IB MYP Sciences eAssessment: Preparing for the Investigation Skills Task

The full syllabus guide confirms the Investigation skills task carries 50 of the eAssessment’s 100 total marks – fully half, and by a clear margin the largest of the three tasks. These notes focus specifically on preparing for it, alongside the subject overview and assessment revision notes already on the site.

Why this task deserves proportionately more preparation time

Because Investigation skills is worth half the total marks, a student who knows scientific content well but has not practised designing, running and evaluating investigations is under-prepared for where most of the marks actually sit, regardless of how strong their Knowing and understanding (25 marks) or Applying science (25 marks) performance might be. Preparation time should reflect this weighting, not be split evenly across all three tasks.

Criterion B: Inquiring and designing

Covers formulating a testable hypothesis, identifying variables (independent, dependent, and controlled), and designing a method that could actually answer the investigation’s question. Revise the difference between a vague prediction and a genuinely testable hypothesis: a testable hypothesis states a specific, measurable relationship between an independent and dependent variable, ideally with a stated scientific reasoning for the prediction, not just a guess at what might happen.

Criterion C: Processing and evaluating

Covers collecting, processing and interpreting data, and explaining conclusions appropriately reached from it – including identifying limitations in the method and suggesting realistic improvements. Revise the distinction between a conclusion that is merely stated and one that is properly justified by referring back to the actual data collected (trends, patterns, anomalies) rather than by restating the original hypothesis as though it were automatically confirmed.

Worked practice example

A student investigates how the concentration of a salt solution affects the rate at which a simple plant tissue (such as potato) loses mass through osmosis.

• Hypothesis (Criterion B): “As the concentration of the salt solution increases, the mass of the potato sample will decrease more, because a more concentrated external solution has a lower water potential, causing more water to leave the plant cells by osmosis.” This states a specific, measurable relationship (concentration vs mass change) and gives a scientific reason for the prediction, rather than simply guessing an outcome.
• Variables (Criterion B): independent variable – salt solution concentration; dependent variable – change in mass of the potato sample; controlled variables – sample size/shape, soaking time, temperature. A strong answer names controlled variables explicitly and explains briefly why each must be controlled (e.g. temperature affects the rate of osmosis independently of concentration, so an uncontrolled temperature would confound the results).
• Processing data (Criterion C): calculate percentage change in mass for each sample rather than raw mass change alone, since percentage change allows fair comparison between samples that started at slightly different masses.
• Evaluating (Criterion C): a genuinely useful evaluation names a specific limitation (e.g. only one sample was tested per concentration, so a single anomalous result could distort the pattern) and a specific, realistic improvement (e.g. repeat each concentration three times and use the mean), rather than a generic statement such as “more trials would improve accuracy” with no explanation of why.

Common preparation mistakes

• Writing a prediction without a stated scientific reason – this scores lower under Criterion B than a hypothesis that explains why the predicted relationship should occur.
• Presenting data without processing it – raw, unprocessed data (e.g. mass readings with no calculated change or percentage change) does not demonstrate the interpretation Criterion C actually rewards.
• Evaluating only the accuracy of measurements (“we might have measured wrong”) without considering the design of the investigation itself (sample size, repeats, controlled variables) – genuine evaluation should address both.
• Assuming the eAssessment investigation task will match the discipline (biology, chemistry, physics) most recently taught – because the on-screen examination can draw on any of biology, chemistry or physics content, practise this task’s skills across more than one discipline’s data, not just the most recent unit.

How to approach it

Because this task can present either a single investigation or several discrete scenarios, practise both formats: working through one investigation end-to-end (hypothesis through evaluation), and answering shorter, self-contained questions about an investigation someone else designed (where you are asked to identify a flaw, or process given data, without having designed the study yourself). Practising with real, imperfect data – data with some scatter or an anomalous point – is more realistic preparation than only ever working with clean, textbook-perfect results, since real eAssessment data is rarely perfectly tidy.

Self-test

1. Why does the Investigation skills task deserve proportionately more preparation time than the other two tasks?
2. What makes a hypothesis “testable” rather than just a guess?
3. In the worked potato/osmosis example, why is percentage change in mass a better measure to report than raw mass change alone?
4. Give one example of a weak evaluation statement and explain what a stronger version would add.
5. Why should preparation for this task span more than one science discipline, regardless of which discipline was most recently taught in class?

Answers: 1. Because it is worth 50 of the 100 total eAssessment marks, fully half, so preparation time should be weighted to reflect its actual share of the assessment. 2. A testable hypothesis states a specific, measurable relationship between an independent and dependent variable, usually supported by a stated scientific reason for the prediction, rather than a vague, unmeasurable guess. 3. Because percentage change accounts for samples that started at slightly different masses, allowing a fair comparison between them, whereas raw mass change alone could be misleading if starting masses varied. 4. A weak statement is “more trials would improve accuracy” with no explanation; a stronger version names the specific limitation (e.g. only one trial per concentration) and a specific, realistic improvement (e.g. repeat each concentration three times and use the mean), explaining why that improvement would help. 5. Because the MYP Sciences on-screen examination can draw on biology, chemistry or physics content regardless of the course model (discrete, modular or integrated) a school followed, so revision confined to one recently taught discipline leaves genuine gaps.

Official syllabus

International Baccalaureate Organization, Middle Years Programme Subject Brief – Sciences, from 2014, (c) 2015 – the same source already cited by the full syllabus guide, which first described the Investigation skills task’s 50-mark weighting. The worked potato/osmosis practice example above is an original example written for this resource, not a reproduction of any specific official eAssessment question.