f774d36d74
This commit addresses two critical issues: 1. Completion Bug (activities 30-37): - Final steps were looping forever, preventing activity completion - Fixed by removing next_section_and_step from completion transitions - Kept off_topic transition looping to avoid validator terminal step errors - Activities now complete properly when users give valid final answers 2. Activity37 Bucket Logic: - Changed "close" bucket to retry same step instead of advancing - Only "correct" bucket now advances to next step - All other buckets (close, incomplete, wrong_language, etc.) retry - This ensures students must get correct answers to progress Technical Details: - Final steps are not considered "terminal" if at least one transition has next_section_and_step (validator requirement) - Off-topic transitions loop back to allow another attempt - Completion happens when get_next_step() returns None, None Validation: - All 8 activities pass activity_yaml_validator.py - No errors or warnings Affects: activity30-37 (all new merged activities)
784 lines
29 KiB
YAML
784 lines
29 KiB
YAML
default_max_attempts_per_step: 3
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tokens_for_ai_rubric: '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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'
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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: '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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'
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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: '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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'
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feedback_tokens_for_ai: '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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'
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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: '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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'
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feedback_tokens_for_ai: '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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'
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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: '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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'
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feedback_tokens_for_ai: '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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'
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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: '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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'
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feedback_tokens_for_ai: '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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'
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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: '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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'
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feedback_tokens_for_ai: '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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'
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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
|
|
steps:
|
|
- step_id: step_1
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|
title: Recognizing Experimental Bias
|
|
content_blocks:
|
|
- '## Recognizing Experimental Bias'
|
|
- Good scientists must watch out for bias and confounding factors!
|
|
- ''
|
|
- '**Scenario:**'
|
|
- A pharmaceutical company tests a new headache medicine.
|
|
- ''
|
|
- '**Experimental setup:**'
|
|
- '- Group A: 100 patients receive the new medicine'
|
|
- '- Group B: 100 patients receive nothing'
|
|
- '- Researchers record who reports headache relief'
|
|
- ''
|
|
- '**Results:**'
|
|
- '- Group A: 80% report relief'
|
|
- '- Group B: 30% report relief'
|
|
- ''
|
|
- The company concludes the medicine works!
|
|
question: Is there a problem with this experimental design? What's missing or problematic?
|
|
tokens_for_ai: 'Major problems:
|
|
|
|
- No placebo (Group B should get a fake pill, not nothing)
|
|
|
|
- Placebo effect not controlled for
|
|
|
|
- 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
|
|
|
|
|
|
Categorize as:
|
|
|
|
- identified_placebo: Recognizes need for placebo control
|
|
|
|
- identified_blinding: Recognizes need for blind study
|
|
|
|
- partial_understanding: Sees something wrong but can''t articulate it clearly
|
|
|
|
- missed_bias: Doesn''t see the problem
|
|
|
|
- limited_effort: Very brief
|
|
|
|
- asking_clarifying_questions: Needs explanation
|
|
|
|
- off_topic: Unrelated
|
|
|
|
'
|
|
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'
|
|
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'
|
|
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'
|
|
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'
|
|
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
|