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Co-constructing educational innovations for an uncertain future: Design thinking and developmental evaluation in the school reform process

2025· article· en· W4407723148 on OpenAlexaffabout
Elizabeth Kurucz, Emily Krysten Spencer-Mueller, Catherine Hands, Nadine Gudz, Karin Archer

Bibliographic record

VenueEvaluation and Program Planning · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicTeacher Education and Leadership Studies
Canadian institutionsLet's Talk ScienceYork UniversityWilfrid Laurier UniversityBrock UniversityUniversity of Guelph
Fundersnot available
KeywordsProcess (computing)Process managementEngineering ethicsMathematics educationEngineering managementPsychologyComputer scienceManagement scienceEngineering

Abstract

fetched live from OpenAlex

This qualitative research examines the question: In what ways does a developmental evaluation of a STEM program co-developed through a design thinking process illuminate program goal attainment? Students, parents, teachers, high school staff, school district administrators, advisory committee members, community, and college and university partners in a southern Ontario region participated in a collective effort to develop an innovative approach to STEM education in the context of the United Nations’ Sustainable Development Goals, collaboratively prototyping the concept in a design workshop, and further refining it with diverse stakeholders. Collaborators co-constructed a developmental evaluation framework to continuously learn from experimentation toward program goals. Data sources include participant observation, field notes, interviews, and document analysis. Findings highlight program strengths needed to sustain it, and challenges that threaten its longevity. The paper concludes with a program assessment based on its intended impacts and opportunities to scale a design thinking approach in education to other jurisdictions. • Design thinking and developmental evaluation are novel strategies for school reform implementation. • Collaborative educational re-imagining enables progressive curriculum innovation that meets individual and societal needs. • Developmental evaluation gives researchers, educators and policymakers new ways to evaluate and modify ongoing curriculum. • Considering depth, sustainability, spread and ownership shift possibilities assists scaling a reform from one school to many.

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 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)0.010
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.424
Threshold uncertainty score0.816

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.293
GPT teacher head0.537
Teacher spread0.244 · 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 teacher head, not a consensus.

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

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

Citations4
Published2025
Admission routes2
Has abstractyes

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