Creativity in Motion: Examining the Creative Potential System and Enriched Movement Activities as a Way to Ignite It
Bibliographic record
Abstract
In a global and highly competitive world, the importance of creativity is increasing as it supports adaptability, health, and actualization. Yet, because most research focuses on what it takes to produce creative artifacts, interventions supporting growth in creative potential remains underexplored. To address this limitation, the first goal of this paper is to review the creativity science literature to identify the elements that underpin the realization of an individual's creative potential. The summary of the literature is presented using a framework which highlights the interactions between environmental elements (i.e., cultural values, social interactions, and material world) and actors' elements (i.e., affective attributes and states, cognitive skills, and physical expression). Using a systemic perspective, the framework illustrates 'what' creativity enhancement interventions should aim for, to facilitate the emergence of creative actions. Given the current lack of holistic, embodied, and interactive evidence-based interventions to nurture the creative potential elements identified, the second part of this review builds on movement sciences literature and physical literacy conceptualization to suggest that enriched movement activities are promising avenues to explore. Specifically, following non-linear pedagogy approaches, an intervention called movement improvisation is introduced. Ecological dynamics principles are used to explain how improvising with movement in a risk-friendly environment can lead to cognitive, affective, social, and cultural repertoire expansion. To interrogate this argument further, the review concludes with possible solutions to withstand research challenges and raises future study questions. Overall, combining creativity and movement sciences in this review demonstrates the potential for well-designed movement interventions to ignite creative potential for individuals and overcome the tendency to remain anchored in a state of inertia.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
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".