Teaching Electricity and Magnetism with PhET Simulations

Coursera Courses ↗ · Coursera

Open Course on Coursera

Free to audit · Opens on Coursera

Teaching Electricity and Magnetism with PhET Simulations

Coursera · Beginner ·📄 Research Papers Explained ·1mo ago
PhET Interactive Simulations (https://phet.colorado.edu/), a project of the University of Colorado Boulder, provides fun, free, interactive, research-based science and mathematics simulations for use across, primary, secondary, and higher education levels. We extensively test and evaluate each simulation to ensure educational effectiveness. All simulations are open source and free to all students and teachers. In this course, you will acquire teaching and facilitation strategies for how to use PhET simulations for teaching introductory, conceptual electricity and magnetism topics. Specifically, you will interact with 16 PhET simulations, engage as a learner with model lessons, and reflect as a teacher on PhET’s instructional strategies in the context of introductory electricity and magnetism. To finish this course, you need to complete one assignment with peer review: design your own sim-based plans (such as a unit plan) for teaching electricity and/or magnetism, making use of five or more PhET simulations and instructional strategies.
Watch on Coursera ↗ (saves to browser)
Sign in to unlock AI tutor explanation · ⚡30

Related AI Lessons

The ABCs of reading medical research and review papers these days
Learn to critically evaluate medical research papers by accepting nothing at face value, believing no one blindly, and checking everything
Medium · LLM
#1 DevLog Meta-research: I Got Tired of Tab Chaos While Reading Research Papers.
Learn to manage research paper tabs efficiently and apply meta-research techniques to improve productivity
Dev.to AI
How to Set Up a Karpathy-Style Wiki for Your Research Field
Learn to set up a Karpathy-style wiki for your research field to organize and share knowledge effectively
Medium · AI
The Non-Optimality of Scientific Knowledge: Path Dependence, Lock-In, and The Local Minimum Trap
Scientific knowledge may be stuck in a local minimum, hindering optimal progress, and understanding this concept is crucial for advancing research
ArXiv cs.AI
Up next
Microsoft Research Forum | Season 2, Episode 4
Microsoft Research
Watch →