Connecting creativity, technology, and communities of practice: Exploring the efficacy of technological tools in support of creative innovation
Bibliographic record
Abstract
Creativity is increasingly becoming both an important issue in our rapidly changing society, and a popular subject of research. Research findings are beginning to conceptualize creativity as a much more complex process and studies are now focusing on the effects of social interaction and collaborative efforts on creativity as well as the potential impact of technology on collaboration and the creative process itself.\n\t\nThis study looks at the influence of both collaboration and technology on the creative process to develop a clearer picture of the way in which they intersect. Due to the complexity of this study, two theoretical frameworks (Communities of Practice and Genex Framework) have been employed to inform the development of the study and to assist in contextualizing the results.\n\nTo this end, this mixed-methods study collected data both from fashion design students enrolled in the third year of a Bachelor of Fashion Design program, and from their faculty. Data gathering methods included personal semi-structured interviews with both students (n = 13) and faculty (n = 9) and an online questionnaire with a larger group of students (n = 65).\n\nThe research questions that framed this study focus on developing an initial understanding of the creative process as experienced by these students and then exploring in depth the ways that collaboration and working in community affect the creative process, as well as the impact of technology in supporting both creativity and collaboration.\n\nResults suggest that technology was indeed a valuable support in the creative process through its ability to facilitate particular kinds of collaborative practices, including brainstorming, developing and sharing ideas, and giving and receiving feedback. Such practices directly affected the creative process by enhancing the development of more professional sketches as well as facilitating the collaborative efforts of the members of the design community.\n\nFinally, the implications of these results for curriculum design and the appropriate choice of pedagogical approaches are discussed. The results presented will help to support curriculum designers and instructors who seek to encourage creative endeavour to focus on effective technological tools as well as strategies that promote collaboration and a sense of community in order to achieve these ends.
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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 | 0.022 | 0.081 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".