01
Authentic theme
The brief is connected to a human, environmental or community need and avoids presenting technology as an automatic solution.
International AI & robotics challenges
Shared global problems become structured, evidence-led student challenges.
CIRC Global Challenges bring schools and student teams together around AI, robotics and responsible innovation. Each challenge combines a real-world theme, a common technical brief, local investigation, milestone reviews and an international showcase. Programmes can be non-competitive, judged or delivered in progressive regional and global stages.
Common challenge briefs
Multiple entry levels
Evidence-based judging
International showcase
01 / Challenge design
A competition is valuable only when the learning architecture is strong
02
Comparable requirements
Core objectives, constraints, evidence and safety rules allow fair review while leaving room for local creativity.
03
Accessible entry levels
Simulation, low-cost hardware and advanced engineering divisions enable participation across different resources and experience.
04
Process and product
Judging recognises research, iteration, responsible decisions and teamwork as well as final performance.
02 / Challenge theme
Climate-Resilient Schools
Teams design an intelligent system that helps a school understand or respond to heat, air quality, energy, water, biodiversity or another locally relevant climate issue.
Research
Establish local evidence
Teams define a measurable school problem, collect permitted data and distinguish observation from assumption.
Solution
Sense, analyse or act
Projects may combine sensors, data analysis, prediction, dashboards or robotic intervention at an appropriate level.
Test
Evaluate impact and limitations
Students compare a baseline and prototype result, explain uncertainty and consider cost, maintenance and unintended effects.
Showcase
Create a global evidence atlas
Participating schools contribute a concise local case so audiences can compare context, methods and design choices.
03 / Challenge theme
Autonomous Search and Support
Students develop robots or simulations for a controlled search-and-support mission. The challenge rewards safe, reliable behaviour and clear technical evidence rather than speed alone.
01
Mission tasks
Navigate a mapped or partially known zone, identify targets, deliver a lightweight item or transmit useful information.
02
Engineering constraints
Teams work within specified size, energy, communication, autonomy and safety limits.
03
Failure scenarios
Changed routes, sensor uncertainty or connection loss test whether systems stop, recover or request human assistance appropriately.
04
Technical review
Architecture, code, test logs, risk controls and operator procedures form part of the judged evidence.
04 / Challenge theme
AI for Inclusive Communities
Teams create a digital or robotic prototype that improves access to information, services, movement or participation for a clearly defined community scenario.
01
Co-design evidence
Teams demonstrate how user needs were researched and avoid making unsupported assumptions about disability or disadvantage.
02
Accessible experience
Interface, language, interaction and physical design are evaluated against relevant user tasks and accessibility principles.
03
Responsible data
Projects minimise sensitive information, explain consent and maintain meaningful human choice.
04
Social value review
Students consider affordability, availability, maintenance and who might still be excluded by the proposed system.
05 / Challenge theme
Future Food and Intelligent Agriculture
Students investigate how sensing, data and automation might support resilient food systems while considering biological, environmental and economic constraints.
01
Local context
Projects begin with a crop, growing environment, supply issue or food-waste challenge relevant to the team’s region.
02
Technical pathway
Possible solutions include monitoring, image classification, controlled irrigation, robotic inspection or decision-support dashboards.
03
Evidence requirement
Teams validate measurements or model outputs and explain where expert agricultural judgement remains necessary.
04
Systems impact
Water, energy, materials, cost and labour implications are considered alongside technical performance.
06 / Participation pathway
A transparent route from registration to international showcase
Stage 1
Briefing and team formation
Schools receive the brief, eligibility, safeguarding requirements, technical rules, assessment rubric and teacher orientation.
Stage 2
Research and concept review
Teams submit a problem statement, initial evidence, proposed architecture, risk considerations and project plan.
Stage 3
Build and verification
Milestone reviews examine progress, testing, documentation and responsible design without completing the work for students.
Stage 4
Demonstration and defence
Finalists present the system, respond to technical questions and reflect on limitations, iteration and next steps.
07 / Entry levels
Comparable ambition without requiring identical equipment
Foundation
Concept and simulation
Teams use visual coding, digital models or supplied datasets to demonstrate logic, research and responsible decision-making.
Development
Integrated prototype
Students combine code, electronics, sensors or an application into a working solution tested against common criteria.
Advanced
Autonomy and research
Teams use more complex models, robotics or original data and provide deeper evaluation and verification.
Open
Local innovation category
A flexible division recognises solutions shaped by distinctive regional needs while maintaining core evidence and safety standards.
08 / Judging framework
Clear criteria reward credible work, not polished claims
01
Problem and research
Quality of context, user understanding, evidence, requirements and recognition of uncertainty.
02
Technical solution
Architecture, appropriate use of AI or robotics, integration, functionality and clarity of technical explanation.
03
Testing and responsibility
Verification, failure analysis, safety, privacy, fairness, accessibility and human oversight.
04
Team and communication
Role ownership, iteration, documentation, presentation quality and ability to answer questions honestly.
09 / Challenge integrity
Safeguarding, authorship and fair participation are designed into the event
01
Student ownership
Permitted mentor support and AI tool use are declared; teams identify what students designed, built and understood.
02
Safe participation
Schools retain safeguarding responsibility and use approved, moderated channels for international interaction.
03
Technical safety
Hardware, batteries, tools, movement, radio use and demonstrations follow venue and school risk controls.
04
Fair review
Published rubrics, judge guidance, conflict declarations and evidence-based scoring improve transparency.
10 / Challenge outputs
The programme creates value beyond prizes
01
Student portfolios
Research, design, code, testing, reflection and technical presentations provide durable evidence of learning.
02
Teacher network
Briefings, shared resources and post-event review connect educators interested in sustained AI and robotics learning.
03
International case library
Approved summaries show how the same global issue generates different locally grounded solutions.
04
Progression opportunities
Strong teams may progress to research mentoring, advanced studios or future international projects, subject to programme criteria.
Build the next programme
Ready to turn AI and robotics into purposeful student work?
We can shape a class project, school pilot, international team or multi-school pathway around your learners.