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AQA A Level Biology exam technique guide & maths formulas (based on past paper analysis)

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This document provides A* level exam technique, helping you secure tiop marks in AQA A Level Biology even with the extremely specific mark schemes! INCLUDES - Frameworks that ensure you hit the marking points every time - Strategy for AO1 questions, AO2 and AO3 - ALL the maths formulas (AS and A Level ) - Specific tips for each unit (3.1 - 3.8) - A list of all the required practicals, and possible long answer questions

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Voorbeeld van de inhoud

✍️ Exam tech

,Main tips
-​ Highlighter, read q TWICE & only draw on graphs with a pencil and a ruler
-​ Command word !
-​ Bullet point answers
-​ Focus on the specific question demand = ao2 = key q = WHAT CHANGED
-​ Ao2 = unfamiliar context = figure out the topic + treat like a textbook
-​ Ao2 = clear chains of cause - and effect = flow diagrams help to understand
-​ Be specific = attachment protein of what? LOCATION? Who’s DNA?
-​ Show cause and effect
-​ Count marking points + 1 insurance point
-​ Annotate the AO_ next to each question
-​ List rule = right + wrong answer = wrong, so make sure you don’t fumble too many
points
NEVER ABBRIEVIATE
-​ GP / TP / RuBp
-​ Hb - haemoglobin
-​ Acetyl CoA - acetyl coenzyme A
-​ DCT + PCT - distal + proximal convoluted tubule
-​ AVN + SAN - atrioventricular node + sinoatrial node
-​ AV + SL valve - atrioventricular + semilunar valve

AO1
-​ Recall, key terms + specific A level vocab, logical, clear sequence
-​ Compare & contrast = ‘all statements must be clearly linked & comparative with and /
whereas/ but, no inference (clear distinct sentences) = count them

AO2
-​ Explain =
-​ 1 - Identify the topic
-​ 2 - RECALL the magic marking phrases
-​ 3 - Now figure out the chain of c → e
-​ WHAT CHANGED / the cause → explain / effect → link to question
-​ Many / A large number of
-​ So / As / Causes / Therefore
-​ more / less / greater / lesser / higher / lower / reduced /
prevents / high rate of / lower rate of / more, less likely to /
faster, slower than /
-​ Clear cause - and effect
-​ State the cause (temperature increases)
-​ Explain the mechanism (AS higher kinetic energy, SO more e-s complexes)
-​ Link to the question + the effect (SO rate of reaction increases)

AO3 - Analysis, interpretation & evaluation
-​ Use the DV to compare, not the wording of the conclusion (ie - not ‘more effective’,
but ‘greater reduction in mean __ so shows ___’)
-​ Again, with hypotheses - use the DV, not the conclusion like in psych
-​ REJECTS = ‘Results’ due to chance (must say difference / increase / decrease / fall /
rise)

, Evaluate…conclusion
DCE
-​ Compare (what does the data show?)
-​ Conclude (increase / decrease / greater / lower / higher __ in x than y / relationship
-​ Evaluate (use the conclusion to guide - pros, cons, validity)
-​ Tailor the evaluation points to the question’s context + add a justification for safety
-​ Make a claim + so _____
-​ If data has probability / SD = ‘significant’ & ‘chance’ must be integrated into answer

C - compare
Comparative point using the DV NOT from the question stem, but from the data
-​ ___ increased for both groups
-​ All conditions compared to (control) show ___
-​ ___ reduces __ and ___ movement
-​ Greater (proportional) effect on ___
-​ For the control an increase in ___ increases ____;
-​ For ___ an increase in ___ reduces ___;
-​ 2 reduces ____ (compared to control);
-​ 1 and 3 increases _____ (compared to control);
C - what can you conclude
Based on data comparison → link to the conclusion / context = effects, what does it mean)
-​ SO ____ / so shows ____
E - evaluation
Tailor the rote learned ones to the question context
If it isn’t written = it never happened.
-​ Graph shows correlation but doesn’t prove _____ due to __ / could be due to other
factors
-​ Maths models may be inaccurate
-​ Unknown effects of x exposure
-​ Different age / sex
-​ No stats test to prove they are significant
-​ Sample size → large enough to be representative
-​ Duration → unknown / long enough to know the long-term effects
-​ Tested on animals → would have a different effect on humans
-​ Stats → to see if there is a significant difference / correlation
-​ Tested on male/females only → didn’t know effect on the other sex
-​ Tested on a particular age → don’t know effect on other ages
-​ Tested on 1 species → don’t know if it applies to all species
-​ Control → comparison
-​ Double blind / placebo → reduce bias
-​ Sample size mark - give a back up point
-​ Cost
-​ SD overlap → difference not significant
-​ Less than ___ probability that the result is due to chance → so not / significant
-​ Side effects
Evaluate the ethics (1)
-​ IDEA FOR & AGAINST
-​ Harmful BUT stops human suffering
-​ Animal abuse BUT prevents human deaths
Variables
-​ Sex

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