoning? • How do students use math, biology, and chemistry concepts to reason about watershed problems? • 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) • How does RiverWeb support collaborative scientific reasoning and argumentation? • How and when do students utilize scaffolding provided by the teacher, peers and/or digital resources?
Method • Students • 16 9th grade students, 2 Honors biology classes • Introduction to the interdependence of living organisms • Procedure • 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) • In-depth examination of students’ emerging understanding of science phenomena • Data sources • 10 hrs of video and audio (8 student-pairs x 2 x 75 min) • notebook entries, prediction statements, pretest and posttests • Data Analyses • 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 • Overall, students exhibited the following difficulties: • inability to establish whether the differences observed are due to cause-and-effect or are based on a relationship between variables • lack of understanding of definitions and concepts (e.g., runoff) • difficulty reading and comparing multiple representations • incomplete co-construction of knowledge • 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. • Teachers provide individualized levels of scaffolding. • Students create incorrect analogies and/or use incorrect visual representations of complex concepts. • Engaged students are metacognitively aware of their performance and will address deficiencies by deploying various strategies.
Summary • “Flexible” application of educational research • Theoretically-based and empirically-driven approach • Evolution and scaling-up of “computers as cognitive tools” theme • Self-regulation learning model • Role of modeling and visualization tools for science • Teachers’ professional development
Future Directions • 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 • Build additional RiverWeb features • Content assistants • Hypothesis-testing area • Explore the use of AI techniques • model SRL and explanation-based coach