data/explorations/modeling_graphs/Graph Modeling.yaml - develop - githubmirror/oppia

data/explorations/modeling_graphs/Graph Modeling.yaml
633 строки19 KB
Hitesh Tomar
Fix part of #13820: Adds backend validation for RTE content and translations of exploration state (#16065)
13 окт 2022, 22:53
13 окт 2022, 22:53910eb9f
author_notes: ''
auto_tts_enabled: true
blurb: ''
category: Graph Theory
correctness_feedback_enabled: false
edits_allowed: true
init_state_name: Introduction
language_code: en
objective: Learn how to model objects as graphs
param_changes: []
param_specs: {}
schema_version: 47
states:
  Bosses correct:
    classifier_model_id: null
    content:
      content_id: content
      html: "<p>As you can see, graphs are very useful for modeling real world behavior.\
        \ They are widely used in many fields, such as computer science and statistics.\_\
        </p><p>\_</p><p>Maybe from now on you'll start seeing graphs all over the\
        \ place!\_</p>"
    interaction:
      answer_groups: []
      confirmed_unclassified_answers: []
      customization_args:
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          value:
            content_id: ca_buttonText_0
            unicode_str: Continue
      default_outcome:
        dest: END
        feedback:
          content_id: default_outcome
          html: ''
        labelled_as_correct: false
        missing_prerequisite_skill_id: null
        param_changes: []
        refresher_exploration_id: null
      hints: []
      id: Continue
      solution: null
    next_content_id_index: 1
    param_changes: []
    recorded_voiceovers:
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        content: {}
        default_outcome: {}
    solicit_answer_details: false
    written_translations:
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        ca_buttonText_0: {}
        content: {}
        default_outcome: {}
  Bosses question:
    classifier_model_id: null
    content:
      content_id: content
      html: '<p>There are 6 employees in a company: Fred, George, Hannah, Irene, John
        and Kevin.</p><ul><li>Fred and Hannah report to John.</li><li>Kevin reports
        to George.</li><li>John and George report to Irene.</li></ul><p>Try modeling
        this as a graph, with a directed edge from an employee to his or her immediate
        superior.</p>'
    interaction:
      answer_groups:
      - outcome:
          dest: Bosses correct
          feedback:
            content_id: feedback_1
            html: <p>Well done!</p>
          labelled_as_correct: false
          missing_prerequisite_skill_id: null
          param_changes: []
          refresher_exploration_id: null
        rule_specs:
        - inputs:
            g:
              edges:
              - dst: 0
                src: 1
                weight: 1
              - dst: 0
                src: 2
                weight: 1
              - dst: 2
                src: 5
                weight: 1
              - dst: 1
                src: 4
                weight: 1
              - dst: 1
                src: 3
                weight: 1
              isDirected: true
              isLabeled: true
              isWeighted: false
              vertices:
              - label: Irene
                x: 156.59375
                y: 43.0
              - label: John
                x: 126.59375
                y: 99.0
              - label: George
                x: 220.59375
                y: 92.0
              - label: Fred
                x: 103.59375
                y: 163.0
              - label: Hannah
                x: 163.59375
                y: 163.0
              - label: Kevin
                x: 218.59375
                y: 162.0
          rule_type: IsIsomorphicTo
        tagged_skill_misconception_id: null
        training_data: []
      confirmed_unclassified_answers: []
      customization_args:
        canAddEdge:
          value: true
        canAddVertex:
          value: false
        canDeleteEdge:
          value: true
        canDeleteVertex:
          value: false
        canEditEdgeWeight:
          value: false
        canEditVertexLabel:
          value: false
        canMoveVertex:
          value: true
        graph:
          value:
            edges: []
            isDirected: true
            isLabeled: true
            isWeighted: false
            vertices:
            - label: Fred
              x: 150.0
              y: 50.0
            - label: George
              x: 200.0
              y: 50.0
            - label: Irene
              x: 150.0
              y: 100.0
            - label: Hannah
              x: 269.09375
              y: 49.0
            - label: John
              x: 201.09375
              y: 101.0
            - label: Kevin
              x: 265.09375
              y: 100.0
      default_outcome:
        dest: Bosses question
        feedback:
          content_id: default_outcome
          html: <p>Not exactly... try again!</p>
        labelled_as_correct: false
        missing_prerequisite_skill_id: null
        param_changes: []
        refresher_exploration_id: null
      hints: []
      id: GraphInput
      solution: null
    next_content_id_index: 2
    param_changes: []
    recorded_voiceovers:
      voiceovers_mapping:
        content: {}
        default_outcome: {}
        feedback_1: {}
    solicit_answer_details: false
    written_translations:
      translations_mapping:
        content: {}
        default_outcome: {}
        feedback_1: {}
  Cities correct:
    classifier_model_id: null
    content:
      content_id: content
      html: "<p>Distances on a map are a very common thing to use graphs to model,\
        \ as computers can then process these graphs to do stuff like path-finding\
        \ without worrying about extra details that a full map would have. Note that\
        \ it doesn't matter how far apart the vertices are when you draw them, the\
        \ important thing is the weight of the edge.</p><p>\_</p><p>Another piece\
        \ of extra information we might want to add to a graph are relations that\
        \ only go in one direction. In that case, instead of having lines between\
        \ dots, we have arrows instead. In mathematician-speak, this would be a \"\
        directed graph\", since every edge has a direction.</p><p>\_</p><p>Let's give\
        \ this a try now!</p>"
    interaction:
      answer_groups: []
      confirmed_unclassified_answers: []
      customization_args:
        buttonText:
          value:
            content_id: ca_buttonText_0
            unicode_str: Continue
      default_outcome:
        dest: Bosses question
        feedback:
          content_id: default_outcome
          html: ''
        labelled_as_correct: false
        missing_prerequisite_skill_id: null
        param_changes: []
        refresher_exploration_id: null
      hints: []
      id: Continue
      solution: null
    next_content_id_index: 1
    param_changes: []
    recorded_voiceovers:
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        content: {}
        default_outcome: {}
    solicit_answer_details: false
    written_translations:
      translations_mapping:
        ca_buttonText_0: {}
        content: {}
        default_outcome: {}
  Cities question:
    classifier_model_id: null
    content:
      content_id: content
      html: '<p>Use the following information about distances between cities to model
        them on a graph:</p><ul><li>Paris is 344km from London.</li><li>London is
        932km from Berlin.</li><li>Berlin is 878km from Paris.</li><li>Paris is 1054km
        from Madrid.</li><li>London is 1265km from Madrid.</li><li>Madrid is 1871km
        from Berlin.</li></ul><p>(Note: On the graph, don''t put "km" on the edges,
        just put the number)</p>'
    interaction:
      answer_groups:
      - outcome:
          dest: Cities correct
          feedback:
            content_id: feedback_1
            html: <p>Excellent!</p>
          labelled_as_correct: false
          missing_prerequisite_skill_id: null
          param_changes: []
          refresher_exploration_id: null
        rule_specs:
        - inputs:
            g:
              edges:
              - dst: 1
                src: 0
                weight: 344
              - dst: 0
                src: 2
                weight: 932
              - dst: 1
                src: 2
                weight: 878
              - dst: 3
                src: 1
                weight: 1054
              - dst: 0
                src: 3
                weight: 1265
              - dst: 2
                src: 3
                weight: 1871
              isDirected: false
              isLabeled: true
              isWeighted: true
              vertices:
              - label: London
                x: 158.59375
                y: 45.0
              - label: Paris
                x: 227.59375
                y: 197.0
              - label: Berlin
                x: 218.59375
                y: 64.0
              - label: Madrid
                x: 99.59375
                y: 177.0
          rule_type: IsIsomorphicTo
        tagged_skill_misconception_id: null
        training_data: []
      confirmed_unclassified_answers: []
      customization_args:
        canAddEdge:
          value: true
        canAddVertex:
          value: false
        canDeleteEdge:
          value: true
        canDeleteVertex:
          value: false
        canEditEdgeWeight:
          value: true
        canEditVertexLabel:
          value: false
        canMoveVertex:
          value: true
        graph:
          value:
            edges: []
            isDirected: false
            isLabeled: true
            isWeighted: true
            vertices:
            - label: London
              x: 305.09375
              y: 32.0
            - label: Paris
              x: 324.09375
              y: 98.0
            - label: Madrid
              x: 211.09375
              y: 190.0
            - label: Berlin
              x: 491.09375
              y: 119.0
      default_outcome:
        dest: Cities question
        feedback:
          content_id: default_outcome
          html: <p>Not quite, try again!</p>
        labelled_as_correct: false
        missing_prerequisite_skill_id: null
        param_changes: []
        refresher_exploration_id: null
      hints: []
      id: GraphInput
      solution: null
    next_content_id_index: 2
    param_changes: []
    recorded_voiceovers:
      voiceovers_mapping:
        content: {}
        default_outcome: {}
        feedback_1: {}
    solicit_answer_details: false
    written_translations:
      translations_mapping:
        content: {}
        default_outcome: {}
        feedback_1: {}
  END:
    classifier_model_id: null
    content:
      content_id: content
      html: <p>Congratulations, you have finished!</p>
    interaction:
      answer_groups: []
      confirmed_unclassified_answers: []
      customization_args:
        recommendedExplorationIds:
          value: []
      default_outcome: null
      hints: []
      id: EndExploration
      solution: null
    next_content_id_index: 0
    param_changes: []
    recorded_voiceovers:
      voiceovers_mapping:
        content: {}
    solicit_answer_details: false
    written_translations:
      translations_mapping:
        content: {}
  Friends correct:
    classifier_model_id: null
    content:
      content_id: content
      html: "<p>Friendships and social relations are just one example of things that\
        \ can be modeled by graphs.</p><p>\_</p><p>Sometimes, though, we want a bit\
        \ more information in our graphs. For example, let's say that we want to use\
        \ a graph to model distances between cities. In this case, we can attach numbers\
        \ to each edge to represent this data. In mathematician-speak, such a graph\
        \ is a \"weighted graph\", since each edge has a \"weight\" number.</p><p>\_\
        </p><p>Let's give this a try!</p>"
    interaction:
      answer_groups: []
      confirmed_unclassified_answers: []
      customization_args:
        buttonText:
          value:
            content_id: ca_buttonText_0
            unicode_str: Continue
      default_outcome:
        dest: Cities question
        feedback:
          content_id: default_outcome
          html: ''
        labelled_as_correct: false
        missing_prerequisite_skill_id: null
        param_changes: []
        refresher_exploration_id: null
      hints: []
      id: Continue
      solution: null
    next_content_id_index: 1
    param_changes: []
    recorded_voiceovers:
      voiceovers_mapping:
        ca_buttonText_0: {}
        content: {}
        default_outcome: {}
    solicit_answer_details: false
    written_translations:
      translations_mapping:
        ca_buttonText_0: {}
        content: {}
        default_outcome: {}
  Friends question:
    classifier_model_id: null
    content:
      content_id: content
      html: '<p>There are a group of 5 people in a room: Alice, Bob, Charlie, David
        and Emily. We have that:</p><ul><li>Alice is friends with everyone but David<br></li><li>Bob
        is friends with Alice only<br></li><li>Charlie is friends with Alice and David<br></li><li>David
        is friends with Charlie and Emily<br></li><li>Emily is friends with Alice
        and David<br></li></ul><p>Try to model the friendships as a graph!</p>'
    interaction:
      answer_groups:
      - outcome:
          dest: Friends correct
          feedback:
            content_id: feedback_1
            html: <p>Correct!</p>
          labelled_as_correct: false
          missing_prerequisite_skill_id: null
          param_changes: []
          refresher_exploration_id: null
        rule_specs:
        - inputs:
            g:
              edges:
              - dst: 1
                src: 0
                weight: 1
              - dst: 0
                src: 2
                weight: 1
              - dst: 4
                src: 0
                weight: 1
              - dst: 3
                src: 4
                weight: 1
              - dst: 2
                src: 3
                weight: 1
              isDirected: false
              isLabeled: true
              isWeighted: false
              vertices:
              - label: Alice
                x: 68.09375
                y: 91
              - label: Bob
                x: 128.09375
                y: 124
              - label: Charlie
                x: 114.09375
                y: 189
              - label: David
                x: 45.09375
                y: 206
              - label: Emily
                x: 17.09375
                y: 161
          rule_type: IsIsomorphicTo
        tagged_skill_misconception_id: null
        training_data: []
      - outcome:
          dest: Friends question
          feedback:
            content_id: feedback_2
            html: <p>Did you forget to add new edges?</p>
          labelled_as_correct: false
          missing_prerequisite_skill_id: null
          param_changes: []
          refresher_exploration_id: null
        rule_specs:
        - inputs:
            g:
              edges: []
              isDirected: false
              isLabeled: true
              isWeighted: false
              vertices:
              - label: Alice
                x: 115.09375
                y: 85
              - label: Bob
                x: 184.09375
                y: 110
              - label: Charlie
                x: 164.09375
                y: 156
              - label: David
                x: 109.09375
                y: 185
              - label: Emily
                x: 80.09375
                y: 138
          rule_type: IsIsomorphicTo
        tagged_skill_misconception_id: null
        training_data: []
      confirmed_unclassified_answers: []
      customization_args:
        canAddEdge:
          value: true
        canAddVertex:
          value: false
        canDeleteEdge:
          value: true
        canDeleteVertex:
          value: false
        canEditEdgeWeight:
          value: false
        canEditVertexLabel:
          value: false
        canMoveVertex:
          value: true
        graph:
          value:
            edges: []
            isDirected: false
            isLabeled: true
            isWeighted: false
            vertices:
            - label: Bob
              x: 380.59375
              y: 97.0
            - label: Emily
              x: 259.59375
              y: 98.0
            - label: David
              x: 291.59375
              y: 157.0
            - label: Charlie
              x: 353.59375
              y: 159.0
            - label: Alice
              x: 320.59375
              y: 57.0
      default_outcome:
        dest: Friends question
        feedback:
          content_id: default_outcome
          html: <p>Not quite... Let's try again!</p>
        labelled_as_correct: false
        missing_prerequisite_skill_id: null
        param_changes: []
        refresher_exploration_id: null
      hints: []
      id: GraphInput
      solution: null
    next_content_id_index: 3
    param_changes: []
    recorded_voiceovers:
      voiceovers_mapping:
        content: {}
        default_outcome: {}
        feedback_1: {}
        feedback_2: {}
    solicit_answer_details: false
    written_translations:
      translations_mapping:
        content: {}
        default_outcome: {}
        feedback_1: {}
        feedback_2: {}
  Introduction:
    classifier_model_id: null
    content:
      content_id: content
      html: "<p>When mathematicians talk about graph theory, they usually aren't referring\
        \ to curve sketching!</p><p>\_</p><p>A graph is a mathematical object that\
        \ consists of \"vertices\" and \"edges\". Does this sound complicated? Actually,\
        \ it isn't: in simple terms, graphs are just dots joined by lines! The dots\
        \ are called \"vertices\" and the lines are called \"edges\". An example of\
        \ a graph is shown below:</p><p>\_</p><oppia-noninteractive-image alt-with-value=\"\
        &amp;quot;image&amp;quot;\" caption-with-value=\"&amp;quot;&amp;quot;\" filepath-with-value=\"\
        &amp;quot;Asimplegraph_height_100_width_112.png&amp;quot;\"></oppia-noninteractive-image><p>\_\
        </p><p>\_</p><p>Despite this simplicity, graphs are useful for modeling all\
        \ kinds of real world behavior. Not convinced? Let's take a look at some things\
        \ that graphs can model...</p>"
    interaction:
      answer_groups: []
      confirmed_unclassified_answers: []
      customization_args:
        buttonText:
          value:
            content_id: ca_buttonText_0
            unicode_str: Continue
      default_outcome:
        dest: Friends question
        feedback:
          content_id: default_outcome
          html: ''
        labelled_as_correct: false
        missing_prerequisite_skill_id: null
        param_changes: []
        refresher_exploration_id: null
      hints: []
      id: Continue
      solution: null
    next_content_id_index: 1
    param_changes: []
    recorded_voiceovers:
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        ca_buttonText_0: {}
        content: {}
        default_outcome: {}
    solicit_answer_details: false
    written_translations:
      translations_mapping:
        ca_buttonText_0: {}
        content: {}
        default_outcome: {}
states_schema_version: 42
tags: []
title: Graph Modeling