994d5e5de9
Created 5 comprehensive educational activities that use only YAML features (buckets, transitions, metadata operations, AI feedback) without Python scripts: - activity30-logic-puzzles.yaml: Critical thinking through deductive reasoning, contrapositives, syllogisms, and knights/knaves puzzles - activity31-scientific-method.yaml: Learn scientific method through historical case studies (Semmelweis, Newton) and experimental design principles - activity32-world-geography.yaml: Choose-your-own-adventure journey exploring continents, countries, capitals, and cultural facts - activity33-environmental-science.yaml: Role-playing as environmental consultant making sustainability decisions on transportation, energy, land use, waste, and food - activity34-media-literacy.yaml: Develop critical media consumption skills, evaluate sources, recognize bias, fact-check claims, and spot manipulation All activities: - Follow existing YAML schema and validate successfully - Use Socratic buckets for educational feedback - Include set_language support - Track progress via metadata - Provide AI-generated personalized feedback - Are educational, engaging, and progressively challenging - Include final reflection steps Also added NEW_ACTIVITIES_PLAN.md documenting the planning process and design rationale for each activity.
677 lines
32 KiB
YAML
677 lines
32 KiB
YAML
default_max_attempts_per_step: 3
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tokens_for_ai_rubric: |
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Evaluate the student's understanding of the scientific method.
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Consider:
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- Their ability to identify steps in the scientific method
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- Understanding of hypothesis formation and testing
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- Recognition of controls and variables
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- Critical thinking about experimental design
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- Engagement with the case studies
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Provide encouraging feedback and suggestions for applying scientific thinking in their own explorations.
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sections:
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- section_id: "introduction"
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title: "Welcome to Scientific Method Explorer"
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steps:
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- step_id: "welcome"
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title: "Welcome to Scientific Method"
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content_blocks:
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- "# Welcome to Scientific Method Explorer!"
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- "Explore how scientists make discoveries through the scientific method."
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- ""
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- "You'll follow in the footsteps of famous scientists, learning to:"
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- "- Ask testable questions"
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- "- Form hypotheses"
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- "- Design experiments"
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- "- Identify variables and controls"
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- "- Analyze results and draw conclusions"
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- ""
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- "**The Scientific Method Steps:**"
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- "1. **Observe** - Notice something interesting"
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- "2. **Question** - Ask why or how"
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- "3. **Hypothesize** - Make an educated guess"
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- "4. **Experiment** - Test your hypothesis"
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- "5. **Analyze** - Look at your data"
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- "6. **Conclude** - Determine if hypothesis was supported"
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- ""
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- "Ready to think like a scientist?"
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question: "Are you ready to explore the scientific method through real discoveries?"
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tokens_for_ai: |
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Student is expressing readiness. Accept any positive response.
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Categorize as:
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- ready: Positive, ready to begin
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- set_language: Setting language preference
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- off_topic: Unrelated
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buckets:
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- ready
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- set_language
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- off_topic
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transitions:
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ready:
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content_blocks:
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- "Excellent! Let's begin with a fascinating historical case study."
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next_section_and_step: "section_1:step_1"
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set_language:
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content_blocks:
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- "I'll communicate in your preferred language."
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counts_as_attempt: false
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next_section_and_step: "introduction:welcome"
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off_topic:
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content_blocks:
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- "Let's get started with exploring science! Are you ready?"
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counts_as_attempt: false
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next_section_and_step: "introduction:welcome"
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- section_id: "section_1"
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title: "Case Study: Germ Theory"
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steps:
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- step_id: "step_1"
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title: "The Mystery of Childbed Fever"
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content_blocks:
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- "## The Mystery of Childbed Fever (1840s)"
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- "**The Observation:**"
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- "Dr. Ignaz Semmelweis noticed something disturbing in his Vienna hospital:"
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- "- Ward 1 (doctors and medical students): 10% of mothers died from childbed fever"
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- "- Ward 2 (midwives): Only 4% of mothers died"
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- ""
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- "**The Puzzle:**"
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- "Both wards had similar conditions, but Ward 1 had much higher death rates."
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- ""
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- "Semmelweis observed that doctors in Ward 1 came directly from autopsy rooms to deliver babies, while midwives in Ward 2 did not perform autopsies."
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question: "What question should Semmelweis ask based on this observation? What do you think might be causing the difference in death rates?"
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tokens_for_ai: |
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Good scientific questions might be:
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- Are doctors carrying something deadly from autopsies?
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- Does something on doctors' hands cause the fever?
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- Is there a connection between autopsies and infections?
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Categorize as:
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- correct_question: Identifies a connection between autopsy work and infections
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- partial_understanding: Notices the pattern but doesn't form a clear causal question
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- creative_thinking: Proposes alternative explanations worth considering
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- limited_effort: Very brief or vague
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- off_topic: Unrelated
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feedback_tokens_for_ai: |
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If they identify the connection to autopsies and handwashing, praise their observation.
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If they suggest other factors, acknowledge the thinking but guide toward the autopsy connection.
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buckets:
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- correct_question
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- partial_understanding
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- creative_thinking
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- limited_effort
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- off_topic
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transitions:
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correct_question:
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ai_feedback:
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tokens_for_ai: "Excellent scientific observation! You've identified the key question that Semmelweis asked."
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metadata_add:
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score: "n+1"
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experiments_designed: "n+1"
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next_section_and_step: "section_1:step_2"
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partial_understanding:
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ai_feedback:
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tokens_for_ai: "Good thinking! Can you be more specific about what might be different about the doctors' hands?"
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next_section_and_step: "section_1:step_2"
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creative_thinking:
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ai_feedback:
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tokens_for_ai: "Interesting hypothesis! Acknowledge their creativity while guiding them to consider the autopsy connection."
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metadata_add:
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score: "n+1"
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next_section_and_step: "section_1:step_2"
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limited_effort:
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content_blocks:
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- "Think about what the doctors were doing that the midwives were not. What might they be carrying on their hands?"
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next_section_and_step: "section_1:step_1"
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off_topic:
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content_blocks:
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- "Let's focus on the medical mystery. What difference between the two wards might explain the death rates?"
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next_section_and_step: "section_1:step_1"
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- step_id: "step_2"
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title: "Forming a Hypothesis"
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content_blocks:
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- "## Forming a Hypothesis"
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- "Semmelweis formed a hypothesis:"
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- ""
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- "**'Cadaveric particles' from autopsies on doctors' hands are causing childbed fever.**"
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- ""
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- "This was revolutionary! In the 1840s, germs were not yet understood."
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- ""
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- "**Now for the experiment:**"
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- "Semmelweis needs to test this hypothesis. He decides to require doctors to wash their hands with chlorinated lime solution before examining patients."
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- ""
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- "**Question for you:**"
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- "To make this a good scientific experiment, what should we compare?"
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question: "What should Semmelweis measure before and after the handwashing requirement? What would be the control group?"
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tokens_for_ai: |
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Good answers should mention:
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- Measure death rates before and after handwashing
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- Compare Ward 1 with handwashing to previous Ward 1 without handwashing
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- Or compare Ward 1 (with handwashing) to Ward 2 (baseline)
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- The control is the previous data or Ward 2
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Categorize as:
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- correct_method: Identifies need to compare death rates before/after or between groups
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- partial_understanding: Mentions measuring death rates but unclear on control
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- confused_about_controls: Doesn't understand the concept of a control group
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- limited_effort: Very brief answer
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- asking_clarifying_questions: Requests explanation of terms
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- off_topic: Unrelated
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feedback_tokens_for_ai: |
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If they understand controls, praise them! If confused about controls, explain that
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a control group helps us know if changes are due to our intervention or something else.
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buckets:
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- correct_method
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- partial_understanding
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- confused_about_controls
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- limited_effort
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- asking_clarifying_questions
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- off_topic
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transitions:
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correct_method:
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ai_feedback:
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tokens_for_ai: "Excellent experimental thinking! You understand the importance of controls in science."
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metadata_add:
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score: "n+2"
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controls_identified: "n+1"
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next_section_and_step: "section_1:step_3"
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partial_understanding:
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ai_feedback:
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tokens_for_ai: "Good! You're thinking about measurement. Explain what a control group is and why it's important."
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metadata_add:
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score: "n+1"
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next_section_and_step: "section_1:step_3"
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confused_about_controls:
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content_blocks:
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- "**Control groups** help us compare results."
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- "We need to know: Are death rates different WITH handwashing vs WITHOUT handwashing?"
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- "That way we know if handwashing made the difference!"
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next_section_and_step: "section_1:step_2"
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limited_effort:
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content_blocks:
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- "Think about what Semmelweis should measure and what he should compare it to."
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next_section_and_step: "section_1:step_2"
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asking_clarifying_questions:
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ai_feedback:
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tokens_for_ai: "Answer their question about experimental design and controls helpfully."
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counts_as_attempt: false
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next_section_and_step: "section_1:step_2"
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off_topic:
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content_blocks:
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- "Let's focus on designing the experiment. What should we measure?"
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next_section_and_step: "section_1:step_2"
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- step_id: "step_3"
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title: "The Results!"
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content_blocks:
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- "## The Results!"
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- "Semmelweis implemented handwashing with chlorinated lime in 1847."
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- ""
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- "**The data:**"
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- "- **Before handwashing (1846):** Death rate in Ward 1 = 10%"
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- "- **After handwashing (1847-1848):** Death rate in Ward 1 = 2%"
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- ""
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- "This was a dramatic improvement! The death rate dropped by 80%."
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- ""
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- "**Analysis step:**"
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- "Now we must analyze these results and draw a conclusion."
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question: "Based on these results, was Semmelweis's hypothesis supported? What can we conclude about the cause of childbed fever?"
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tokens_for_ai: |
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The hypothesis WAS supported - handwashing dramatically reduced death rates, suggesting
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that something on doctors' hands (cadaveric particles/germs) was indeed causing the fever.
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Categorize as:
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- correct_conclusion: States hypothesis was supported, handwashing worked, something on hands caused illness
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- partial_understanding: Gets general idea but incomplete reasoning
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- overstating: Claims this "proves" rather than "supports" (good to address scientific certainty)
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- limited_effort: Very brief
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- off_topic: Unrelated
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feedback_tokens_for_ai: |
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If correct, praise their analysis! If they say "proves," gently explain that in science
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we say evidence "supports" a hypothesis rather than "proves" it absolutely.
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buckets:
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- correct_conclusion
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- partial_understanding
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- overstating
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- limited_effort
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- off_topic
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transitions:
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correct_conclusion:
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ai_feedback:
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tokens_for_ai: "Excellent analysis! You've worked through a complete scientific investigation. Explain the impact this had on medicine."
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metadata_add:
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score: "n+2"
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case_studies_completed: "n+1"
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next_section_and_step: "section_2:step_1"
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partial_understanding:
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ai_feedback:
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tokens_for_ai: "Good! Can you connect the results more explicitly to the hypothesis about what was on doctors' hands?"
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metadata_add:
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score: "n+1"
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case_studies_completed: "n+1"
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next_section_and_step: "section_2:step_1"
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overstating:
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ai_feedback:
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tokens_for_ai: "Great thinking! One note: in science we say results 'support' a hypothesis rather than 'prove' it. Explain why scientific conclusions are provisional."
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metadata_add:
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score: "n+1"
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case_studies_completed: "n+1"
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next_section_and_step: "section_2:step_1"
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limited_effort:
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content_blocks:
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- "Look at the dramatic change in death rates. What does this tell us about Semmelweis's hypothesis?"
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next_section_and_step: "section_1:step_3"
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off_topic:
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content_blocks:
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- "Let's analyze the data. Death rates dropped from 10% to 2%. What does this mean?"
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next_section_and_step: "section_1:step_3"
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- section_id: "section_2"
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title: "Design Your Own Experiment"
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steps:
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- step_id: "step_1"
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title: "Newton's Light Experiment"
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content_blocks:
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- "## Newton's Light Experiment"
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- "Let's explore another famous case, then YOU'LL design an experiment!"
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- ""
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- "**The Observation (1660s):**"
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- "Isaac Newton observed that sunlight passing through a prism splits into rainbow colors."
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- ""
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- "**The Common Belief:**"
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- "Most people thought the prism was adding color to the light, like stained glass adds color."
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- ""
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- "**Newton's Hypothesis:**"
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- "Newton proposed something radical: White light is actually MADE of all the colors combined, and the prism just separates them."
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- ""
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- "**Your Task:**"
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- "Newton needs to prove that the colors come FROM the white light, not from the prism."
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question: "Design an experiment that could test whether the colors are already in white light or are created by the prism. What would you do?"
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tokens_for_ai: |
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Newton's actual experiment: He used a second prism to recombine the separated colors
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back into white light. If the prism created the colors, you couldn't get white light back.
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Good student answers might suggest:
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- Using a second prism to recombine colors
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- Testing different prisms (if prism creates color, different prisms would create different colors)
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- Blocking some colors and seeing what recombines
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- Comparing different light sources
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Categorize as:
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- excellent_design: Proposes recombining colors or testing multiple prisms
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- creative_approach: Different but scientifically sound experiment
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- partial_understanding: Has an idea but experimental design is unclear
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- confused: Doesn't understand what needs to be tested
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- limited_effort: Very brief
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- asking_clarifying_questions: Needs help
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- off_topic: Unrelated
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feedback_tokens_for_ai: |
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Encourage creative experimental thinking! If they propose recombining colors, that's
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exactly what Newton did. If they have other ideas, evaluate if they would actually
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distinguish between the two hypotheses.
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buckets:
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- excellent_design
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- creative_approach
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- partial_understanding
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- confused
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- limited_effort
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- asking_clarifying_questions
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- off_topic
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transitions:
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excellent_design:
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ai_feedback:
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tokens_for_ai: "Brilliant experimental design! Explain how this is similar to what Newton actually did and praise their scientific thinking."
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metadata_add:
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score: "n+3"
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experiments_designed: "n+1"
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next_section_and_step: "section_2:step_2"
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creative_approach:
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ai_feedback:
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tokens_for_ai: "Interesting approach! Evaluate whether their experiment would actually distinguish between the two hypotheses. If yes, praise them. If not, guide them."
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metadata_add:
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score: "n+2"
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experiments_designed: "n+1"
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next_section_and_step: "section_2:step_2"
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partial_understanding:
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ai_feedback:
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tokens_for_ai: "You're thinking in the right direction. Ask: if the prism creates color, could you reverse the process? If light contains the colors, could you recombine them?"
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next_section_and_step: "section_2:step_1"
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confused:
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content_blocks:
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- "**Hint:** Think about what would happen differently based on each explanation:"
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- "- If the PRISM creates color, could you get white light back from colored light?"
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- "- If WHITE LIGHT contains colors, could you recombine them?"
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next_section_and_step: "section_2:step_1"
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limited_effort:
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content_blocks:
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- "Take time to think creatively! How could you test whether colors come from the light or from the prism?"
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next_section_and_step: "section_2:step_1"
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asking_clarifying_questions:
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ai_feedback:
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tokens_for_ai: "Answer their question and provide guidance on experimental design principles."
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counts_as_attempt: false
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next_section_and_step: "section_2:step_1"
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off_topic:
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content_blocks:
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- "Let's focus on designing an experiment about light and prisms."
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next_section_and_step: "section_2:step_1"
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- step_id: "step_2"
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title: "Identifying Variables"
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content_blocks:
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- "## Identifying Variables"
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- "Great thinking! Newton did indeed use a second prism to recombine the colors back into white light."
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- ""
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- "**Understanding Variables:**"
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- "In any experiment, we need to identify:"
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- "- **Independent variable:** What YOU change"
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- "- **Dependent variable:** What you MEASURE"
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- "- **Control variables:** What you keep THE SAME"
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- ""
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- "**Example scenario:**"
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- "You want to test if plants grow faster with music."
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- ""
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- "You set up:"
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- "- 10 plants with music"
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- "- 10 plants without music"
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- "- All plants get same water, light, soil, and temperature"
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- "- Measure growth after 2 weeks"
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question: "Identify the independent variable, dependent variable, and control variables in this plant experiment."
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tokens_for_ai: |
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Correct answers:
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- Independent variable: Presence/absence of music (what you change)
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- Dependent variable: Plant growth/height (what you measure)
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- Control variables: Water, light, soil, temperature (what you keep the same)
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Categorize as:
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- correct: Correctly identifies all three types of variables
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- partial_understanding: Gets 2 out of 3 correct
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- confused: Mixes up independent and dependent
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- limited_effort: Very brief or incomplete
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- asking_clarifying_questions: Needs clarification
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- off_topic: Unrelated
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feedback_tokens_for_ai: |
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If they confuse independent and dependent, explain: independent is what the experimenter
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controls/changes, dependent is what responds/changes as a result.
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buckets:
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- correct
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- partial_understanding
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- confused
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- limited_effort
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- asking_clarifying_questions
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- off_topic
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transitions:
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correct:
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ai_feedback:
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tokens_for_ai: "Perfect! You understand variables - a crucial concept in experimental design."
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metadata_add:
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score: "n+2"
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controls_identified: "n+1"
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next_section_and_step: "section_3:step_1"
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partial_understanding:
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ai_feedback:
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tokens_for_ai: "Good start! Clarify which variables they got right and help with the others."
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metadata_add:
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score: "n+1"
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next_section_and_step: "section_3:step_1"
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confused:
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content_blocks:
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- "**Tip:** The INDEPENDENT variable is what the experimenter changes on purpose."
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- "The DEPENDENT variable is what you measure to see the effect."
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- "CONTROL variables are kept the same so they don't interfere."
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next_section_and_step: "section_2:step_2"
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limited_effort:
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content_blocks:
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- "Try to identify each type: What are you changing? What are you measuring? What are you keeping the same?"
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next_section_and_step: "section_2:step_2"
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asking_clarifying_questions:
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ai_feedback:
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tokens_for_ai: "Answer their question about variables clearly with examples."
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counts_as_attempt: false
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next_section_and_step: "section_2:step_2"
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off_topic:
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content_blocks:
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- "Let's focus on identifying the different types of variables in this experiment."
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next_section_and_step: "section_2:step_2"
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- section_id: "section_3"
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title: "Avoiding Bias and Errors"
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steps:
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- step_id: "step_1"
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title: "Recognizing Experimental Bias"
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content_blocks:
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- "## Recognizing Experimental Bias"
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|
- "Good scientists must watch out for bias and confounding factors!"
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|
- ""
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|
- "**Scenario:**"
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|
- "A pharmaceutical company tests a new headache medicine."
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|
- ""
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|
- "**Experimental setup:**"
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|
- "- Group A: 100 patients receive the new medicine"
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|
- "- Group B: 100 patients receive nothing"
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|
- "- Researchers record who reports headache relief"
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|
- ""
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|
- "**Results:**"
|
|
- "- Group A: 80% report relief"
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|
- "- Group B: 30% report relief"
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|
- ""
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|
- "The company concludes the medicine works!"
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|
question: "Is there a problem with this experimental design? What's missing or problematic?"
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|
tokens_for_ai: |
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|
Major problems:
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|
- No placebo (Group B should get a fake pill, not nothing)
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|
- Placebo effect not controlled for
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|
- Patients know if they're getting treatment (should be blind/double-blind)
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|
- Researcher bias possible if they know who got real medicine
|
|
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|
Categorize as:
|
|
- identified_placebo: Recognizes need for placebo control
|
|
- identified_blinding: Recognizes need for blind study
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|
- partial_understanding: Sees something wrong but can't articulate it clearly
|
|
- missed_bias: Doesn't see the problem
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|
- limited_effort: Very brief
|
|
- asking_clarifying_questions: Needs explanation
|
|
- off_topic: Unrelated
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|
feedback_tokens_for_ai: |
|
|
If they identify placebo effect, excellent! If not, explain that people often feel
|
|
better just because they think they're getting treatment. That's why we need placebo
|
|
controls and blind studies.
|
|
buckets:
|
|
- identified_placebo
|
|
- identified_blinding
|
|
- partial_understanding
|
|
- missed_bias
|
|
- limited_effort
|
|
- asking_clarifying_questions
|
|
- off_topic
|
|
transitions:
|
|
identified_placebo:
|
|
ai_feedback:
|
|
tokens_for_ai: "Excellent! You identified the placebo effect. Explain why placebos are crucial in medical research."
|
|
metadata_add:
|
|
score: "n+3"
|
|
bias_identified: "n+1"
|
|
next_section_and_step: "section_3:step_2"
|
|
identified_blinding:
|
|
ai_feedback:
|
|
tokens_for_ai: "Great catch! Explain how blinding prevents bias in both patients and researchers."
|
|
metadata_add:
|
|
score: "n+3"
|
|
bias_identified: "n+1"
|
|
next_section_and_step: "section_3:step_2"
|
|
partial_understanding:
|
|
ai_feedback:
|
|
tokens_for_ai: "You're sensing something's wrong. Guide them toward the placebo effect concept."
|
|
next_section_and_step: "section_3:step_1"
|
|
missed_bias:
|
|
content_blocks:
|
|
- "**Hint:** Think about the psychological effect of KNOWING you're getting medicine."
|
|
- "What if people feel better just because they believe they're being treated?"
|
|
next_section_and_step: "section_3:step_1"
|
|
limited_effort:
|
|
content_blocks:
|
|
- "Think carefully: Is it fair to compare people who GET something to people who get NOTHING?"
|
|
next_section_and_step: "section_3:step_1"
|
|
asking_clarifying_questions:
|
|
ai_feedback:
|
|
tokens_for_ai: "Answer their question about experimental design and bias."
|
|
counts_as_attempt: false
|
|
next_section_and_step: "section_3:step_1"
|
|
off_topic:
|
|
content_blocks:
|
|
- "Let's analyze this medical experiment. Is the design fair and unbiased?"
|
|
next_section_and_step: "section_3:step_1"
|
|
|
|
- step_id: "step_2"
|
|
title: "Scientific Integrity"
|
|
content_blocks:
|
|
- "## Scientific Integrity"
|
|
- "Excellent work identifying bias!"
|
|
- ""
|
|
- "**Key principles for good science:**"
|
|
- ""
|
|
- "✓ **Use controls** - Compare to a baseline or control group"
|
|
- "✓ **Use placebos** - Control for psychological effects"
|
|
- "✓ **Blind studies** - Subjects don't know if they got real treatment"
|
|
- "✓ **Double-blind** - Researchers also don't know (prevents their bias)"
|
|
- "✓ **Replicate** - Repeat experiments to confirm results"
|
|
- "✓ **Peer review** - Other scientists check your work"
|
|
- "✓ **Large sample sizes** - More data = more reliable"
|
|
- "✓ **Account for confounding variables** - What else might affect results?"
|
|
- ""
|
|
- "These principles help ensure that scientific findings are reliable and trustworthy."
|
|
question: "Why do you think it's important for other scientists to be able to replicate (repeat) an experiment? What purpose does replication serve in science?"
|
|
tokens_for_ai: |
|
|
Good answers mention:
|
|
- Verifying results weren't due to chance
|
|
- Catching errors or fraud
|
|
- Building confidence in findings
|
|
- Testing if results hold in different conditions
|
|
- Science is self-correcting
|
|
|
|
Categorize as:
|
|
- insightful: Understands multiple purposes of replication
|
|
- correct_understanding: Gets the basic concept (verification)
|
|
- partial_understanding: General idea but incomplete
|
|
- limited_effort: Very brief
|
|
- off_topic: Unrelated
|
|
feedback_tokens_for_ai: |
|
|
Encourage their understanding of how science builds reliable knowledge through
|
|
replication and peer review. Connect it to why we can trust scientific consensus.
|
|
buckets:
|
|
- insightful
|
|
- correct_understanding
|
|
- partial_understanding
|
|
- limited_effort
|
|
- off_topic
|
|
transitions:
|
|
insightful:
|
|
ai_feedback:
|
|
tokens_for_ai: "Excellent understanding of scientific process! You grasp why science is a self-correcting system."
|
|
metadata_add:
|
|
score: "n+3"
|
|
next_section_and_step: "section_4:step_1"
|
|
correct_understanding:
|
|
ai_feedback:
|
|
tokens_for_ai: "Correct! Replication is indeed crucial for verifying results. Expand on other benefits if they didn't mention them."
|
|
metadata_add:
|
|
score: "n+2"
|
|
next_section_and_step: "section_4:step_1"
|
|
partial_understanding:
|
|
ai_feedback:
|
|
tokens_for_ai: "You're on the right track. Explain how replication helps catch errors and builds confidence."
|
|
metadata_add:
|
|
score: "n+1"
|
|
next_section_and_step: "section_4:step_1"
|
|
limited_effort:
|
|
content_blocks:
|
|
- "Think about what happens if only ONE person does an experiment. How do we know if their result was accurate?"
|
|
next_section_and_step: "section_3:step_2"
|
|
off_topic:
|
|
content_blocks:
|
|
- "Let's focus on why repeating experiments is important in science."
|
|
next_section_and_step: "section_3:step_2"
|
|
|
|
- section_id: "section_4"
|
|
title: "Reflection and Conclusion"
|
|
steps:
|
|
- step_id: "step_1"
|
|
title: "Congratulations!"
|
|
content_blocks:
|
|
- "## Congratulations, Scientist! 🔬"
|
|
- "You've completed the Scientific Method Explorer!"
|
|
- ""
|
|
- "**What you've learned:**"
|
|
- "✓ The steps of the scientific method"
|
|
- "✓ How to form testable hypotheses"
|
|
- "✓ Experimental design principles"
|
|
- "✓ Identifying variables (independent, dependent, control)"
|
|
- "✓ The importance of controls and placebos"
|
|
- "✓ Recognizing bias in experiments"
|
|
- "✓ Why replication and peer review matter"
|
|
- ""
|
|
- "**Famous scientists you studied:**"
|
|
- "- Ignaz Semmelweis (germ theory and handwashing)"
|
|
- "- Isaac Newton (nature of light)"
|
|
- ""
|
|
- "**Why this matters:**"
|
|
- "The scientific method is how we reliably discover truth about the natural world."
|
|
- "These principles apply whether you're:"
|
|
- "- Testing a new technology"
|
|
- "- Debugging code (forming and testing hypotheses!)"
|
|
- "- Evaluating health claims"
|
|
- "- Understanding climate science"
|
|
- "- Or pursuing any evidence-based inquiry"
|
|
question: "How might you apply scientific thinking in your own life or studies? Give an example of a question you could investigate using the scientific method."
|
|
tokens_for_ai: |
|
|
This is a reflection question. Accept any thoughtful application of scientific method
|
|
to a real-world question or problem.
|
|
|
|
Categorize as:
|
|
- excellent_application: Proposes a specific, testable question with clear methodology
|
|
- good_application: Identifies a reasonable application area
|
|
- basic_reflection: General but genuine reflection
|
|
- limited_effort: Very brief
|
|
- off_topic: Unrelated
|
|
feedback_tokens_for_ai: |
|
|
Provide personalized, encouraging feedback on their learning journey. Acknowledge their
|
|
application ideas. Encourage them to actually try investigating something scientifically.
|
|
Emphasize that scientific thinking is a powerful tool for understanding the world.
|
|
buckets:
|
|
- excellent_application
|
|
- good_application
|
|
- basic_reflection
|
|
- limited_effort
|
|
- off_topic
|
|
transitions:
|
|
excellent_application:
|
|
ai_feedback:
|
|
tokens_for_ai: "Fantastic! Your example shows you truly understand how to apply the scientific method. Encourage them to actually investigate their question!"
|
|
metadata_add:
|
|
activity_completed: "true"
|
|
next_section_and_step: "section_4:step_1"
|
|
good_application:
|
|
ai_feedback:
|
|
tokens_for_ai: "Great thinking! Provide positive feedback and suggestions for how they could make their investigation more rigorous."
|
|
metadata_add:
|
|
activity_completed: "true"
|
|
next_section_and_step: "section_4:step_1"
|
|
basic_reflection:
|
|
ai_feedback:
|
|
tokens_for_ai: "Thank them for their reflection and summarize the key scientific principles they've learned."
|
|
metadata_add:
|
|
activity_completed: "true"
|
|
next_section_and_step: "section_4:step_1"
|
|
limited_effort:
|
|
ai_feedback:
|
|
tokens_for_ai: "Acknowledge their completion and encourage them to think scientifically in their daily life."
|
|
metadata_add:
|
|
activity_completed: "true"
|
|
next_section_and_step: "section_4:step_1"
|
|
off_topic:
|
|
content_blocks:
|
|
- "Think about how you could use scientific thinking in your own investigations. What question might you explore?"
|
|
next_section_and_step: "section_4:step_1"
|