"Fair? Shared? Supported?: examining expectations and realities for Irish-medium practitioners". Research report on the additional competences and associated workloads of the Irish-medium practitioner by the Centre for Language Education Research, Queen’s University Belfast
Bibliographic record
Abstract
In Northern Ireland, teacher shortages and the lack of dedicated opportunities for Teacher Professional Learning (TPL) in the Irish Medium Education (IME) sector are recognised as some of the issues which have the potential to contribute to sustained educational underachievement for pupils in Northern Ireland (Fair Start Policy 2021). In order to better understand and evidence challenges for teachers and educational practitioners in the IME sector in Northern Ireland this research project undertook: 1) a comprehensive systematic-style literature review in relation to the competencies<br/>of bilingual/Irish-medium education practitioners 2) interviews with student teachers, teachers, principals, and teacher educators on the additional competencies and challenges of working in IME in Northern Ireland<br/>3) the design of an action plan aimed at aiding teacher retention and helping to<br/>alleviating attrition rates of Irish-medium practitioners in Northern Ireland<br/>The systematic literature review of international research conducted in immersion education contexts sought to capture a clear and comprehensive picture of (i) the challenges associated with immersion education models, (ii) responses to those challenges, and (iii) teacher competencies involved in delivering instruction. While several important themes arose from the analysis of the interview data, they are encompassed by two overarching themes: i) the resource gap and ii) the disparity/incongruity of systemic assessment. First, in relation to the resources gap, we use this phrase in our analysis to reference both material and human resources.Teaching and learning resources include classroom-based materials, subject-specific textbooks, exam preparation materials, language testing materials. Reference to material resources also includes the physicality of school buildings and facilities, which are becoming<br/>overstretched as enrolment numbers increase. Regarding human resources, teachers in an immersion context hold a double role. Not only are they the ‘human’ resources employed to teach and prepare children and young people for their futures, as all teachers are, but immersion teachers are also the most significant ‘language resource’ through which pupils can develop their Irish language oracy and literacy. What is evidenced in the interview data<br/>is a consistent concern that these human resources are being overstretched in a number of ways and under resourced in others which includes subject specialist teachers for post-primary contexts. The matter of significant additional work to undertake as an immersion teacher is compounded by in the context of relatively new and growing sector of education for which IME tailored statutory support and recognition is yet to be fully woven into the current education system. This points to a significant risk, rather than a challenge to the IME sector.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.031 | 0.049 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.009 |
| Scholarly communication | 0.014 | 0.009 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".