Background
Cognitive style of people and whether they could explain gender differences.
Systemising: the drive and ability to analyse the rules underlying a system to predict its behaviour.
Empathising: the drive and ability to identify another’s mental states and to respond to these with one of a range of appropriate emotions.
Aim:
- To see whether there is still a gender difference in the number of people studying the physical sciences and humanities.
- To see whether males are more likely to be systemisers and females more likely to be empathisers.
- To see whether physical science students are more likely to be systemisers and humanities students more likely to be empathisers.
- To see whether cognitive style is a better predictor than gender in explaining enrolment onto physical science courses compared to humanities courses.
Method
Sample:
415 students – 203 males and 212 females – of either physical science or humanities subject. Selected from an online data base.
Average age was 21.
87.7% were right-handed, 10.6% were left handed and 1.7%were ambidextrous.
Recruited through email post and university advertisements – price draw as incentive.
Participants with psychiatric illness were excluded.
Procedure:
The participants answered the questionnaire and performance tasks vis a secure university website.
They had to give their sex, date of birth, handedness, diagnoses of medical conditions, educational level and degree type.
The tasks and questionnaire could be completed at any order and any time. However, could be done only once.
Systemising Quotient Questionnaire
Originally consisted of 40 items but was revised (SQ-R) and consisted of 75 items. Minimum score was 0 and the maximum was 150. It had gender-neutral items and improved psychometric properties.
Empathising Quotient Questionnaire
40-item questionnaire which measured different aspects of empathy – cognitive or affective.
The participants had to choose between four options: “definitely agree”, “slightly agree”, “slightly disagree”, “definitely disagree”. Half of the items were reverse-scored to avoid response bias.
A brain type was calculated for each participant: Type S, Type E, Type B, Extreme Type E and Extreme Type S.
FC-EFT performance task:
Forced choice task. Selecting one of two possible answers. Participants had to find the small black and white shape in one of two larger and more complex diagrams. 50 seconds for decision.
Eye Test:
Four-choice task which tested cognitive empathy. Participants had to choose one of the four words which best described what the person’s eyes resembled. 20 seconds for decision.
Independent Variables:
- The gender
- The brain type/cognitive style
- The eye task
- FC-EFT
Dependent variable:
Whether people in different university courses had different brain types.
Results:
- There was a difference in sex with regards to students of physical sciences and humanities.
- Questionnaire results showed that there was a significant relationship between sex and cognitive style.
- Males were more likely to have a Type S or Extreme Type S brain.
- Females were more likely to have a Type E or Extreme Type E brain.
- Physical sciences students were more likely to have Type S or Extreme Type S brain.
- Humanities students were more likely to have Type E or Extreme Type E brain.
Logistic regression analysis was conducted to examine which factors were the best predictor of choice:
- Brain type was strongest predictor.
- Performance on the FC-EFT task was the next predictor.
- Performance on the eye test was the next predictor.
- Gender was the weakest predictor.
Conclusion:
It would appear that ‘gender differences’ in degree choice between physical sciences and humanities is less of an actual ‘gender difference’ but of a cognitive style difference. Students with certain brain types tend to pick their degrees differently – systemisers pick physical sciences in the main while empathisers pick humanities subjects in the main.
Strengths:
- Replicable: the procedure was standardising for all participants. Although, there was a problem with duration, the main procedure is easily replicable and therefore the reliability of the results can be checked.
- Quantitative data: the data collected was in the form of statistics, numbers and figures. Therefore, it can be easily analysed and it will take less time to organise. Even though it is not very detailed, it is objective as it gives no room for interpretation.
- Generalisability: a total of 415 participants took part in the study over a short period, therefore it gives a wide spread of results. This can be easily applied to other students of physical and humanities degrees.
- Validity: the researchers used psychometric tasks, which makes comparisons useful as the people’s results are being compared on the same, standardised scale. This makes the differences more meaningful and more likely to be valid.
Weaknesses:
- Sample selection bias: since every participant volunteered to be part of this study, it creates a problem of representativeness. It is possible that the sample had something in common that made them sign up for the study. There are limitations in terms of selection because it was not random and unbiased.
- Lack of control: the researchers did not have much control in the experiment. There was no way to ensure that the correct participant was the one carrying out the study, there was the issue of participants being able to leave the study in-between and continue it later. Also, there was no standard environment, where they participated in.
- Social desirability: participants may give social desirable answers as they want to look good. Since, the participants completed the questionnaire by themselves, they could have chosen wrong answers which is different to how they process information.
- Close-ended questions: There may have been some questions were the participants had to choose an answer that was not how they process information but it was the closest answer to how they do it. Therefore, it may not be a fully true representation of their cognitive style.
CIE A Level Psychology 