PLANTABETA

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Tutorial ​

Active Recall is the most effective way to learn new things.

Multiple choice tests, where Plantors choose from a selection of images or a selection of text answers.

https://brilliant.org/

  • Active Recall
  • Matching
  • Multiple Choice
  • Sequencing
  • Error Detection
  • Crosswords

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  • Tree Genus Identification (Species Identification is more nuanced than required)
py
treeList = [
    'Abies', 
    'Alnus', 
    'Pinus', 
    'Populus', 
    'Pseudotsuga', 
    'Quercus', 
    'Salix', 
    'Thuja', 
    'Tsuga'
    ]

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  • https://www.verywellmind.com/bronfenbrenner-ecological-model-7643403

  • Documentation to play the (game == simulation == PlantorExperience)

  • Documentation for the game is also documentation for the job

  • Knowledge Gaps are the low hanging fruit of PLANTABETA education

  • Every minute counts

  • Simulate the job with Test coded in Python. Use Voronoi and other algorithms to check answers

  • The most simple test is multiple choice naming test

    • Gif of the PlantorMOTON
    • Image of Instruments
    • Name all the objects

  • ErrorRecognition

    • What did they forget?
    • What is the error

  • Keep a list of all the BetaElements which have been included in a test. Each BetaElement should appear as many times as possible. Minimum 3 times in each format Image, Text, Video.

  • "Test.LabelDiagram"

  • "Tests.BetaDecomposition"

  • "Tests.FillInBlank"

  • "Tests.IncreasingDifficulty"

  • "Tests.MatchingTest"

  • "Tests.MOTONDecomposition"

  • "Tests.MOTONTest.VideoAnswer"

  • "Tests.MultipleChoiceTest"

  • "Tests.Overview"

  • "Tests.Recall.Recall.RecallBetaDiagram"

  • "Tests.VIA_Decomposition"

  • "Tests.ContactHighlight"

  • "Tests.Senario"

  • "Tests.Sequencing"