UNLOCKING STUDENT CREATIVITY WITH LEGO® SERIOUS PLAY: A CASE STUDY FROM THE GRADUATE MARKETING CLASSROOM
Bibliographic record
Abstract
The importance of play is well established in early childhood development; however the importance of play appears to diminish in more advanced levels of education. Despite this, the demand for experiential, engaging learning experiences that seek to differentiate graduate-level programs in a fiercely competitive market continues to increase. This research sought to explore the phenomenon of bringing play and playfulness to the graduate-level classroom as a means through which to enhance creativity, student engagement, and teamwork. The LEGO® Serious Play (LSP) activity was originally created to be used as a facilitation strategy for business executives seeking to enhance innovation and business performance. This research sought to develop a protocol to adapt the LSP activity for masters’ students completing a mandatory marketing course. The primary aim of the research considered whether LSP would provide a valuable learning activity for future graduate-level marketing classes. As such, feedback was collected on the activity from students following engagement with LSP. The results of the study provide guidelines for marketing educators to seamlessly incorporate novel activities, such as LSP, into their teaching practice.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".