Bibliographic record
Abstract
With the belief that teaching design, innovation and entrepreneurship studies requires methods and techniques that are themselves innovative and entrepreneurial in nature, LEGO® SERIOUS PLAY™ (LSP) has been used within the Technology Management and Entrepreneurship (TME) Program at the University of New Brunswick, Faculty of Engineering, as a complementary instructional technique since 2005. LSP is a creative and experiential process that can facilitate strategic planning, problem solving, team building, and innovation mining through the use of specialized LEGO® brick kits. Designed for the corporate environment, it made its formal debut in 2002. Since then, over 250 global organizations, in 27 countries have used this facilitated thinking technique. Example companies that offer enthusiastic testimonials for the methodology include Daimler/Chrysler, Verizon Wireless, Ikea, and Pfizer. LSP is now emerging in the educational environment. The current generation of students, before becoming gripped to electronics, was encouraged by parents to use their hands and imaginations to construct models using LEGO® bricks. They were at one time ‘Imagineers’. In addition, engineering students tend to work hard and play harder. Thus it became desirable to test how introducing the element of play [1][2] with purpose into the Entrepreneurship and Design classrooms could awaken students’ creative energies that spur innovation. “Constructivism” [3] has been increasingly emphasized as an effective approach to learning. Also, the related “Constructionist” theory suggests that by using our hands and 3D modeling to explore ideas we can surface more information, past experience, intuition and understanding than we can effectively express through speech alone. Based on the promising LSP initial TME pilot results in 2006, it was predicted that Engineering students as a whole could further benefit from the LSP experience and use this form of concrete thinking to solve design/innovation challenges and teaming issues. The LSP pilot action research was extended in collaboration with graduating Civil Engineering students in their Team Capstone Design Course winter 2008. Lego based (LSP) workshops subsequently conducted demonstrated a positive impact on the design teams with respect to their views on team responsibility and accountability, ability to collaborate and cooperate as well as their awareness of team risks and responsibilities over those teams with no LSP workshop experience.
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 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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.016 | 0.004 |
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".