SYSI 1004 · Perception, Learning, and Cognition in Systems

Led by Lev Vygotsky Simulacrum

Perception and learning in systems from Gibson's ecological approach and Vygotsky's zone of proximal development through distributed cognition, situated learning, and AI-augmented cognition.

1. Module 1

   Gibson's Ecological Perception: Affordances and Direct Perception

   Led by Lev Vygotsky Simulacrum

   The question

   Gibson's Ecological Perception: Affordances and Direct Perception: this module examines the concept in its full depth, drawing on the theoretical foundations, empirical evidence, and practical applications relevant to systems intelligence in the AI age.

   Outcome

   The student can describe, explain, and apply the key concepts of this module to real-world systems design challenges. (Gibson's Ecological Perception)

   Sub-units

   1. ○ 1.1 The Ecological Approach: Perception as Detection of Information in the Environment Open this unit → ✓ ↻
   2. ○ 1.2 Affordances: Opportunities for Action That the Environment Offers Open this unit → ✓ ↻
   3. ○ 1.3 Direct Perception: No Representation Required Open this unit → ✓ ↻
   4. ○ 1.4 Optic Flow and Invariants: How the Moving Organism Perceives the World Open this unit → ✓ ↻
   5. ○ 1.5 Affordances in Design: From Door Handles to Digital Interfaces Open this unit → ✓ ↻
   Begin the course → Print certificate of completion
2. Module 2

   Vygotsky's Zone of Proximal Development: Learning as Social Interaction

   Led by Lev Vygotsky Simulacrum

   The question

   Vygotsky's Zone of Proximal Development: Learning as Social Interaction: this module examines the concept in its full depth, drawing on the theoretical foundations, empirical evidence, and practical applications relevant to systems intelligence in the AI age.

   Outcome

   The student can describe, explain, and apply the key concepts of this module to real-world systems design challenges. (Vygotsky's Zone of Proximal Development)

   Sub-units

   1. ○ 2.1 The ZPD: What the Learner Can Do With Help That They Cannot Do Alone Open this unit → ✓ ↻
   2. ○ 2.2 Scaffolding: The Structure That Supports Learning and Is Gradually Removed Open this unit → ✓ ↻
   3. ○ 2.3 Internalisation: From Social Interaction to Individual Capacity Open this unit → ✓ ↻
   4. ○ 2.4 The More Knowledgeable Other: The Role of the Teacher, the Peer, and the Tool Open this unit → ✓ ↻
   5. ○ 2.5 AI as Scaffolding: How Intelligent Tutoring Systems Implement the ZPD Open this unit → ✓ ↻
   Open this module → Print certificate of completion
3. Module 3

   Distributed Cognition: Intelligence Across Brain, Body, and World

   Led by Lev Vygotsky Simulacrum

   The question

   Distributed Cognition: Intelligence Across Brain, Body, and World: this module examines the concept in its full depth, drawing on the theoretical foundations, empirical evidence, and practical applications relevant to systems intelligence in the AI age.

   Outcome

   The student can describe, explain, and apply the key concepts of this module to real-world systems design challenges. (Distributed Cognition)

   Sub-units

   1. ○ 3.1 Hutchins and the Ship: Cognition Is Not in the Head Open this unit → ✓ ↻
   2. ○ 3.2 The Cognitive Artefact: How Tools Extend and Reshape Thought Open this unit → ✓ ↻
   3. ○ 3.3 Socially Distributed Cognition: Teams Think Together Open this unit → ✓ ↻
   4. ○ 3.4 The Cockpit as a Cognitive System: Human-Machine Ensembles Open this unit → ✓ ↻
   5. ○ 3.5 AI as a Cognitive Partner: Extending Human Thought Through Machine Collaboration Open this unit → ✓ ↻
   Open this module → Print certificate of completion
4. Module 4

   Situated Learning: Knowledge Is Inseparable from Context

   Led by Lev Vygotsky Simulacrum

   The question

   Situated Learning: Knowledge Is Inseparable from Context: this module examines the concept in its full depth, drawing on the theoretical foundations, empirical evidence, and practical applications relevant to systems intelligence in the AI age.

   Outcome

   The student can describe, explain, and apply the key concepts of this module to real-world systems design challenges. (Situated Learning)

   Sub-units

   1. ○ 4.1 Lave and Wenger: Legitimate Peripheral Participation Open this unit → ✓ ↻
   2. ○ 4.2 Communities of Practice: Learning by Joining, Not by Being Taught Open this unit → ✓ ↻
   3. ○ 4.3 Transfer: Why Knowledge Learned in One Context Often Fails in Another Open this unit → ✓ ↻
   4. ○ 4.4 The Apprenticeship Model: Learning by Doing Under Guidance Open this unit → ✓ ↻
   5. ○ 4.5 Situated AI: Why Context Matters for Machine Learning Too Open this unit → ✓ ↻
   Open this module → Print certificate of completion
5. Module 5

   Designing for Human-AI Cognitive Partnership

   Led by Lev Vygotsky Simulacrum

   The question

   Designing for Human-AI Cognitive Partnership: this module examines the concept in its full depth, drawing on the theoretical foundations, empirical evidence, and practical applications relevant to systems intelligence in the AI age.

   Outcome

   The student can describe, explain, and apply the key concepts of this module to real-world systems design challenges. (Designing for Human-AI Cognitive Partnership)

   Sub-units

   1. ○ 5.1 Complementary Intelligence: Where Humans Excel and Where Machines Excel Open this unit → ✓ ↻
   2. ○ 5.2 Cognitive Load: How AI Can Reduce or Increase the Burden on Human Thought Open this unit → ✓ ↻
   3. ○ 5.3 Decision Support vs. Decision Making: When the AI Recommends and When It Decides Open this unit → ✓ ↻
   4. ○ 5.4 Explainable AI as Cognitive Partnership: Understanding Why the Machine Suggests What It Suggests Open this unit → ✓ ↻
   5. ○ 5.5 The Future of Augmented Cognition: Thinking With, Not Against, the Machine Open this unit → ✓ ↻
   Open this module → Print certificate of completion