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D-Index & Metrics

Social Sciences and Humanities

D-Index
53
Citations
15317
World Ranking
2258
National Ranking
1092

Overview

Uri Wilensky is affiliated with Northwestern University in the United States. Their research primarily spans the field of Computer Science, with particular focus on Developmental and Educational Psychology, Computer Science Applications, Artificial Intelligence, Management Science and Operations Research, and Education. Their work addresses various domains within these areas, contributing to interdisciplinary insights.

The scientist's main topics of research include Teaching and Learning Programming, Innovative Teaching and Learning Methods, Educational Games and Gamification, Multi-Agent Systems and Negotiation, Genetics, Bioinformatics, and Biomedical Research, Complex Systems and Decision Making, and Experimental Learning in Engineering.

Uri Wilensky has published extensively in several venues. Frequent publication venues include:

  • Proceedings.
  • arXiv (Cornell University)
  • Journal of Science Education and Technology
  • Journal of Artificial Societies and Social Simulation
  • International Conference of Learning Sciences

Recent papers authored or co-authored by Uri Wilensky include:

  • Modeling and Measuring High School Students' Computational Thinking Practices in Science, 2020, Journal of Science Education and Technology
  • Constructionist co-design: A dual approach to curriculum and professional development, 2021, British Journal of Educational Technology
  • Leveraging Modularity During Replication of High-Fidelity Models: Lessons from Replicating an Agent-Based Model for HIV Prevention, 2020, Journal of Artificial Societies and Social Simulation
  • High-Fidelity Agent-Based Modeling to Support Prevention Decision-Making: an Open Science Approach, 2021, Prevention Science
  • LevelSpace: A NetLogo Extension for Multi-Level Agent-Based Modeling, 2020, Journal of Artificial Societies and Social Simulation

Collaborations frequently involve co-authors Michael Horn, John Chen, Jacob Kelter, Sugat Dabholkar, and Amanda Peel, reflecting sustained academic partnerships across multiple publications.

Best Publications

  • Defining Computational Thinking for Mathematics and Science Classrooms

    David Weintrop;Elham Beheshti;Michael S. Horn;Kai Orton

  • An Introduction to Agent-Based Modeling: Modeling Natural, Social, and Engineered Complex Systems with NetLogo

    Uri Wilensky;William Rand

  • NetLogo: A simple environment for modeling complexity

    S. Tisue;U. Wilensky

  • Thinking in Levels: A Dynamic Systems Approach to Making Sense of the World

    Uri Wilensky;Mitchel Resnick

  • Complex Systems in Education: Scientific and Educational Importance and Implications for the Learning Sciences.

    Michael J. Jacobson;Michael J. Jacobson;Uri Wilensky

  • Thinking like a wolf, a sheep, or a firefly: Learning biology through constructing and testing computational theories - An embodied modeling approach

    Uri Wilensky;Kenneth Reisman

  • To block or not to block, that is the question: students' perceptions of blocks-based programming

    David Weintrop;Uri Wilensky

  • Connected Chemistry—Incorporating Interactive Simulations into the Chemistry Classroom

    Mike Stieff;Uri Wilensky

  • Abstract Meditations on the Concrete and Concrete Implications for Mathematics Education

    Uri Wilensky

  • Diving into Complexity: Developing Probabilistic Decentralized Thinking through Role-Playing Activities.

    Mitchel Resnick;Uri Wilensky

  • Comparing Block-Based and Text-Based Programming in High School Computer Science Classrooms

    David Weintrop;Uri Wilensky

  • Learning through participatory simulations: network-based design for systems learning in classrooms

    Uri Wilensky;Walter Stroup

  • What is Normal Anyway? Therapy for Epistemological Anxiety

    Uri Wilensky

  • Promoting Transfer by Grounding Complex Systems Principles.

    Robert L. Goldstone;Uri Wilensky

  • Making Models Match: Replicating an Agent-Based Model

    Uri Wilensky;William Rand

  • Comparing Virtual and Physical Robotics Environments for Supporting Complex Systems and Computational Thinking

    Matthew Berland;Uri Wilensky

  • Model-Based Teaching and Learning With BioLogica TM : What Do They Learn? How Do They Learn? How Do We Know?

    Barbara C. Buckley;Janice D. Gobert;Ann C. H. Kindfield;Paul Horwitz

  • Using Commutative Assessments to Compare Conceptual Understanding in Blocks-based and Text-based Programs

    David Weintrop;Uri Wilensky

  • Learning Electricity with NIELS: Thinking with Electrons and Thinking in Levels

    Pratim Sengupta;Uri Wilensky

  • Inventing a "Mid Level" to Make Ends Meet: Reasoning between the Levels of Complexity

    Sharona T. Levy;Uri Wilensky

  • Thinking Like a Wolf, a Sheep, or a Firefly: Learning Biology Through Constructing and Testing Computational Theories

    Uri Wilensky;Kenneth Reisman

  • Know your enemy: learning from in-game opponents

    David Weintrop;Uri Wilensky

Frequent Co-Authors

Chris Dede
Chris Dede Harvard University
Yasmin B. Kafai
Yasmin B. Kafai University of Pennsylvania
C. Hendricks Brown
C. Hendricks Brown Northwestern University
Richard Noss
Richard Noss University College London
Robert L. Goldstone
Robert L. Goldstone Indiana University
David H. Uttal
David H. Uttal Northwestern University
Brian Mustanski
Brian Mustanski Northwestern University
Justin D. Smith
Justin D. Smith University of Utah
Roger Azevedo
Roger Azevedo University of Central Florida
Daniel C. Dennett
Daniel C. Dennett Tufts University

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