MétaCan
Menu
Back to cohort
Record W7058142154

Linking Theory and Practice: A Structured Approach to Developing Subject Expertise and Professional Skills in Higher Education

2025· other· en· W7058142154 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueSunderland Repository (University of Sunderland) · 2025
Typeother
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsSubject (documents)CurriculumFlexibility (engineering)Professional developmentHigher educationVocational educationBest practiceSession (web analytics)
DOInot available

Abstract

fetched live from OpenAlex

This session presents the FES Subject Passports initiative, originally developed for teacher training but adaptable to other profession-facing programmes, such as nursing, social work, and engineering. The initiative bridges theoretical knowledge with practical application, ensuring students not only gain subject expertise but also develop the professional skills necessary for success in their fields. This approach aligns with debates in higher education on curriculum integration, employability, and the development of transferable skills (Schleicher, 2018; Tight, 2023). By offering subject-specific frameworks, the initiative supports the development of both subject mastery and pedagogical competence, ensuring students are well-prepared for professional practice. The FES Subject Passports were developed in response to the need for higher education programmes to prepare graduates for the workforce, as outlined in the UK’s Industrial Strategy (Department for Business, Energy & Industrial Strategy, 2017). This initiative draws on Eraut’s (2004) work, which highlights the importance of integrating theory with practice in professional education. Research indicates that when academic learning is applied in real-world scenarios, students are better equipped for professional roles (Brockbank & McGill, 2007). The success of the FES Subject Passports pilot, particularly in the development of the English Language Passport, demonstrates the effectiveness of structured, subject-specific resources in enhancing student learning and fostering professional confidence (Ofsted, 2024). The Passport initiative initially addresses the challenges of delivering education in the diverse FES sector, which spans subjects ranging from English and Mathematics to vocational courses like automotive engineering and equine studies. The flexibility of the FES Subject Passports allows mentors to contextualise theoretical knowledge, making it relevant to specific subject areas and professional practice, a feature supported by studies on practice-based education (Eraut, 2007). This makes the Passport model adaptable to other professional disciplines, such as nursing, social work, and engineering, ensuring a broader applicability across higher education. This session will show participants how the FES Subject Passports model and approaches to deliberate-practice (Ericsson, 2008; Christodoulou, 2017; Ericsson, 2019) can be adapted for use in various profession-facing degree programmes, supporting the achievement of Sustainable Development Goal (SDG) 4 (Quality Education) by improving the quality of education and SDG 10 (Reduced Inequalities) by ensuring equitable support for diverse learners. By linking curriculum design with professional practice and employability, the initiative ensures that all learners have access to the tools necessary to succeed. Participants will leave the session with an actionable plan for implementing subject-specific frameworks within their own disciplines. Through an interactive component, attendees will begin developing their own version of a subject passport, enabling them to apply the principles of subject mastery and professional skills development in their specific educational contexts.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.533
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.012
GPT teacher head0.261
Teacher spread0.249 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it