Samenvatting
Summary 2.7C Problem 4 - Under Pressure
A short summary of Problem 4
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Problem 4 -Under Pressure1. The articles by Suarez-Pellicioni (2016), Carey (2016) and Beilock (2008) are all review
articles. But do Suarez-Pellicioni, Carey and Beilock provide any justification
[=verantwoording] in terms of inclusion criteria for the evidence they discuss in their articles?
And how does their selection of articles differ from each other?
2. What are the commonalities between the Attentional-Control Theory (ACT) mentioned by
Suarez-Pellicioni, the Debilitating Anxiety Model (DAM) from Carey, and the Distraction
Account of Failure (DAF or ‘choking under pressure’) from Beilock? And how do these
theories differ from each other?
3. In their experiments, Ramirez and Beilock (2011) showed that writing about worries before a
high-stakes test improved test performance. For whom do you think this strategy would
work best: for students with high working memory capacity or students with low working
memory capacity? And do you think this would also be a good strategy to apply during the
exam of 2.7 (so write down your worries first, only then look at the questions)? And what
alternative strategies do you think would be effective in reducing negative effects of your
anxiety for the exam of 2.7?
NOTES
Suárez-Pellicioni, M., Núñez-Peña, M.I, & Colomé, A. (2016).
Math anxiety: A review on its cognitive consequences,
psychophysiological correlates and brain bases. Cognitive,
Affective and Behavioral Neuroscience, 16, 3-22.
AIM: REVIEW, about math anxiety, its impacts on numerical cognition, its electrophysiological
correlates and brain bases; factors and mechanisms that have been claimed to play a role in the
origins or the maintenance of math anxiety are discussed….
Math anxiety → many definitions, what every definition has in common with the others is the
idea that for some ppl dealing with numbers or math-related situations evokes an emotional
response that disrupts their performance
- Mathematics Anxiety Rating Scale (MARS) → 98 items rating scale, where ppl rate how
anxious they feel in situations ranging from formal math setting to informal everyday
situations
- Metanalysis → although individuals who are high in MA also tend to score high on trait
anxiety, these two types of anxieties are clearly separated
- MA is not purely restricted to testing (test anxiety) → the two constructs do not seem to
be interchangeable
, - MA is not recognized in the DSM – but math appears to generate enough difficulty to be
considered the of object of genuine phobia!
- Math avoidance is an unavoidable consequence of MA
- MA is shown to have a worrying negative effect on performance
-------------------------------------------------------------------------------------------------------------------------------
MA and numerical cognition
- Studies have assessed the effect that characteristics off arithmetical problems had on
performance like:
→ problem size effect → reaction times and errors increase as the size of the problem
increases
→ split effect → RTs and errors decrease as the proposed solution in an arithmetic
verification task deviates more from the correct one
Ashcraft and Faust → the first study where MA and numerical cognition were converged →
- Formed 4 groups according to the participants’ levels of MA and manipulated the
complexity of the task by presenting 4 stimulus sets in a verification task (2 simple sets
including single-digit additions and multiplications, 2 complex sets including two digit
additions and mixed arithmetic operations)
RESULTS:
→ the 4 anxiety groups performed rather similarly in the simple addition and
multiplication tasks → meaning that the effect of MA on RTs was either very weak or
nonexistent in the simple condition
→ complex sets were challenging enough to elicit the effects of MA → authors proposed
the anxiety- complexity effect → the deterioration in HMA individuals’ performance
when the stimulus condition become more difficult or complex
→ the group with HMA was frequently faster than the group with middle HMA and the
group with middle LMA, but showed the highest error rates → they sacrificed accuracy
for speed
→ for complex conditions, the HMA groups took the same time to reject false carry
problems, regardless of where the incorrect value was located, suggesting that they did
not take advantage of the opportunity to self-terminate processing upon detecting the
incorrect value, a shortcut that their LMA peers seemed to employ
The finding can be explained if we consider 2 different types of avoidance:
- Global avoidance effect → (enrolling in fewer math courses) would have left HMA
individuals less well-trained in math, not knowing solving strategies, thus failing in self-
terminating processing when the incorrect value was presented in the units column
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