IA Feedback Example
Environmental Systems & Societies — investigating the effect of waste cooking oil on seed germination
Student Draft — Results & Discussion
The results show a clear decline in mung bean germination as oil concentration increases, dropping sharply across the tested range.Linseed germination remained comparatively stable across the same concentrations1. This confirms that oil concentration negatively affects plant growth2, supporting the alternative hypothesis. The qualitative observations also noted visible changes in seed colour and an oil layer on the dish surface at higher concentrations. 3
EE Feedback Example
Business Management — evaluating how a luxury fashion group's social media strategy affects brand exclusivity
Student Draft — STEEPLE Analysis (Social)
Generation Z increasingly values sustainability and affordability in luxury goods, with a notable share of clothing and accessories now purchased second-hand. This trend has pushed the brand toward more influencer collaborations and user-generated content to sustain demand among younger consumers1. A rival luxury brand grew sales by 45% in the same period, compared to only 2% for the company studied2.3
Solid contextual research, but right now this reads as description rather than evaluation. Ask explicitly: does this trend support or undermine exclusivity? You make that judgement two paragraphs later — bring it forward so every STEEPLE factor is assessed in the moment, not just reported.
Excellent use of a comparative data point — this is exactly the kind of evidence examiners want to see. Now push it further: is the growth gap because the rival uses less social media, or because of something else entirely (pricing, product mix)? Right now the link is implied, not tested against alternatives.
Your three analytical tools each point to a slightly different verdict on exclusivity. The essay will read far more convincingly if your conclusion explicitly reconciles this — e.g. "while the STEEPLE analysis suggests X, the financial data complicates this because Y." That kind of synthesis is what separates a 6 from a 7 in this criterion.
IA Feedback Example — Business Management
Evaluating a tech company's pace of AI feature rollout against the trade-off between innovation speed and brand reputation
Student Draft — SWOT Analysis (Weaknesses)
The company is behind competitors in the AI race because advanced features won't ship until 2026, for privacy and testing reasons1. Early research showed many users were unhappy with the first features, but adoption later increased substantially. This shows that speeding up risks losing trust, while slowing down risks losing market share2.3
Good use of a real constraint, but don't just state the delay — quantify what's at stake. How much market share or revenue is realistically at risk per quarter of delay? SWOT weaknesses score much higher when backed by a number, not just a description.
This trade-off is the heart of your research question — good instinct to name it here. But right now both sides are asserted, not weighed. Which risk is actually bigger for this specific company, given its brand position? That judgement call is what Criterion C is rewarding you to make.
Connect this weakness back to your Ansoff Matrix and financial analysis later in the IA — right now each tool's conclusion sits in isolation. A short bridging sentence here ("this weakness is mitigated by the strength identified in Section X") shows examiners you're thinking across tools, not just within them.
IA Feedback Example — Economics
Commentary on a real news article — a new sugar tax and its effect on market efficiency
Student Draft — Commentary
The new tax will raise $10.1 billion, showing the government wants to reduce consumption of sugary drinks1. However, the Opposition says demand is inelastic, so the tax may not work2.3
Good real-world figure, but it needs to sit alongside your MSB/MSC diagram, not stand alone. Label exactly where this $10.1bn appears as the tax-revenue rectangle on your diagram — examiners reward explicit links between the numbers in the article and the diagram you've drawn.
This is the most important sentence in your commentary — don't just report it. If demand really is inelastic, what does that mean for the size of the welfare loss that remains after the tax? Walk through that consequence explicitly rather than leaving it as a quoted opinion.
Your key concept is Efficiency — make sure your conclusion returns to it directly. Does this policy move the market toward or away from allocative efficiency, and by how much? End on that judgement, not just a summary of both sides.
TOK Feedback Example
TOK Essay — exploring the reliability of scientific knowledge
Student Draft — Knowledge Question Discussion
Science is always changing, so we can never be certain that scientific knowledge is true1. This shows that scientific knowledge is fundamentally unreliable2.3
Watch absolute language like "always" and "never" — TOK rewards nuance over certainty. Consider: does provisionality (science updating over time) necessarily mean unreliability? These might be two separate ideas worth untangling rather than treating as the same claim.
Good instinct, but this needs a concrete real-life situation to anchor it — e.g. the shift from Newtonian mechanics to relativity. Abstract claims without a specific example will struggle to reach the top mark band, however logically sound the reasoning is.
Try linking this explicitly back to your knowledge question — e.g. "this suggests that the provisional nature of scientific knowledge does not necessarily undermine its reliability, but instead reflects..." Counter-claims like this demonstrate exactly the critical balance TOK examiners are looking for.
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Strong comparative observation — but push further: why would a small, thin-coated seed like mung bean respond so differently from the larger, more oil-resistant testa of linseed? Linking this to seed coat permeability turns a description into real biological reasoning, which is exactly what this criterion rewards.
"Confirms" is stronger language than a single experiment can support. You've already run the ANOVA — use it here. Try: "the extremely low p-value provides strong statistical evidence that..." Swapping descriptive claims for statistically-grounded ones will lift this section noticeably.
You're sitting on valuable evidence here and not using it — the oil layer and colour changes are physical evidence of how the oil interferes with germination, not just that it does. Pull this qualitative data into your discussion to support the quantitative trend; right now they're presented separately.