International Journal of Computers for Mathematical Learning

, Volume 14, Issue 1, pp 21–50

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


DOI: 10.1007/s10758-009-9144-z

Cite this article as:
Sengupta, P. & Wilensky, U. Int J Comput Math Learning (2009) 14: 21. doi:10.1007/s10758-009-9144-z


Electricity is regarded as one of the most challenging topics for students of all ages. Several researchers have suggested that naïve misconceptions about electricity stem from a deep incommensurability (Slotta and Chi 2006; Chi 2005) or incompatibility (Chi et al.1994) between naïve and expert knowledge structures. In this paper we argue that adopting an emergent levels-based perspective as proposed by Wilensky and Resnick (1999), allows us to reconceive commonly noted misconceptions in electricity as behavioral evidences of “slippage between levels,” i.e., these misconceptions appear when otherwise productive knowledge elements are sometimes activated inappropriately due to certain macro-level phenomenological cues only. We then introduce NIELS (NetLogo Investigations In Electromagnetism), a curriculum of emergent multi-agent-based computational models. NIELS models represent phenomena such as electric current and resistance as emergent from simple, body-syntonic interactions between electrons and other charges in a circuit. We discuss results from a pilot implementation of NIELS in an undergraduate physics course, that highlight the ability of an emergent levels-based approach to provide students with a deep, expert-like understanding of the relevant phenomena by bootstrapping, rather than discarding their existing repertoire of intuitive knowledge.


NetLogoNIELSElectricityPhysicsCognitionDesignComplex systemsLearning sciencesMulti-agent based modelsKnowledge representationLearningEducationNetLogo investigations in electromagnetismOhm’s LawResistanceElectric currentElectrostaticsEmergentPhenomenological primitivesP-prims

Copyright information

© Springer Science+Business Media B.V. 2009

Authors and Affiliations

  1. 1.Department of Learning SciencesNorthwestern UniversityEvanstonUSA
  2. 2.Center for Connected Learning and Computer-based Modeling (CCL)Northwestern UniversityEvanstonUSA
  3. 3.Department of Electrical Engineering and Computer ScienceNorthwestern UniversityEvanstonUSA