IB Diploma Programme: DP 2
Age Group: 17 to 18 years
Subjects: Biology HL/SL + ESS + Chemistry + TOK
Type: Advanced Field Investigation Supporting IA and Extended Essay Development
Duration: Full-Day Ecological Systems Analysis
Venue: ChukkiMane Eco-Campus
Learning Approach: Quantitative observation • Systems modelling • Comparative evaluation • Research design refinement
TOK: To what extent do scientific models accurately represent complex ecological realities?
EE Support: Refinement of research methodology • Variable control • Sampling design • Data reliability evaluation
Agro-Ecosystem Modelling and Sustainability Evaluation is a DP 2 advanced field investigation focusing on ecological measurement, methodological rigor, and evaluative reasoning.
Students move beyond observation to structured ecological assessment, comparative sustainability analysis, and research feasibility evaluation. Emphasis is placed on data reliability, sampling bias, and the limitations of field research in complex systems.
The program mirrors IA and EE expectations in structure, documentation precision, and analytical depth.
Dynamic Equilibrium • Limiting Factors • Feedback Mechanisms • Carrying Capacity • Sustainability Thresholds
· Thinking Skills: evaluation, synthesis, modelling, hypothesis testing
· Research Skills: sampling strategy design, variable control, data validation
· Communication Skills: structured scientific argumentation using command terms
· Self-Management Skills: methodological discipline and precision
· Social Skills: collaborative peer review
Students will:
· evaluate agro-ecosystems using measurable ecological indicators
· design and critique field-based research methodologies
· analyse nutrient cycling through systems modelling
· assess sustainability thresholds and resilience factors
· construct IA and EE-ready research frameworks
Students will be able to:
· quantify biodiversity indicators using defined sampling criteria
· evaluate ecological stability using systems terminology
· justify methodological choices in field investigations
· analyse limitations of observational data
· refine a research question with explicit independent and dependent variables
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