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Record W4417424863 · doi:10.1080/13632434.2025.2602874

Conceptualising innovation in education: a scoping review of implications for school leadership and change

2025· article· en· W4417424863 on OpenAlexaff
Paul Campbell, Stephen MacGregor, Nicola Sum, Sharon Friesen, Rania Sawalhi, Joan M. Conway, Dorothy Andrews, Dana Braunberger, Yui Chung Kam

Bibliographic record

VenueSchool Leadership and Management · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicTeacher Education and Leadership Studies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsWork (physics)Context (archaeology)Field (mathematics)Government (linguistics)Perspective (graphical)

Abstract

fetched live from OpenAlex

School leadership is increasingly recognised as a critical lever for driving innovation in education, yet the concept of innovation itself remains conceptually ambiguous and inconsistently enacted across contexts. This scoping review examines how innovation is conceptualised in the school leadership literature and explores its relationship to leadership and change. Drawing on 63 peer-reviewed studies published between 2014 and 2025, the review follows the PRISMA framework and employs thematic synthesis to identify key patterns and tensions. Five themes emerged: innovation as a situated and relational process; leadership as enabler, mediator, or constraint; tensions between policy and practice; conditions and cultures that support innovation; and equity, inclusion, and the politics of innovation. The findings highlight the centrality of leadership, particularly distributed and transformational models, in shaping innovation, while also revealing persistent gaps in addressing issues of equity and inclusion. The review proposes a conceptual framework that integrates these themes and underscores the need for context-sensitive, equity-focused approaches to innovation. It concludes by identifying implications for leadership development, policy coherence, and future research, particularly in underrepresented and transitional contexts. This work contributes to a more nuanced understanding of innovation as a dynamic, relational, and contested process within school leadership and educational change.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.034
metaresearch head score (Gemma)0.096
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.034
Threshold uncertainty score0.178

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0340.096
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0250.029
Science and technology studies0.0020.005
Scholarly communication0.0090.011
Open science0.0030.005
Research integrity0.0040.005
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 head0.376
GPT teacher head0.467
Teacher spread0.092 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreReview

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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