The ICT gender imbalance in schools and beyond : missed opportunities
Bibliographic record
Abstract
'Pipeline shrinkage', the steady attrition of women in the ICT industry despite their academic achievement, has been of great concern not only in the United Kingdom but also internationally for almost a quarter of a century. This study reviewed literature and prior research from both national and international perspectives, with a particular research focus on the experiences of students in three British secondary schools. The situation may have been exacerbated in British schools as government strategies have increasingly focussed on male students' apparent 'underachievement' relative to female students. One aspect of focus has been the resurrection of interest in single-sex classes in state schools. The comparatively strong academic achievement of female students has led to little focussed research on why they fail to capitalise on their ICT ability and study the subject beyond school level. Their behavioural intentions have not been the focus of the research. This study tested the fit of The Theory of Planned Behaviour (TpB) as a theoretical framework to examine how behavioural, normative and control beliefs differed, both between male and female students in mixed and single gender schools and female students taught in mixed or single sex classroom contexts. Samples of 150 students were questioned from which 120 were useable; 40 from each of the three participating schools. In two cases 25 students were Key Stage 4 students and 15 were A-Level students. A series of semi-structured interviews were undertaken with a further sample of 30 Key Stage 4 ICT students. Results showed data fitted the TpB model and explained female students' lack of intention to study ICT beyond their current level as beliefs were found to be related to that intention. Recommendations were provided for changes in practice based on attitudinal responses to behavioural beliefs, learning styles and teaching strategies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".