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3.8.3
Genome Projects
Analytical deep dive — question counts, mark distribution, mastery curves, command-word breakdowns, and examiner narrative analysis.
Questions
4
Total marks
9
Marks / Q
2.2
Accessibility
61.0%
Mastery
35.5%
Student strength
59.5%
01
At a glance
3.8.3 · Genome Projects
8YRSYNTHESIS
3.8.3 (Genome Projects) appeared in 3 of the 8 years between 2017 and 2024, contributing 4 questions and 9 marks across Papers 1, 2 and 3. APPLICATION dominates the mark distribution at 88.9% of total marks. The accessibility–mastery gap sits at 25.5 percentage points (61.0% vs 35.5%) — most students reach partial credit, but full marks remain harder to secure. Mastery varied year-to-year, lowest in 2024 (16.5%) and highest in 2018 (60.0%).
Access–mastery gap
+26 pp
Lowest mastery
2024 · 16.5%
Highest mastery
2018 · 60.0%
02
Question type split
By marks · compound to dominant
9MARKS
9
marks
Application88.9%8 marks
Knowledge11.1%1 marks
Calculation0.0%0 marks
(by marks; compound rows assigned to dominant type):
03
Credit terms — quick reference
Mark scheme tier-locked
6TERMS
Tier 1 · Always credit
Tier 2 · Sometimes credit
Reject · Never credit
all DNA/genes within a speciesdifferent genes (same species)mRNA sequencesamino acid sequences'gene machine''no stats test' (meaningless here); 'LS could be cured if caught early'; 'screen only carriers'; 'LS cannot be passed on' (death in 3y)
04
Question patterns
Recurring formats & tariff structure
0PARAGRAPHS
05
Year-over-year presence
P1 + P3 · 2017–2024
8YEARS
| Year | Questions | Total marks | Mean accessibility | Mean mastery |
|---|---|---|---|---|
| 2017 | 0 | 0 | — COVID | — COVID |
| 2018 | 1 | 1 | 60.0% | 60.0% |
| 2019 | 0 | 0 | — COVID | — COVID |
| 2020 | 0 | 0 | — COVID | — COVID |
| 2021 | 0 | 0 | — COVID | — COVID |
| 2022 | 1 | 2 | 55.0% | 49.0% |
| 2023 | 0 | 0 | — COVID | — COVID |
| 2024 | 2 | 6 | 64.5% | 16.5% |
06
Mark scheme intelligence
2017–2024 mark scheme corpus
6TERMS
Tier 1 — frequently credited
| Term | Times credited | Years | Notes |
|---|---|---|---|
| all DNA/genes within a species | 1 | 2018 | |
| different genes (same species) | 1 | 2024 | |
| mRNA sequences | 1 | 2024 | |
| amino acid sequences | 1 | 2024 | |
| 'gene machine' | 1 | 2024 | |
| 'no stats test' (meaningless here); 'LS could be cured if caught early'; 'screen only carriers'; 'LS cannot be passed on' (death in 3y) | 1 | 2024 |
Marks in this sub-section are typically awarded for precise terminology and correct application of biological principles. Sequential mark schemes — where each mark requires building on the previous one — are common in multi-mark questions; stating the first step without progression rarely earns more than one mark. Calculation marks are typically split between method (correct setup and value extraction) and answer (accurate numerical result), allowing partial credit when arithmetic errors occur.
07
Where students lose marks
Examiner-anchored error patterns
2CASE STUDIES
Conceptual errors
- Defining the genome at species level rather than organism level — "all the DNA/genes in a species" was explicitly rejected; the genome is all the DNA in a cell or organism
- Assuming elevated PSA must indicate cancer — PSA is produced by all prostate cells, not only cancerous ones; non-cancerous conditions such as enlarged prostate and urinary tract infections also raise PSA levels, making false positives a structural feature of the test
- Treating a comparison of mitochondrial genes between geckos of the same species as a comparison of different genes — because the geckos are the same species, they share the same genes; any differences lie in alleles (DNA base sequences), not in gene identity
Vocabulary errors
- "All genes in a chromosome" or "all genes in a species" for genome — both were rejected in 2018; the required qualifier is "in a cell/organism"
- Vague descriptions of PSA test failure ("inaccurate," "unreliable," "not specific enough") without naming specific non-cancer conditions — the mark scheme required a named physiological cause, not a general comment on test quality
- "Different genes" instead of "different alleles" when describing base sequence variation within the same species — explicitly flagged in the 2024 gecko question as a marking error
Application errors
- On the Leigh syndrome universal screening evaluation (2024 P3 Q05.4): applying rote "no statistics test" phrasing that is meaningless in this clinical genetics context — effective evaluation required engagement with LS-specific data (1 in 40 000 globally, 75 causative genes, Faroe Islands frequency, cost of probe production)
- Stating LS could be "cured if caught early" — LS has no cure; students who did not engage with the stem information applied general early-diagnosis reasoning that is factually incorrect for this condition
- On the mitochondrial comparison question (2024 P2 Q10.4): naming techniques (PCR, sequencing) correctly but not explaining what is being compared or why a difference in the output would indicate a distinct genetic group — the technique alone was insufficient without stating comparison of DNA base sequences and the inference from different alleles
High-impact failures · examiner narrative
2024 P2 Q10.43 marks
Only 3% mastery, with approximately 11% of students not attempting. The near-universal error was treating the nocturnal and diurnal geckos as different species with different genes, rather than recognising them as the same species with potentially different alleles. This made the entire comparison framework wrong: students who understood the techniques (PCR, automated sequencing) but applied them to "different genes" scored nothing because the conceptual framing was incorrect from the start. Comparing mRNA sequences or amino acid sequences instead of DNA base sequences was also rejected. Students who named techniques without explaining what makes comparison rapid (automation, computerised sequencing) failed to secure the third mark.
2024 P3 Q05.43 marks
Approximately 30% mastery, with a fairly even spread across all mark levels — indicating no dominant correct response pattern rather than a single consistent error. The examiner flagged three rote errors: "no statistics test" (meaningless here, as no statistical test is being described), "LS can be cured if caught early" (factually false — LS is fatal within three years and has no cure), and "no point screening if they will die anyway" (not a valid argument against carrier screening). Effective responses used LS-specific data from the question to argue proportionately: frequency (1 in 40 000 globally vs 1 in 1 700 in the Faroe Islands), the need for 75 separate probes, and cost versus benefit of population-wide screening.
08
Difficulty signals
Performance metric synthesis
26PP GAP
Mean accessibility
61.0%
Mean mastery
35.5%
Mean student strength
59.5%
The accessibility–mastery gap of 25.5 percentage points characterises this sub-section's difficulty profile. Most students reach partial credit; full marks remain harder to achieve. Within 3.8 (The control of gene expression), 3.8.3 ranks 3 of 4 sub-sections by mean mastery (1 = hardest). Mastery trajectory is falling across the cohort window: 60.0% in 2018 → 16.5% in 2024 (-43.5 percentage points). Mean mastery was lowest in 2024 (16.5%) and highest in 2018 (60.0%).