IB Biology IA Grader
- Lots of students struggle to decode their Biology Internal Assessment grade and assessment.
- This is a free grading tool that breaks down the IB Biology IA rubric into plain English, so you understand exactly where your scientific investigation stands across all four assessment criteria.
- The embedded grader makes self-evaluation faster and more accurate than manual rubric checking, so you're never left guessing.
The grader works in two modes:
- Draft Mode: Quick assessment of your work-in-progress. Input your current sections and get instant feedback on which criteria need more work before you finish writing.
- Full Mode: Complete evaluation of your finished IA. Input your final project details across all criteria and get a comprehensive grade breakdown with specific improvement suggestions for each section.
Quick Start Checklist
- Before using the grader, ensure you understand these key elements:
- Research Question - Clear, focused, and testable question that can be investigated experimentally
- Defining Variables - Independent, dependent, and controlled variables clearly identified with units
- Methodology - Step-by-step replicable procedure with scientific reasoning for each step
- Raw Data - Minimum 5 trials with quantitative measurements and appropriate range
- Data Processing - Calculations, graphs, statistical analysis with error bars and uncertainties
- Scientific Theory - Background research connecting your investigation to biological concepts
- Word Count Verification - Maximum 3,000 words (excluding data tables, graphs, and bibliography)
- Safety & Ethics - Evidence of risk assessment and ethical considerations where applicable
Rubric Breakdown
- The IB Biology IA is assessed using four criteria, each worth up to 6 marks, totaling 24 marks.
- Below is a breakdown of each criterion, what it assesses, and how to excel in each area.
Criterion A: Research Design (6 marks)
- This criterion tests how well you plan and design your scientific investigation.
- It evaluates your research question, methodology, and variable control.
| Mark Band | What It Means | Evidence You Must Show |
|---|---|---|
| 5–6 | Comprehensive and well-justified research design. | Clear research question, thorough background, detailed methodology, and control of variables. |
| 3–4 | Adequate research design with some justification. | Research question and methodology present but lacking depth or clarity. |
| 1–2 | Limited research design with minimal justification. | Unclear research question, insufficient methodology, and poor control of variables. |
| 0 | No relevant research design presented. | Absent or entirely inappropriate research question and methodology. |
Criterion B: Data Analysis (6 marks)
- This evaluates how well you process, present, and interpret your data.
- It tests your ability to analyze patterns and discuss uncertainties.
| Mark Band | What It Means | Evidence You Must Show |
|---|---|---|
| 5–6 | Thorough and accurate data analysis with clear interpretation. | Comprehensive data collection, appropriate processing, and insightful interpretation. |
| 3–4 | Adequate data analysis with some interpretation. | Sufficient data collection and processing with basic interpretation. |
| 1–2 | Limited data analysis with minimal interpretation. | Insufficient data collection, poor processing, and superficial interpretation. |
| 0 | No relevant data analysis presented. | Absent or entirely inappropriate data collection and processing. |
Criterion C: Conclusion (6 marks)
- This assesses how well you answer your research question using your data.
- It evaluates your scientific understanding and connection to biological theory.
| Mark Band | What It Means | Evidence You Must Show |
|---|---|---|
| 5–6 | Well-supported conclusions addressing the research question. | Clear linkage between data analysis and conclusions with biological context. |
| 3–4 | Conclusions addressing the research question with some support. | Basic linkage between data analysis and conclusions. |
| 1–2 | Limited conclusions with minimal support. | Weak linkage between data analysis and conclusions. |
| 0 | No relevant conclusions presented. | Absent or entirely inappropriate conclusions. |
Criterion D: Evaluation (6 marks)
- This tests your ability to critically evaluate your investigation.
- It assesses your identification of limitations and realistic improvements.
| Mark Band | What It Means | Evidence You Must Show |
|---|---|---|
| 5–6 | Comprehensive evaluation with well-justified improvements. | Detailed analysis of strengths, limitations, and realistic improvements. |
| 3–4 | Adequate evaluation with some justified improvements. | Basic analysis of strengths, limitations, and improvements. |
| 1–2 | Limited evaluation with minimal improvements. | Superficial analysis of strengths, limitations, and improvements. |
| 0 | No relevant evaluation presented. | Absent or entirely inappropriate evaluation. |
How to Interpret Your Grade from the Tool
- The embedded grader calculates your total score out of 24 marks across all four criteria.
- Here's how to interpret your results:
- 22-24 marks (Grade 7 territory): Excellent work with sophisticated scientific investigation. Minor refinements needed.
- 19-21 marks (Grade 6 range): Strong investigation with good data analysis. Focus on evaluation depth and biological theory application.
- 16-18 marks (Grade 5 level): Competent work meeting basic requirements. Strengthen data processing and conclusion justification.
- 13-15 marks (Grade 4 range): Adequate foundation but needs significant improvement. Review methodology detail and variable control.
- Below 13 marks: Major revision required across most criteria. Restructure approach and strengthen experimental design.
If you're between bands, focus on Criterion B (Data Analysis) and Criterion D (Evaluation) - these often offer the biggest improvement opportunities.
Grade Boundaries & Converting Your Mark
IB Biology IA grade boundaries vary by session but your IA contributes significantly to your final grade:
| IB Grade | Typical Mark Range (out of 25) | Percentage |
|---|---|---|
| 7 | 22-24 | 88-100% |
| 6 | 19-21 | 76-84% |
| 5 | 16-18 | 64-72% |
| 4 | 13-15 | 52-60% |
| 3 | 10-12 | 40-48% |
| 2 | 7-9 | 28-36% |
| 1 | 0-6 | 0-24% |
- Your IA contributes 20% for SL and 20% for HL to your final Biology grade
- A strong IA can boost your overall grade significantly, especially if you're borderline between grade bands.
Subject-Specific Tips
- Experimental Design:
- Choose easily measurable biological processes like enzyme activity, osmosis, or photosynthesis.
- Ensure your independent variable has a clear quantitative range (e.g., pH 4, 5, 6, 7, 8).
- Data Collection:
- Record raw data in tables with appropriate units and decimal places.
- Take multiple measurements at each condition to calculate means and standard deviations.
- Statistical Analysis:
- Use appropriate statistical tests (t-tests, correlation analysis) where relevant.
- Calculate percentage uncertainties and show propagation of errors.
- Biological Theory:
- Connect your results to specific biological processes (e.g., enzyme kinetics, membrane transport).
- Reference relevant biological concepts from the IB syllabus in your background and conclusion.
- Practical Considerations:
- Address safety protocols (chemical hazards, biological materials handling).
- Consider ethical issues (animal welfare, environmental impact) where applicable.
- Vague research question → Make it specific with clear variables, units, and controlled conditions
- Insufficient trials → Conduct minimum 5 repeats to ensure statistical reliability
- Poor variable control → Identify and control all variables except your independent variable
- Missing uncertainties → Include error bars, standard deviation, and uncertainty calculations
- Weak data processing → Show sample calculations, use appropriate graphs, and include statistical analysis
- Superficial conclusion → Quantify results, reference specific data, and connect to biological theory
- Generic evaluation → Identify specific limitations and suggest realistic, detailed improvements
- Word count violations → Stay within 3,000 words - only first 3,000 words are marked
- Missing safety considerations → Address risk assessment and ethical issues where relevant
- Poor graph presentation → Include proper titles, axis labels, units, error bars, and trend lines
FAQs
- How long should my IA be?
- Maximum 3,000 words - focus on quality over quantity and stay within the limit.
- Do I need to use complex equipment?
- No, simple school laboratory equipment is fine - focus on good experimental design rather than sophisticated apparatus.
- Should I include statistical tests?
- Basic statistics (mean, standard deviation) are expected. Advanced tests (t-tests, ANOVA) can enhance higher-level analysis.
- How many trials should I do?
- Minimum 5 repeats per condition, but more is better for statistical reliability.
- Can I investigate human subjects?
- Limited human studies are allowed but require strict ethical protocols and school approval.
- What if my results don't support my hypothesis?
- Unexpected results are fine - focus on explaining why using biological theory and evaluating methodology.
- Should I include preliminary experiments?
- Yes, preliminary work demonstrates good research design and helps justify your methodology.
- How detailed should my method be?
- Detailed enough for someone else to replicate exactly - include equipment specifications, measurements, and timing.
- Can I use online data or secondary sources?
- No, you must collect primary data through your own experimental work.
- What biological processes work well for IAs?
- Enzyme investigations, plant responses, microbiology, osmosis/diffusion, and photosynthesis/respiration are popular and work well.
Use the Free Biology IA Grader Now
- Stop guessing about your grade.
- The comprehensive grading tool evaluates your IA against all four official criteria, giving instant feedback on strengths and improvement areas.
- Input your investigation details and get a preliminary grade calculation that helps you focus revision efforts where they matter most.
- Biology-specific analysis helps you master the scientific methodology and data analysis that separate excellent from average Biology IAs.