IB Diploma Programme: DP 1
Age Group: 16 to 17 years
Subjects: Biology + ESS + Chemistry + TOK
Type: Scientific Field Investigation (IA and EE skill development aligned)
Duration: Full-Day Experiential Ecological Systems Study
Venue: ChukkiMane Eco-Campus
Learning Approach: Scientific observation • Systems modelling • Field data analysis • Evidence-based reasoning
TOK: How do scientific models help us understand complex natural systems?
EE Support: Research question development • Variable identification • Field-based scientific observation
Agro-Ecosystems and Sustainable Biological Systems is a DP 1 scientific field investigation examining how food forests function as integrated biological and chemical systems.
Students analyse nutrient cycles, soil composition, pollination networks, biodiversity indicators, energy transfer, and sustainable agricultural techniques. The experience strengthens scientific observation, systems modelling, and hypothesis formation.
The program directly supports Internal Assessment skill development through measurable variables, data recording, and ecological interpretation.
Energy Flow • Nutrient Cycling • Biodiversity • Interdependence • Ecological Equilibrium
Students strengthen:
· Thinking Skills: hypothesis formation, analysis, evaluation, modelling
· Research Skills: field observation, variable identification, systems mapping
· Communication Skills: scientific explanation using disciplinary vocabulary
· Self-Management Skills: precision, methodical recording, reflection
· Social Skills: collaborative investigation
Students will:
· analyse food forests as ecological systems
· evaluate composting as a biochemical decomposition process
· investigate pollination networks and species interaction
· compare traditional and mechanized energy systems
· apply IA-style experimental design thinking
Students will be able to:
· identify producers, consumers, and decomposers in situ
· map nutrient cycles within agro-ecosystems
· evaluate biodiversity indicators
· analyse sustainability through measurable variables
· formulate a Biology or ESS IA-style research question
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