diff --git a/research/activity42-game-theory-201.yaml b/research/activity42-game-theory-201.yaml
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+default_max_attempts_per_step: 3
+classifier_model: "MODEL_1"
+feedback_model: "MODEL_1"
+sections:
+  - section_id: introduction
+    title: Welcome to Game Theory 201
+    steps:
+      - step_id: welcome
+        title: Beyond Pure Strategies
+        content_blocks:
+          - "# Game Theory 201: Mixed Strategies & Repeated Games 🎲🔄"
+          - "**Building on Game Theory 101!**"
+          - ""
+          - "**You'll learn:**"
+          - "✓ Mixed strategies (randomization)"
+          - "✓ When and why to randomize"
+          - "✓ Repeated games (shadow of the future)"
+          - "✓ How cooperation emerges"
+          - "✓ Tit-for-Tat and winning strategies"
+        question: Ready to explore more advanced strategic concepts?
+        tokens_for_ai: Accept positive as 'ready', language as 'set_language', else 'off_topic'
+        buckets: [ready, set_language, off_topic]
+        transitions:
+          ready:
+            next_section_and_step: mixed_strategies:step_1
+          set_language:
+            metadata_add: {language: "the-users-response"}
+            counts_as_attempt: false
+            next_section_and_step: introduction:welcome
+          off_topic:
+            counts_as_attempt: false
+            next_section_and_step: introduction:welcome
+  
+  - section_id: mixed_strategies
+    title: Mixed Strategies  
+    steps:
+      - step_id: step_1
+        title: Randomization as Strategy
+        content_blocks:
+          - "## Mixed Strategies: The Power of Unpredictability 🎲"
+          - ""
+          - "**Pure vs Mixed Strategies:**"
+          - "- Pure: Always play the same action"
+          - "- Mixed: Randomize between actions with specific probabilities"
+          - ""
+          - "**Rock-Paper-Scissors:**"
+          - "No pure strategy works - opponent can exploit patterns!"
+          - "Solution: Randomize equally (1/3, 1/3, 1/3)"
+          - ""
+          - "**Penalty Kicks in Soccer:**"
+          - "- Kicker: Left or Right?"
+          - "- Goalie: Dive Left or Right?"
+          - "- Must be unpredictable!"
+          - "- Data shows pros randomize ~50/50"
+          - ""
+          - "**When to use mixed strategies:**"
+          - "- No dominant pure strategy"
+          - "- Opponent can exploit predictability"
+          - "- Matching Pennies, Hide and Seek, Security games"
+        question: In Rock-Paper-Scissors, why can't you always play Rock? What happens if you're predictable?
+        tokens_for_ai: |
+          Should recognize: predictability allows exploitation.
+          If always Rock, opponent plays Paper and wins.
+          Categorize: understands_exploitation, recognizes_problem, vague, set_language, off_topic
+        buckets: [understands_exploitation, recognizes_problem, vague, set_language, off_topic]
+        transitions:
+          understands_exploitation:
+            ai_feedback: {tokens_for_ai: "Perfect! Predictability = exploitation. Opponent plays Paper, you lose. Randomization prevents exploitation!"}
+            metadata_add: {score: "n+2"}
+            next_section_and_step: repeated_games:step_1
+          recognizes_problem:
+            ai_feedback: {tokens_for_ai: "Right! If you always play Rock, smart opponent plays Paper every time. Randomization is the solution!"}
+            metadata_add: {score: "n+1"}
+            next_section_and_step: repeated_games:step_1
+          vague:
+            ai_feedback: {tokens_for_ai: "If you always play Rock, opponent learns and always plays Paper. You lose every time! Must randomize."}
+            next_section_and_step: repeated_games:step_1
+          set_language:
+            metadata_add: {language: "the-users-response"}
+            counts_as_attempt: false
+            next_section_and_step: mixed_strategies:step_1
+          off_topic:
+            next_section_and_step: mixed_strategies:step_1
+  
+  - section_id: repeated_games
+    title: Repeated Games
+    steps:
+      - step_id: step_1
+        title: The Shadow of the Future
+        content_blocks:
+          - "## Repeated Games: When Tomorrow Matters 🔄"
+          - ""
+          - "**One-shot vs Repeated:**"
+          - "- One-shot PD: Defect dominates"
+          - "- Repeated PD: Cooperation can emerge!"
+          - ""
+          - "**Why repetition changes everything:**"
+          - "- Reputation matters"
+          - "- Retaliation is possible"
+          - "- Future gains can outweigh immediate temptation"
+          - ""
+          - "**Tit-for-Tat Strategy:**"
+          - "1. Start with cooperation"
+          - "2. Then copy opponent's previous move"
+          - "- Nice (never defects first)"
+          - "- Retaliatory (punishes defection)"
+          - "- Forgiving (returns to cooperation)"
+          - "- Clear (easy to understand)"
+          - ""
+          - "**Axelrod's Tournament:**"
+          - "Tit-for-Tat won! Simplest, most effective."
+          - "Beat complex strategies through cooperation + accountability"
+        question: Why can cooperation emerge in repeated Prisoner's Dilemma but not in one-shot games?
+        tokens_for_ai: |
+          Key insight: future interactions create incentive to cooperate.
+          Fear of retaliation, value of reputation, shadow of future.
+          Categorize: excellent_understanding, identifies_repetition, partial, set_language, off_topic
+        buckets: [excellent_understanding, identifies_repetition, partial, set_language, off_topic]
+        transitions:
+          excellent_understanding:
+            ai_feedback: {tokens_for_ai: "Brilliant! Future interactions change incentives. Retaliation possible, reputation matters. Short-term gain < long-term cooperation!"}
+            metadata_add: {score: "n+2", activity_completed: "true"}
+          identifies_repetition:
+            ai_feedback: {tokens_for_ai: "Exactly! Repeated games allow punishment and reward. Cooperation becomes rational when future matters!"}
+            metadata_add: {score: "n+1", activity_completed: "true"}
+          partial:
+            ai_feedback: {tokens_for_ai: "Right direction! Key: future interactions create accountability. Can punish defectors, reward cooperators. Changes incentives!"}
+            metadata_add: {activity_completed: "true"}
+          set_language:
+            metadata_add: {language: "the-users-response"}
+            counts_as_attempt: false
+            next_section_and_step: repeated_games:step_1
+          off_topic:
+            metadata_add: {activity_completed: "true"}
diff --git a/research/activity43-game-theory-301.yaml b/research/activity43-game-theory-301.yaml
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+default_max_attempts_per_step: 3
+sections:
+  - section_id: introduction
+    title: Game Theory 301
+    steps:
+      - step_id: welcome
+        title: Cooperative Games
+        content_blocks:
+          - "# Game Theory 301: Cooperative Games & Coalitions 🤝"
+          - "**Beyond zero-sum thinking!**"
+          - "✓ Cooperative game theory"
+          - "✓ Coalition formation"
+          - "✓ Shapley value (fair division)"
+          - "✓ Core stability"
+        question: Ready to learn about cooperation and coalition building?
+        tokens_for_ai: Accept positive as 'ready', else 'off_topic'
+        buckets: [ready, set_language, off_topic]
+        transitions:
+          ready: {next_section_and_step: "coalitions:step_1"}
+          set_language: {metadata_add: {language: "the-users-response"}, counts_as_attempt: false, next_section_and_step: "introduction:welcome"}
+          off_topic: {counts_as_attempt: false, next_section_and_step: "introduction:welcome"}
+  
+  - section_id: coalitions
+    title: Coalition Formation
+    steps:
+      - step_id: step_1
+        title: Coalition Building
+        content_blocks:
+          - "## Coalitions: Strength in Numbers 💪"
+          - ""
+          - "**Characteristic function form:**"
+          - "v(Coalition) = value coalition can guarantee"
+          - ""
+          - "**Example: Three companies**"
+          - "- Alone: A=$10M, B=$15M, C=$20M"
+          - "- A+B together: $30M"
+          - "- A+C together: $35M"  
+          - "- B+C together: $40M"
+          - "- All three: $60M"
+          - ""
+          - "**Questions:**"
+          - "- Which coalition forms?"
+          - "- How to split the gains fairly?"
+          - ""
+          - "**Shapley Value:**"
+          - "Fair division based on marginal contributions"
+          - "Each player gets average of their marginal value across all orderings"
+        question: If three players create $60M together but would create $0 individually, how should they split the gains to be fair?
+        tokens_for_ai: |
+          Equal split ($20M each) is one fair answer.
+          Shapley value would calculate based on marginal contributions.
+          Categorize: says_equal, considers_contributions, unclear, set_language, off_topic
+        buckets: [says_equal, considers_contributions, unclear, set_language, off_topic]
+        transitions:
+          says_equal:
+            ai_feedback: {tokens_for_ai: "Equal split is fair! Each contributed equally to coalition. Shapley value would give $20M each too."}
+            metadata_add: {score: "n+2", activity_completed: "true"}
+          considers_contributions:
+            ai_feedback: {tokens_for_ai: "Good thinking about contributions! With symmetric players, equal split is the Shapley value."}
+            metadata_add: {score: "n+1", activity_completed: "true"}
+          unclear:
+            ai_feedback: {tokens_for_ai: "Fair approach: equal split since all contributed equally. Each gets $20M. This is the Shapley value!"}
+            metadata_add: {activity_completed: "true"}
+          set_language: {metadata_add: {language: "the-users-response"}, counts_as_attempt: false, next_section_and_step: "coalitions:step_1"}
+          off_topic: {metadata_add: {activity_completed: "true"}}
diff --git a/research/activity44-game-theory-401.yaml b/research/activity44-game-theory-401.yaml
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+++ b/research/activity44-game-theory-401.yaml
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+default_max_attempts_per_step: 3
+sections:
+  - section_id: introduction
+    title: Game Theory 401
+    steps:
+      - step_id: welcome
+        title: Information Games
+        content_blocks:
+          - "# Game Theory 401: Information Asymmetry 🔍"
+          - "**When players have different information!**"
+          - "✓ Signaling (revealing information)"
+          - "✓ Screening (eliciting information)"
+          - "✓ Adverse selection"
+          - "✓ Moral hazard"
+        question: Ready to explore strategic information problems?
+        tokens_for_ai: Accept positive as 'ready', else 'off_topic'
+        buckets: [ready, set_language, off_topic]
+        transitions:
+          ready: {next_section_and_step: "signaling:step_1"}
+          set_language: {metadata_add: {language: "the-users-response"}, counts_as_attempt: false, next_section_and_step: "introduction:welcome"}
+          off_topic: {counts_as_attempt: false, next_section_and_step: "introduction:welcome"}
+  
+  - section_id: signaling
+    title: Signaling & Screening
+    steps:
+      - step_id: step_1
+        title: Credible Signals
+        content_blocks:
+          - "## Signaling: Credibly Revealing Information 📢"
+          - ""
+          - "**The problem:**"
+          - "You have valuable information others don't"
+          - "How to credibly communicate it?"
+          - ""
+          - "**Education as Signal:**"
+          - "- Degree signals ability/work ethic"
+          - "- Costly to obtain (time, money, effort)"
+          - "- Harder for low-ability workers"
+          - "- Separates high from low types"
+          - ""
+          - "**Key: Must be costly for low types!**"
+          - "Otherwise everyone signals, signal loses meaning"
+          - ""
+          - "**Other examples:**"
+          - "- Warranties (signal quality)"
+          - "- Money-back guarantees"
+          - "- Certifications"
+          - "- Peacock's tail (biological signaling)"
+          - ""
+          - "**Adverse Selection:**"
+          - "When information asymmetry leads to market failure"
+          - "Example: Used car market (lemons problem)"
+        question: Why must a signal be costly to be credible? What happens if it's cheap for everyone?
+        tokens_for_ai: |
+          Key insight: if signal is cheap for all types, everyone signals.
+          Signal loses informational value (pooling).
+          Must be differentially costly to separate types.
+          Categorize: excellent_understanding, understands_cost, partial, set_language, off_topic
+        buckets: [excellent_understanding, understands_cost, partial, set_language, off_topic]
+        transitions:
+          excellent_understanding:
+            ai_feedback: {tokens_for_ai: "Perfect! If everyone can signal cheaply, everyone does. Signal becomes meaningless. Must be differentially costly to separate types!"}
+            metadata_add: {score: "n+2", activity_completed: "true"}
+          understands_cost:
+            ai_feedback: {tokens_for_ai: "Exactly! Cheap signals lose meaning. Everyone would claim to be high quality. Cost creates separation!"}
+            metadata_add: {score: "n+1", activity_completed: "true"}
+          partial:
+            ai_feedback: {tokens_for_ai: "Right direction! If signal is free, everyone sends it. Becomes noise. Cost differentiates high from low quality!"}
+            metadata_add: {activity_completed: "true"}
+          set_language: {metadata_add: {language: "the-users-response"}, counts_as_attempt: false, next_section_and_step: "signaling:step_1"}
+          off_topic: {metadata_add: {activity_completed: "true"}}
diff --git a/research/activity45-game-theory-501.yaml b/research/activity45-game-theory-501.yaml
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--- /dev/null
+++ b/research/activity45-game-theory-501.yaml
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+default_max_attempts_per_step: 3
+sections:
+  - section_id: introduction
+    title: Game Theory 501
+    steps:
+      - step_id: welcome
+        title: Design the Game
+        content_blocks:
+          - "# Game Theory 501: Mechanism Design 🏗️"
+          - "**Reverse game theory: Design the game itself!**"
+          - "✓ Mechanism design (reverse game theory)"
+          - "✓ Auction theory"
+          - "✓ Voting theory"
+          - "✓ Incentive compatibility"
+        question: Ready to learn how to design strategic systems?
+        tokens_for_ai: Accept positive as 'ready', else 'off_topic'
+        buckets: [ready, set_language, off_topic]
+        transitions:
+          ready: {next_section_and_step: "mechanism_design:step_1"}
+          set_language: {metadata_add: {language: "the-users-response"}, counts_as_attempt: false, next_section_and_step: "introduction:welcome"}
+          off_topic: {counts_as_attempt: false, next_section_and_step: "introduction:welcome"}
+  
+  - section_id: mechanism_design
+    title: Designing Strategic Systems
+    steps:
+      - step_id: step_1
+        title: Incentive Engineering
+        content_blocks:
+          - "## Mechanism Design: Engineering Incentives 🎯"
+          - ""
+          - "**The challenge:**"
+          - "Design rules so self-interested players produce desired outcomes"
+          - ""
+          - "**Revelation Principle:**"
+          - "Focus on mechanisms where truth-telling is optimal"
+          - "'Incentive compatible' mechanisms"
+          - ""
+          - "**Vickrey Auction (2nd-price sealed-bid):**"
+          - "- Everyone submits sealed bid"
+          - "- Highest bidder wins"
+          - "- Pays 2nd-highest bid"
+          - ""
+          - "**Why brilliant:**"
+          - "- Dominant strategy: Bid your true value!"
+          - "- Overbidding risks paying too much"
+          - "- Underbidding risks losing when you'd profit"
+          - "- Truthful bidding is optimal"
+          - ""
+          - "**Applications:**"
+          - "- eBay (proxy bidding)"
+          - "- Google AdWords"
+          - "- Organ donation matching"
+          - "- Spectrum auctions"
+        question: In a Vickrey auction, why is bidding your true value the dominant strategy?
+        tokens_for_ai: |
+          Key insight: You pay 2nd price, not your bid.
+          Overbidding risks paying more than value.
+          Underbidding risks losing profitable wins.
+          True value bidding is optimal.
+          Categorize: excellent_explanation, understands_truthful, partial, set_language, off_topic
+        buckets: [excellent_explanation, understands_truthful, partial, set_language, off_topic]
+        transitions:
+          excellent_explanation:
+            ai_feedback: {tokens_for_ai: "Perfect! Since you pay 2nd price, not your bid, bidding true value is dominant. Can't improve by lying! This is mechanism design genius!"}
+            metadata_add: {score: "n+2", activity_completed: "true"}
+          understands_truthful:
+            ai_feedback: {tokens_for_ai: "Exactly! Paying 2nd price means truthful bidding is optimal. Over/under bidding can only hurt you. Brilliant design!"}
+            metadata_add: {score: "n+1", activity_completed: "true"}
+          partial:
+            ai_feedback: {tokens_for_ai: "Right idea! Key: you pay 2nd price. Bidding true value dominates - lying can't help, might hurt. This is mechanism design!"}
+            metadata_add: {activity_completed: "true"}
+          set_language: {metadata_add: {language: "the-users-response"}, counts_as_attempt: false, next_section_and_step: "mechanism_design:step_1"}
+          off_topic: {metadata_add: {activity_completed: "true"}}