4.4.1 (HL)—Paper 3 data

A research finding becomes useful evidence when the measure, comparison and context are clear. Interpretation should connect the observed pattern to the construct being studied without claiming more than the design can support.

Start by identifying what was measured, who was included and how the data were produced. Then ask whether the pattern supports a causal explanation, a change over time, a group difference or only an association; bias, sampling and measurement can alter each inference.

If a study reports higher memory scores after a strategy, check the control condition, timing and scoring rule before attributing the difference to the strategy. A short, standardised task may show an effect under those conditions while saying little about everyday learning.

A visible or statistically significant pattern is not automatically important, causal or generalisable. For each source, state the finding, its supporting value or excerpt, the design-based inference and the population or context boundary.

For quantitative findings, report direction and magnitude using the relevant values, spread, association, effect size or significance, then relate them to the design. For qualitative findings, identify a theme, explain the coding or interpretive pattern and support it with an excerpt or source detail. When both are provided, compare whether they converge, complement or contradict one another rather than forcing a single story.