Module: Superbugs + Computational Thinking


Unit Plan: Superbugs + Computational Thinking


Major Themes for the Unit

  • Scientific themes: Natural Selection
  • Scientific practice: Modeling and Computational Thinking
  • SSI: Antibiotic Resistance


Driving Question: How can antibiotic resistance be mitigated?


Concepts needed to explore the driving question

  • Science concepts (Examples: carbon cycling, photosynthesis)
    • Natural selection- random mutation, initial variation, selective pressure, favorable trait, differential survival, reproduction, population shift
    • Antibiotic function
    • Antibiotic resistance mechanisms
  • What social ideas and concerns influence negotiation of the issue?
    • Overprescription of antibiotics
    • Usage of antibiotics in food production
    • Policy and economics related to antibiotic usage


Unit-level performance expectations

  • Develop a conceptual understanding of natural selection that accounts for a) genetic variation associated with particular traits, b) selective pressure that leads to differential reproductive success linked to these traits, and c) changes in trait frequencies within the population.
  • Develop algorithmic explanations of natural selection in microbe, animal, and plant contexts.
  • Use contextual algorithms to create a generalized natural selection algorithmic explanation for use in new natural selection contexts.
  • Use algorithms as a basis for reasoning about novel problem situations.
  • Demonstrate socio-scientific reasoning in response to complex SSI.
    • Identify and discuss sources of issue complexity.
    • Identify areas of uncertainty and ask related questions.
    • Analyze the issue from multiple perspectives.
    • Identify and discuss ways in which scientific evidence can inform issue resolution as well as limits on the use of scientific evidence.

Instructional Sequences

Unit assessment(s)

  • Algorithmic explanations of natural selection in the context of the laboratory investigation, the mountain sheep investigation, and the field mustard investigation– Formative
  • Application of NS algorithms to propose a policy for mitigating antibiotic resistance – Formative & Summative
  • Application of Socio-scientific Reasoning in the context of a policy recommendation - Formative & Summative
  • Natural Selection Test; multiple-choice (CINS) plus open-ended item (Opfer, Nehm & Ha, 2012) – Summative



The materials associated with the Superbugs Unit are based, in part, upon work supported by the National Science Foundation Transforming Undergraduate Education in Science (TUES) program under Grant 114062 and The Missouri Transect, a National Science Foundation EPSCoR Program, Cooperative Agreement IIA-1355406. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. The materials presented in Lesson 7. Mountain Sheep Model were created by the PRACCIS team is copyrighted, 2014, by the PRACCIS project team (Clark Chinn and Ravit Golan Duncan, Project Directors). All rights are reserved.