A Report on a Pilot Study into Using Coaching to Support ‘Sixth Form’ Students (Aged 16 to 18) in England
Bibliographic record
Abstract
Abstract This article presents findings from an early-stage pilot study investigating how coaching can support students aged 16–18 in England. As part of a wider comparative project involving England and Canada, this first paper focuses on the English context, drawing on semi-structured interviews with two students at a sixth form college in the East Midlands region of the United Kingdom. The study examines how coaching influences learning strategies, motivation, confidence, and overall well-being during the critical two-year stage between the General Certificate in Secondary Education (GCSE) exams at age 16 and A-Level exams at age 18. Sixth form students face high-stakes assessments alongside increased autonomy and responsibility for their learning. Coaching, distinguished from traditional mentoring or tutoring by its emphasis on questioning, reflection, and goal-setting, offers a structured yet personalized approach to supporting academic and personal development. Findings from the pilot indicate that coaching positively impacted students’ attainment by fostering self-assessment, and practical study strategies, while also enhancing confidence, self-efficacy, and resilience. Participants highlighted coaching as a mechanism for stress management, workload planning, and coping with the pressures of study. Additionally, peer-led support emerged as a potentially effective model to strengthen engagement, belonging, and motivation. This study contributes to the growing evidence that coaching can enhance both academic outcomes and personal well-being, suggesting that embedding coaching within sixth form practice may foster a culture of reflective learning, empowerment, and sustained student success.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".