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Record W7137994443 · doi:10.21606/iasdr.2025.73

Failing through Play: Integrating Iterative Design Methods to Foster Creativity in Primary Education

2025· article· W7137994443 on OpenAlexaff
Fernanda Luiza Fontes, Wonjoon Chung

Bibliographic record

Venuenot available
Typearticle
Language
FieldArts and Humanities
TopicArt Education and Development
Canadian institutionsCarleton University
Fundersnot available
KeywordsCreativityIterative and incremental developmentQualitative researchPrimary educationTeaching methodConstruct (python library)Iterative method

Abstract

fetched live from OpenAlex

Creativity is one of the essential skills to navigate the complexities of the 21st century. In this exploratory research, we investigate how design can enhance current pedagogical methods in primary education to foster creativity in problem-solving activities. Using a case study method, we conduct semi-structured interviews with educators to understand their approaches, motivations, and the barriers they face when employing these activities in their classrooms. We also verify the iterative methods currently incorporated into these activities. Our analysis suggests that crucial elements of the design creative process, such as iteration and problem-finding, are often overlooked. Furthermore, the concept of “iteration” itself is not widely understood in the education field. These findings led us to propose a conceptual framework that integrates play and iterative design methods into primary education, making problem-solving and learning process more enjoyable and minimizing feelings of frustration that often arise from failure. Although the results are not conclusive, these finding suggests promising directions for further investigation and provide insights that can contribute to existing definitions of design and creativity in education.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.656
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.077
GPT teacher head0.388
Teacher spread0.311 · 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.

Study designQualitative
Domainnot available
GenreMethods

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

Citations0
Published2025
Admission routes1
Has abstractyes

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