Launching Day 2 as an intensive, collaborative team challenge. Rather than building utility bots that automate away human effort, student trios design a domain-specific Socratic Learning Companion — an interactive guide for environmental science, math, or history — that implements intentional cognitive scaffolding to accelerate human critical thinking.
Your companion must guide users with conceptual hints, analogies, and reflective questions — supporting active learning, protecting human competence, and fostering independent, critical thinking.
System instructions programme the bot to analyse user inputs and return structured hints, reflective analogies, and guiding questions rather than direct, transactional answers.
Intentional cognitive scaffolding prevents user deskilling — building conceptual mastery, analytical stamina, and self-regulated learning habits over time.
The companion self-identifies as an AI, maintains objective non-anthropomorphic language, and defers all key choices to the human learner.
Teams ingest pre-curated Theme Data Packs into Gemini Notebook. Using semantic search and synthesis, they map data limitations, identify historical representation patterns, and structure their core research questions — then author the bot's Value-Alignment charter.
Students engineer system instructions that implement intentional cognitive scaffolding. The companion is programmed to actively guide users with conceptual hints, analogies, and reflective queries rather than delivering direct, transactional answers.
Teams run active safety audits — stress-testing socioaffective boundaries, autonomy support, and non-anthropomorphic language. The hackathon culminates on Day 5 with a standard AI Project Card presented to an independent panel of researchers.
An industry-standard framework — modelled on frontier AI model cards — documenting model architecture, audited dataset biases, and safety guardrails. Your card should contain:
Domain theme, core learning goals, Socratic tutoring scope, and the Value-Alignment charter authored in Phase 1.
Theme Data Pack limitations, historical representation patterns, and the research questions your investigation surfaced.
Your complete custom system prompts — cognitive scaffolding rules, boundary-setting instructions, and non-anthropomorphic language constraints.
Evidence from the Professional Boundary Probe, Cognitive Scaffolding Audit, Agency Empowerment check, and autonomy safety logs.
The same critical inquiry, packaged as a turnkey model for public activation venues and classroom rollouts nationwide.
Introduction to Responsible AI evaluation and team formation with pre-curated Theme Data Packs.
Hands-on evaluation sprint using Gemini and AI Studio to identify data limitations or algorithmic biases in an assigned theme.
Short flash presentations of audit findings to programme facilitators, earning an instant digital AI Literacy Badge.
Form your trio on Day 1, ingest your data pack on Day 2, and build from there.
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