Age Group: 11-12 years (Grade 6)
Duration: 6-12 weeks (flexible implementation)
Teacher(s): Cross-curricular team
School: [School Name]
Title: Probability Patterns: Data Science as Creative Expression
How We Express Ourselves
An inquiry into the ways in which we discover and express ideas, feelings, nature, culture, beliefs and values; the ways in which we reflect on, extend and enjoy our creativity; our appreciation of the aesthetic.
Data visualization is a powerful language that transforms numbers into stories, helping us understand patterns in our world and communicate discoveries that matter to our communities.
Form: What patterns and structures exist in data and probability?
Function: How do different visualization techniques serve different purposes in communication?
Connection: How do data patterns connect to real-world phenomena and human experiences?
Pattern, Representation, Communication, Evidence, Probability, Uncertainty, Prediction
Discovering Probability Patterns: How mathematical tools help us understand chance and predict outcomes
Artistic Data Communication: How visualization design principles enhance understanding and emotional connection
Community Impact Stories: How data science serves social justice and environmental stewardship
Historical and Contemporary Perspectives: Learning from data visualization pioneers and modern artists
Inquirers: Developing natural curiosity about probability patterns in everyday life
Thinkers: Using critical and creative thinking to interpret statistical evidence and make predictions
Communicators: Expressing mathematical findings through multiple modalities including digital and artistic formats
Risk-takers: Embracing uncertainty and experimental approaches to probability learning
Caring: Using data analysis to understand and address community and environmental challenges
Reflective: Evaluating the effectiveness of different approaches to data communication
Formative Assessments:
Daily probability experiment journals with sample space documentation
Peer feedback on tree diagram accuracy and experimental probability calculations
Digital portfolio development showing progression in Google Sheets proficiency
Mini-presentations of data pioneer research with mathematical demonstrations
Collaborative analysis of real-world probability scenarios
Summative Assessments:
Week 3: Sample Space Art Gallery combining cultural traditions with mathematical accuracy
Week 4: Environmental Probability Investigation using authentic scientific datasets
Week 6: Community Data Stories Exhibition with interactive probability demonstrations
Weekly reflection prompts connecting probability concepts to scientific and artistic applications
Peer feedback protocols for experimental design and data interpretation
Self-assessment rubrics for mathematical accuracy and creative communication
Digital documentation of learning progression through multimedia portfolios
CORE Activities (Essential for standards mastery - all implementations)
HIGH IMPACT Activities (Strongly recommended for deeper learning)
ENRICHMENT Activities (Valuable additions when time permits)
Implementation Levels:
Quick: 6-8 weeks, focus on essential probability standards
Standard: 8-10 weeks, balanced approach with STEAM integration
Extended: 10-12 weeks, comprehensive community connections
WEEK 1: Probability Foundations & Data Pioneers
Day 1: Charles Minard - Mapping Data Stories Guiding Question: How can data visualization reveal hidden stories about human experiences?
Learning Objectives:
Understand data visualization as storytelling medium
Recognize Charles Minard's contributions to statistical graphics
Begin developing statistical questioning skills
Activities (50 minutes):
Napoleon's March Investigation (20 min): Examine Minard's famous 1869 map; identify the six types of data represented simultaneously
Data Detective Training (20 min): Practice reading complex visualizations; discuss what makes them effective for communication
Statistical Questions Brainstorm (10 min): Generate questions about school/community that could be answered through data collection
Materials: Minard map reproductions, statistical question templates, investigation worksheets Assessment Evidence: Students identify 4+ data dimensions in complex visualizations and formulate 3+ statistical questions Standards Alignment: Foundation for 6.4.1.1 (understanding outcomes and events in context) Implementation Options: Extended includes creating timeline of Minard's life and historical context research
Day 2: John Snow - Data for Social Change Guiding Question: How can data analysis solve real-world problems and save lives?
Learning Objectives:
Explore John Snow's use of data mapping to solve cholera outbreak
Understand data as evidence for scientific claims
Connect historical data work to contemporary community challenges
Activities (50 minutes):
Cholera Mystery Investigation (25 min): Use Snow's original data to recreate his analysis; plot deaths and water pumps on map
Modern Disease Tracking (15 min): Examine how epidemiologists use similar methods today (COVID-19 tracking, flu patterns)
Community Problem Identification (10 min): Brainstorm local issues that could benefit from data analysis approaches
Materials: Snow's cholera data, London maps, colored markers, contemporary epidemiology examples Assessment Evidence: Students successfully recreate Snow's analysis and identify 2+ modern applications Standards Alignment: Foundation for 6.4.1.4 (using data to make predictions and solve problems) Implementation Options: Extended includes partnership with local health department for authentic data
Day 3: Sample Space Foundations Guiding Question: What are all the possible things that could happen in a probability experiment?
Learning Objectives (Standard 6.4.1.1):
Define sample space as set of all possible outcomes
Determine sample spaces for simple experiments (≤36 outcomes)
Use organized lists and tables to represent sample spaces systematically
Activities (50 minutes):
Outcome Discovery (15 min): Physical exploration with coins, dice, spinners; list all possible results
Sample Space Organization (25 min): Create systematic lists and tables for single and two-step experiments
Sample Space Size Challenge (10 min): Determine which experiments have sample spaces ≤36; explain reasoning
Materials: Coins, dice, 6-sided spinners, organization worksheets, chart paper Assessment Evidence: Accurate and complete sample space determination for 3+ different experiment types Standards Alignment: 6.4.1.1 (Determine sample space using tables and organized representations) Implementation Options: Enrichment includes designing custom experiments with specified sample space sizes
Day 4: Tree Diagrams & Systematic Counting Guiding Question: How can tree diagrams help us organize complex probability experiments systematically?
Learning Objectives (Standard 6.4.1.1):
Create tree diagrams for multi-step experiments
Use tree diagrams to find complete sample spaces
Connect visual organization to systematic counting principles
Activities (50 minutes):
Physical Tree Building (20 min): Use branches and index cards to build 3D tree diagrams for 2-step experiments
Paper Tree Mastery (20 min): Draw tree diagrams for increasingly complex scenarios (clothing choices, meal combinations)
Tree to Table Translation (10 min): Convert tree diagrams to organized tables; verify completeness
Materials: Tree diagram templates, index cards, colored pencils, rulers, sample scenarios Assessment Evidence: Accurate tree diagrams producing complete sample spaces for multi-step experiments Standards Alignment: 6.4.1.1 (Sample space determination using tree diagrams) Implementation Options: Extended includes cultural pattern integration inspired by traditional tree-of-life artwork
Day 5: Aaron Koblin - Digital Data Art Guiding Question: How do contemporary artists use technology to make data beautiful and meaningful?
Learning Objectives:
Explore Aaron Koblin's approach to data visualization as art
Understand technology's role in modern data storytelling
Begin connecting mathematical accuracy with aesthetic communication
Activities (50 minutes):
Flight Patterns Analysis (20 min): Examine Koblin's airline visualization; discuss how movement patterns reveal social behavior
Design Elements Investigation (20 min): Identify artistic choices (color, movement, scale) that enhance data understanding
Digital Art Planning (10 min): Sketch ideas for representing probability data using Koblin-inspired digital techniques
Materials: Koblin artwork examples, design analysis worksheets, digital planning templates Assessment Evidence: Students identify 3+ design principles and plan digital representation of mathematical content Standards Alignment: Artistic integration supporting all probability standards through enhanced communication Implementation Options: Extended includes video creation showing probability experiments in motion
WEEK 2: Probability Calculations & Experimental Design
Day 6: Probability as Ratio Foundations Guiding Question: How can we express the likelihood of events using mathematical ratios?
Learning Objectives (Standard 6.4.1.2):
Calculate probability using ratio of event size to sample space size
Express probabilities as fractions with sample spaces ≤100
Use vocabulary: likely, unlikely, certain, impossible, probability
Activities (50 minutes):
Likelihood Language Development (15 min): Sort events into probability categories; justify using mathematical reasoning
Ratio Calculation Practice (25 min): Calculate probabilities for dice, cards, spinners; express as fractions
Reasonableness Checking (10 min): Verify probability calculations make sense; identify impossible results
Materials: Probability manipulatives, fraction calculation worksheets, likelihood sorting cards Assessment Evidence: Accurate probability calculations with appropriate likelihood vocabulary for 5+ scenarios Standards Alignment: 6.4.1.2 (Determine probability using ratios; understand likelihood) Implementation Options: Enrichment includes probability calculations with sample spaces approaching 100
Day 7: Fractions, Decimals, Percents in Probability Guiding Question: How can we express the same probability in different mathematical forms?
Learning Objectives (Standard 6.4.1.2):
Convert probabilities between fractions, decimals, and percents
Choose appropriate representations for different audiences
Understand equivalent expressions of likelihood
Activities (50 minutes):
Conversion Practice Stations (30 min): Rotate through fraction-decimal-percent conversion activities using probability contexts
Audience Adaptation Challenge (15 min): Express same probability for different audiences (sports fans prefer percents, mathematicians prefer fractions)
Real-World Probability Collection (5 min): Find examples of probability expressions in media, weather, sports
Materials: Conversion charts, calculators, real-world probability examples, station materials Assessment Evidence: Fluent conversion between representations with audience-appropriate choices Standards Alignment: 6.4.1.2 (Represent probabilities as percents, fractions, decimals) Implementation Options: Extended includes media analysis of probability reporting accuracy
Day 8: Chris Jordan - Data Art for Social Change Guiding Question: How can artists use overwhelming data to create emotional connections and motivate action?
Learning Objectives:
Analyze Chris Jordan's approach to representing massive numerical data
Understand emotional impact of data visualization choices
Connect probability thinking to environmental and social issues
Activities (50 minutes):
"Running the Numbers" Gallery Walk (25 min): Examine Jordan's artwork representing American consumption; calculate underlying statistics
Emotional Impact Discussion (15 min): Discuss how artistic choices (scale, repetition, imagery) affect viewer response to data
Social Issue Data Research (10 min): Identify environmental or social issues involving probability (climate risks, conservation success rates)
Materials: Jordan artwork reproductions, statistical analysis worksheets, social issue research materials Assessment Evidence: Students calculate statistics underlying artistic representations and identify social applications Standards Alignment: Real-world application of probability calculations for social understanding Implementation Options: Extended includes creating Jordan-inspired artwork representing local environmental data
Day 9: Experimental Probability Introduction Guiding Question: What happens when we actually perform probability experiments many times?
Learning Objectives (Standard 6.4.1.3):
Conduct probability experiments with systematic data collection
Compare experimental results to theoretical predictions
Understand variability in experimental outcomes
Activities (50 minutes):
Individual Experiments (20 min): Each student conducts 50 coin flips; record results systematically
Class Data Compilation (20 min): Combine individual results; calculate overall experimental probability
Theory vs. Reality Discussion (10 min): Compare class results to theoretical 50%; discuss why differences occur
Materials: Coins, data recording sheets, class compilation charts, calculators Assessment Evidence: Accurate experimental data collection with thoughtful comparison to theoretical probability Standards Alignment: 6.4.1.3 (Perform experiments comparing experimental and theoretical probability) Implementation Options: Extended includes long-term experiments tracked over multiple days
Day 10: Complex Experimental Design Guiding Question: How can we design probability experiments to answer questions about fairness and prediction?
Learning Objectives (Standard 6.4.1.3 & 6.4.1.4):
Design experiments to test theoretical probability predictions
Calculate experimental probabilities from collected data
Make predictions based on experimental evidence
Activities (50 minutes):
Experiment Design Challenge (15 min): Design experiments to test whether games/spinners are fair; plan data collection methods
Data Collection Implementation (25 min): Conduct designed experiments; record results systematically
Prediction Making (10 min): Use experimental results to make predictions about future outcomes
Materials: Various probability tools (dice, spinners, cards), experiment design templates, prediction worksheets Assessment Evidence: Well-designed experiments with accurate data collection and reasonable predictions Standards Alignment: 6.4.1.3 and 6.4.1.4 (Experimental probability and prediction) Implementation Options: Enrichment includes experiments with sample spaces approaching 100 outcomes
WEEK 3: Cultural Integration & Community Applications
Day 11: Sample Space Art Gallery Project Launch Guiding Question: How can we combine mathematical precision with cultural art traditions?
Learning Objectives:
Research traditional artistic approaches to pattern and organization
Plan large-scale artistic displays demonstrating sample space concepts
Integrate cultural mathematics with contemporary probability understanding
Activities (50 minutes):
Cultural Art Research (20 min): Investigate traditional pattern-making (Aboriginal dot painting, Islamic geometric patterns, African textiles)
Mathematical Art Planning (25 min): Design artistic displays showing sample spaces using cultural techniques
Material Preparation (5 min): Gather supplies for multi-day art creation project
Materials: Cultural art examples, large poster boards, traditional art supplies, planning templates Assessment Evidence: Research-based art plans integrating cultural traditions with mathematical accuracy Standards Alignment: 6.4.1.1 application through artistic expression Implementation Options: Extended includes community elder interviews about traditional mathematical practices
Day 12: Probability Pattern Quilts Guiding Question: How do traditional quilting patterns demonstrate mathematical probability concepts?
Learning Objectives:
Analyze mathematical relationships in traditional quilt designs
Create probability experiments using quilt-inspired patterns
Document experimental results using multiple representation methods
Activities (50 minutes):
Quilt Mathematics Investigation (15 min): Examine traditional patterns for symmetry, repetition, and probability relationships
Quilt-Based Probability Experiments (25 min): Design experiments using quilt square patterns to represent equal likelihood
Dual Documentation (10 min): Record results in both spreadsheet and fabric sample formats
Materials: Quilt pattern examples, fabric squares, needles, thread, pattern-based probability tools Assessment Evidence: Mathematical experiments with accurate documentation in multiple formats Standards Alignment: 6.4.1.2 and 6.4.1.3 foundations through traditional craft integration Implementation Options: Extended includes creating actual quilt squares for permanent display
Day 13: Google Sheets Probability Calculations Guiding Question: How can spreadsheet technology help us analyze probability data efficiently?
Learning Objectives:
Use Google Sheets for probability calculations and data organization
Create charts and graphs representing probability experimental results
Develop digital portfolio documentation skills
Activities (50 minutes):
Spreadsheet Setup (15 min): Create organized data entry systems for probability experiments
Formula Application (25 min): Use formulas to calculate experimental probabilities; create comparative charts
Digital Portfolio Integration (10 min): Add spreadsheet work to ongoing digital learning documentation
Materials: Chromebooks/tablets, Google Sheets tutorial materials, experimental data from previous days Assessment Evidence: Functional spreadsheets with accurate formulas and clear data visualization Standards Alignment: Technology integration supporting all probability standards Implementation Options: Extended includes advanced functions and collaborative spreadsheet analysis
Day 14: Environmental Probability Applications Guiding Question: How does probability thinking help us understand environmental patterns and make conservation decisions?
Learning Objectives:
Apply probability concepts to environmental and climate data
Calculate probabilities related to natural phenomena
Connect mathematical thinking to environmental stewardship
Activities (50 minutes):
Weather Probability Analysis (20 min): Use local weather data to calculate probabilities of rain, snow, temperature ranges
Conservation Success Rates (20 min): Analyze wildlife protection program data; calculate survival and recovery probabilities
Environmental Prediction (10 min): Use probability data to make predictions about environmental outcomes
Materials: Environmental datasets, weather records, conservation organization data Assessment Evidence: Accurate probability applications to authentic environmental data Standards Alignment: 6.4.1.2 and 6.4.1.4 applied to scientific contexts Implementation Options: Extended includes partnership with environmental organizations for authentic data
Day 15: Community Survey Design Guiding Question: How can we collect probability data about issues that matter to our community?
Learning Objectives:
Design surveys incorporating probability questions
Plan systematic data collection from community members
Apply probability thinking to social issues and community needs
Activities (50 minutes):
Community Issue Identification (15 min): Brainstorm local issues amenable to probability analysis (transportation, recycling, safety)
Survey Design (25 min): Create surveys with probability-based questions; test for clarity and usefulness
Data Collection Planning (10 min): Plan systematic approach to community data gathering
Materials: Survey design templates, community issue reference materials, data collection planning sheets Assessment Evidence: Well-designed surveys with clear probability applications to community issues Standards Alignment: Real-world application of all probability standards Implementation Options: Extended includes actual community data collection and analysis
WEEK 4: Advanced Applications & Scientific Modeling
Day 16: Complex Sample Spaces & Multi-Step Experiments Guiding Question: How can we analyze probability situations with many possible outcomes?
Learning Objectives (Standards 6.4.1.1 & 6.4.1.2):
Determine sample spaces approaching maximum size (36 outcomes)
Calculate probabilities for complex multi-step experiments
Use systematic organization for large sample spaces
Activities (50 minutes):
Maximum Complexity Challenge (20 min): Work with experiments having sample spaces near 36 (two dice, three coins, etc.)
Organization Strategy Development (20 min): Develop efficient methods for handling large sample spaces without missing outcomes
Probability Calculation Practice (10 min): Calculate probabilities for events within complex sample spaces
Materials: Multiple dice, coins, spinners, large organization charts, systematic counting worksheets Assessment Evidence: Accurate sample space determination and probability calculation for complex experiments Standards Alignment: 6.4.1.1 and 6.4.1.2 at maximum complexity levels specified Implementation Options: Enrichment includes experiments with sample spaces approaching 100
Day 17: Experimental Probability & Large Samples Guiding Question: How does increasing sample size affect the accuracy of experimental probability?
Learning Objectives (Standard 6.4.1.3):
Conduct large-scale probability experiments
Analyze relationship between sample size and experimental accuracy
Compare different experimental approaches for same theoretical probability
Activities (50 minutes):
Small vs. Large Sample Experiments (30 min): Compare results from 10 trials vs. 100 trials of same experiment
Class vs. Individual Results (15 min): Analyze how combining individual results improves experimental accuracy
Sampling Strategy Discussion (5 min): Discuss implications for scientific research and data collection
Materials: Probability tools for large-scale experiments, data compilation sheets, graphing materials Assessment Evidence: Thoughtful analysis of sample size effects with accurate large-scale data collection Standards Alignment: 6.4.1.3 (understanding differences between experimental and theoretical) Implementation Options: Extended includes multi-day experiments tracking convergence to theoretical probability
Day 18: Prediction & Decision Making Guiding Question: How can experimental probability help us make informed predictions and decisions?
Learning Objectives (Standard 6.4.1.4):
Calculate experimental probabilities from authentic datasets
Make predictions based on experimental evidence
Understand limitations and uncertainty in probability-based predictions
Activities (50 minutes):
Authentic Data Analysis (25 min): Analyze real experimental data (sports statistics, weather patterns, scientific studies)
Prediction Development (20 min): Use experimental probabilities to make specific predictions; justify reasoning
Uncertainty Acknowledgment (5 min): Discuss confidence levels and limitations of probability-based predictions
Materials: Authentic experimental datasets, prediction worksheets, scientific examples of probability applications Assessment Evidence: Reasonable predictions based on experimental evidence with appropriate uncertainty acknowledgment Standards Alignment: 6.4.1.4 (Calculate experimental probabilities and make predictions) Implementation Options: Extended includes comparison with professional predictions (weather, sports, medical)
Day 19: Game Design Challenge Guiding Question: How can we create probability-based games that are both fair and engaging?
Learning Objectives:
Apply all probability concepts to game design
Analyze game fairness using mathematical reasoning
Create engaging applications of probability thinking
Activities (50 minutes):
Game Design Planning (20 min): Design probability-based games with specified fairness criteria
Mathematical Analysis (20 min): Calculate theoretical probabilities for game outcomes; verify fairness
Peer Testing & Feedback (10 min): Test games with classmates; collect feedback on engagement and fairness
Materials: Game design materials, probability calculation tools, testing protocols Assessment Evidence: Mathematically sound games with accurate probability analysis and engaging gameplay Standards Alignment: Integrated application of all Grade 6 probability standards Implementation Options: Extended includes business plan development and community game night
Day 20: Technology Integration & Data Visualization Guiding Question: How can digital tools enhance our understanding and communication of probability concepts?
Learning Objectives:
Create sophisticated probability visualizations using technology
Develop digital presentations of probability concepts
Integrate technology skills with mathematical understanding
Activities (50 minutes):
Advanced Spreadsheet Techniques (25 min): Use conditional formatting, advanced formulas, and chart customization for probability data
Digital Presentation Creation (20 min): Begin multimedia presentations combining probability analysis with visual communication
Portfolio Organization (5 min): Organize digital evidence of probability learning for final presentations
Materials: Computers/tablets, advanced spreadsheet tutorials, presentation software, portfolio templates Assessment Evidence: Sophisticated digital presentations demonstrating probability mastery through technology Standards Alignment: Technology integration supporting all probability standards Implementation Options: Extended includes video creation and interactive digital presentations
WEEK 5: Environmental Science Applications & Community Projects
Day 21: Climate Change Probability Analysis Guiding Question: How can probability thinking help us understand and communicate climate risks?
Learning Objectives:
Apply probability concepts to climate science data
Analyze risk and uncertainty in environmental predictions
Connect mathematical thinking to global environmental challenges
Activities (50 minutes):
Climate Data Investigation (25 min): Analyze historical weather data to calculate probabilities of extreme events
Risk Communication Practice (20 min): Practice explaining climate probabilities to different audiences using appropriate language
Local Climate Analysis (5 min): Identify local climate patterns amenable to probability analysis
Materials: Climate datasets, risk communication guides, local weather data Assessment Evidence: Accurate probability analysis of climate data with effective risk communication Standards Alignment: 6.4.1.2 and 6.4.1.4 applied to environmental science Implementation Options: Extended includes partnership with climate scientists for authentic data analysis
Day 22: Conservation Success Probabilities Guiding Question: How do conservation biologists use probability to protect endangered species?
Learning Objectives:
Calculate survival and recovery probabilities for wildlife populations
Analyze conservation program effectiveness using probability data
Connect probability thinking to biodiversity protection
Activities (50 minutes):
Species Recovery Analysis (30 min): Use authentic conservation data to calculate species survival and recovery probabilities
Conservation Strategy Evaluation (15 min): Compare different conservation approaches using probability-based evidence
Local Wildlife Investigation (5 min): Identify local conservation efforts amenable to probability analysis
Materials: Conservation organization datasets, species recovery data, local wildlife information Assessment Evidence: Mathematical analysis supporting conservation conclusions with probability-based reasoning Standards Alignment: 6.4.1.4 (using experimental probabilities for prediction in authentic contexts) Implementation Options: Extended includes partnership with local wildlife organizations
Day 23: Community Data Collection Project Guiding Question: How can we use probability thinking to understand and improve our local community?
Learning Objectives:
Implement community survey with probability applications
Collect and analyze data about local issues using probability concepts
Apply mathematical thinking to civic engagement
Activities (50 minutes):
Survey Implementation (30 min): Conduct planned community surveys; ensure systematic data collection
Initial Data Analysis (15 min): Begin calculating experimental probabilities from community responses
Pattern Identification (5 min): Identify interesting patterns requiring further analysis or community attention
Materials: Community surveys, data collection materials, initial analysis worksheets Assessment Evidence: Systematic community data collection with accurate initial probability analysis Standards Alignment: Real-world application of all probability standards in community context Implementation Options: Extended includes presentation to community leaders and follow-up analysis
Day 24: Scientific Method & Probability Guiding Question: How do scientists use probability thinking in experimental design and data interpretation?
Learning Objectives:
Connect probability concepts to scientific experimental design
Understand role of uncertainty and prediction in scientific research
Apply probability thinking to student-designed experiments
Activities (50 minutes):
Scientific Experiment Analysis (25 min): Examine real scientific studies using probability in experimental design and interpretation
Student Experiment Design (20 min): Design simple experiments incorporating probability thinking and prediction
Uncertainty Discussion (5 min): Discuss how scientists communicate uncertainty and probability in research findings
Materials: Scientific study examples, experiment design templates, uncertainty communication guides Assessment Evidence: Understanding of probability's role in scientific method with well-designed experimental plans Standards Alignment: 6.4.1.3 and 6.4.1.4 applied to scientific methodology Implementation Options: Extended includes implementation of student-designed experiments
Day 25: Data Storytelling & Community Presentation Preparation Guiding Question: How can we tell compelling stories about probability that engage and educate our community?
Learning Objectives:
Structure probability findings into narrative formats
Prepare interactive presentations for community audiences
Balance mathematical accuracy with accessible communication
Activities (50 minutes):
Story Structure Development (25 min): Organize probability findings into compelling narratives with clear beginning-middle-end structure
Interactive Element Planning (20 min): Plan hands-on probability activities for community presentation visitors
Presentation Rehearsal (5 min): Practice explaining probability concepts to different audience types
Materials: Story planning templates, presentation materials, interactive activity supplies Assessment Evidence: Clear narratives incorporating accurate probability content with engaging interactive elements Standards Alignment: Communication of all probability standards to authentic audiences Implementation Options: Extended includes professional presentation coaching and community venue coordination
WEEK 6: Community Exhibition & Reflection
Day 26: Exhibition Preparation - Mathematical Accuracy Verification Guiding Question: How can we ensure our probability presentations are mathematically accurate and educationally effective?
Learning Objectives:
Verify all probability calculations and experimental results
Prepare for challenging mathematical questions from community visitors
Develop confidence in probability reasoning and explanation
Activities (50 minutes):
Mathematical Content Review (30 min): Systematically verify all sample space determinations, probability calculations, and experimental analyses
Question Preparation (15 min): Anticipate challenging questions about probability concepts; prepare evidence-based responses
Peer Mathematical Review (5 min): Review classmates' mathematical content for accuracy and clarity
Materials: Mathematical verification checklists, question preparation guides, peer review protocols Assessment Evidence: Mathematically accurate presentations with prepared responses to probability questions Standards Alignment: Demonstration of mastery for all Grade 6 probability standards Implementation Options: Extended includes consultation with mathematical mentors for advanced question preparation
Day 27: Exhibition Preparation - Community Engagement Planning Guiding Question: How can we adapt our probability explanations for diverse community audiences?
Learning Objectives:
Practice explaining probability concepts to different audiences
Prepare accessible explanations without sacrificing mathematical accuracy
Develop skills for engaging community members in mathematical thinking
Activities (50 minutes):
Audience Adaptation Practice (30 min): Practice explaining same probability concepts to younger students, parents, and community leaders
Engagement Strategy Development (15 min): Plan strategies for making probability concepts interactive and accessible
Final Presentation Rehearsal (5 min): Rehearse complete presentations with audience-appropriate adaptations
Materials: Audience adaptation guides, engagement strategy templates, rehearsal feedback forms Assessment Evidence: Clear mathematical communication adapted appropriately for diverse community audiences Standards Alignment: Communication of probability standards to authentic audiences Implementation Options: Extended includes training in facilitating mathematical conversations with adults
Day 28: Community Probability Exhibition - Day 1 Guiding Question: How effectively can we teach our community about probability using mathematical evidence and creative communication?
Learning Objectives:
Present probability findings to authentic community audiences
Facilitate interactive probability learning experiences
Demonstrate mastery of Grade 6 probability standards through teaching
Activities (50 minutes):
Interactive Exhibition Facilitation (40 min): Students guide community visitors through probability demonstrations; provide mathematical explanations and facilitate hands-on activities
Real-Time Adaptation (8 min): Adjust presentations based on visitor questions and engagement levels
Reflection Documentation (2 min): Quick documentation of visitor interactions and mathematical questions
Materials: All exhibition materials, visitor feedback forms, documentation tools Assessment Evidence: Successful community education with accurate mathematical content delivery and responsive engagement Standards Alignment: Authentic demonstration of complete Grade 6 probability mastery Implementation Options: Extended includes multiple presentation sessions and community feedback analysis
Day 29: Community Probability Exhibition - Day 2 & Feedback Analysis Guiding Question: How can community feedback help us understand the effectiveness of our mathematical communication?
Learning Objectives:
Continue community education through probability presentations
Collect and analyze feedback about mathematical presentation effectiveness
Reflect on growth in probability understanding and communication skills
Activities (50 minutes):
Extended Community Presentations (35 min): Continue interactive exhibitions incorporating lessons learned from Day 1
Feedback Collection & Analysis (10 min): Systematically gather and analyze visitor feedback about presentation effectiveness
Initial Reflection (5 min): Begin reflecting on personal growth in probability understanding and mathematical communication
Materials: Presentation materials, feedback analysis tools, reflection prompts Assessment Evidence: Improved presentation delivery and thoughtful analysis of community engagement effectiveness Standards Alignment: Continued demonstration of probability mastery with reflective improvement Implementation Options: Extended includes follow-up community surveys and presentation refinement
Day 30: Unit Reflection & Future Connections Guiding Question: How has learning about probability changed our understanding of mathematics, science, and community engagement?
Learning Objectives:
Reflect comprehensively on probability learning growth
Identify connections between probability thinking and future mathematical study
Set goals for continued mathematical development and community engagement
Activities (50 minutes):
Learning Portfolio Completion (25 min): Compile comprehensive evidence of probability learning growth; write reflective analysis of mathematical development
Cross-Curricular Connections Identification (15 min): Identify applications of probability thinking to science, social studies, art, and civic participation
Grade 7 Goal Setting (10 min): Preview upcoming statistical concepts; set specific goals for continued mathematical and community engagement growth
Materials: Portfolio compilation materials, reflection templates, Grade 7 preview materials, goal-setting guides Assessment Evidence: Thoughtful reflection demonstrating understanding of probability growth and future mathematical applications Standards Alignment: Comprehensive reflection on mastery of all Grade 6 probability standards with future learning connections Implementation Options: Extended includes family sharing of learning portfolio and goal-setting conferences
Chromebooks/tablets (1:1 ratio preferred, minimum 1:2 ratio)
Google Sheets access with tutorial support for probability calculations
Internet connectivity for data pioneer research and authentic dataset access
Presentation equipment for community exhibition (projectors, extension cords, microphones)
Probability manipulatives: coins, dice (multiple types), spinners, colored chips, playing cards
Mathematical tools: calculators, rulers, graph paper, colored pencils, chart paper, protractors
Art supplies: traditional materials for cultural integration projects, fabric scraps for quilting mathematics
Organization materials: index cards, poster boards, markers, tape, scissors
Traditional art examples: Aboriginal dot paintings, Islamic geometric patterns, African textile designs, quilting patterns
Historical reproductions: Minard's Napoleon map, Snow's cholera map, early statistical graphics
Contemporary art prints: Aaron Koblin's "Flight Patterns," Chris Jordan's "Running the Numbers" series
Environmental organizations: for authentic climate and conservation data
Health departments: for epidemiology and public health data applications
Local artists: for consultation on data visualization and cultural art integration
Community venues: for authentic audience presentation opportunities
Standard 6.4.1.1: Sample Space Determination
Exceeds: Determines sample spaces for complex experiments (approaching 36 outcomes); creates sophisticated organizational systems using multiple representation methods
Meets: Accurately determines sample spaces using tree diagrams, tables, and pictorial representations; identifies which outcomes relate to specific events
Approaching: Determines sample spaces for simple experiments with support; uses basic organizational methods
Beginning: Attempts sample space determination with extensive guidance; limited understanding of systematic organization
Standard 6.4.1.2: Probability Calculation
Exceeds: Fluently calculates probabilities for complex scenarios (sample spaces approaching 100); converts seamlessly between fractions, decimals, and percents with appropriate audience adaptation
Meets: Accurately calculates probability using ratios; represents as fractions, decimals, and percents; understands likelihood vocabulary
Approaching: Calculates basic probabilities with support; converts between some representations; uses likelihood vocabulary with prompting
Beginning: Attempts probability calculations with extensive support; limited understanding of ratio relationships and likelihood
Standard 6.4.1.3: Experimental vs. Theoretical Probability
Exceeds: Designs sophisticated experiments; analyzes relationships between sample size and accuracy; explains variability with statistical reasoning
Meets: Performs experiments comparing theoretical and experimental probability; understands and explains why differences occur
Approaching: Conducts basic experiments with support; recognizes differences between theoretical and experimental results
Beginning: Attempts experimental work with guidance; limited understanding of theoretical-experimental relationships
Standard 6.4.1.4: Experimental Probability & Prediction
Exceeds: Calculates experimental probabilities from complex datasets; makes sophisticated predictions with uncertainty acknowledgment; applies to authentic scenarios
Meets: Calculates experimental probabilities; makes reasonable predictions when theoretical probabilities unknown; represents in multiple forms
Approaching: Calculates basic experimental probabilities with support; makes simple predictions with guidance
Beginning: Attempts experimental probability calculation with extensive support; limited prediction-making ability
Understanding:
Students demonstrate deep conceptual understanding of probability through multiple mathematical representations
Students explain probability reasoning clearly using precise mathematical vocabulary
Students connect probability thinking to scientific, artistic, and community applications
Inquiry:
Students formulate meaningful questions answerable through probability analysis
Students design appropriate experimental methods and data collection procedures
Students pursue independent investigations extending beyond lesson requirements
Communication:
Students explain probability concepts accurately to diverse audiences using appropriate vocabulary
Students integrate mathematical precision with artistic and narrative communication
Students facilitate interactive learning experiences for community members
Reflection:
Students analyze their growth in probability understanding and mathematical communication
Students identify connections between probability concepts and real-world applications
Students set goals for continued mathematical development and community engagement
Complex probability scenarios with sample spaces approaching maximum specifications (100 outcomes)
Leadership roles in peer teaching and community presentation facilitation
Independent research projects investigating additional data pioneers or contemporary applications
Advanced technology integration including programming and simulation tools
Manipulative support for all probability calculations with gradual progression to abstract thinking
Simplified experiments with smaller sample spaces and clear patterns
Visual organization supports including graphic organizers and step-by-step templates
Partner collaboration with structured roles and individual accountability measures
Bilingual probability vocabulary cards with visual representations and translations
Cultural mathematics connections highlighting probability traditions from students' home cultures
Collaborative grouping with strategic language support partnerships
Multiple representation options allowing demonstration of understanding through various modalities
Extended time for complex probability calculations with alternative assessment formats
Assistive technology for data organization and calculation support
Multiple intelligence approaches incorporating kinesthetic, visual, and auditory learning preferences
Choice in presentation formats maintaining mathematical rigor while accommodating individual strengths
Minnesota Grade 6 probability standards mastery with specific attention to sample space limitations and vocabulary requirements
IB PYP methodology training focusing on inquiry-based learning and transdisciplinary theme integration
Google Sheets proficiency for supporting student technology integration and data analysis
Cultural competency development for respectful integration of diverse mathematical traditions
Cross-curricular team coordination ensuring authentic STEAM integration rather than forced connections
Community partnership development establishing sustainable relationships with local organizations
Assessment calibration sessions ensuring consistent evaluation across different implementation levels
Student learning progression analysis using data to refine instructional approaches
Month 1: Establish community partnerships, curate age-appropriate datasets, prepare cultural art materials
Month 2: Train peer feedback protocols, test technology systems, prepare family engagement opportunities
Month 3: Implement unit with ongoing formative assessment and instructional adjustment
Month 4: Analyze student outcomes, document effective practices, plan improvements for future iterations
Probability game nights featuring student-designed games during Week 4
Cultural mathematics sharing inviting families to contribute traditional pattern-making knowledge
Community exhibition attendance providing authentic audiences for student probability presentations
Home probability investigations extending mathematical thinking into family contexts
Weekly probability newsletters explaining concepts being learned with home extension suggestions
Digital portfolio sharing allowing families to see mathematical growth and development
Family math vocabulary support providing translations and visual supports for probability terminology
Grade 7 transition preparation helping families understand upcoming mathematical expectations
Students will enter Grade 7 with strong foundations in:
Sample space determination supporting advanced counting principles and complex probability
Experimental probability experience enabling sophisticated data collection and analysis
Mathematical communication skills facilitating collaborative learning and peer explanation
Real-world application experience connecting probability to scientific and social contexts
Science: Experimental design, data analysis, scientific method applications
Social Studies: Statistical analysis of demographic data, historical pattern investigation
Language Arts: Data storytelling, research presentation, critical analysis of statistical claims
Arts: Continued data visualization, mathematical art creation, cultural pattern exploration
Environmental advocacy using probability analysis for local conservation and climate issues
Civic engagement preparation developing skills for evidence-based community participation
Mathematical literacy development building foundation for informed democratic participation
Cultural bridge-building connecting mathematical learning with diverse community traditions
This comprehensive Grade 6 unit provides students with essential probability foundations while engaging them in authentic, inquiry-based learning connecting to community needs and cultural traditions. The flexible implementation structure allows teachers to adapt the unit to various time constraints while ensuring all students master Grade 6 probability standards through meaningful, integrated STEAM experiences that prepare them for advanced mathematical thinking and engaged citizenship.