Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT Gamification—the use of gameplay mechanics for nongame applications—enables learning by doing, yet questions abound about its effectiveness for education. This teaching brief reports on the gamification of an entrepreneurship course using a stand‐alone gamification platform integrated with Shopify, a global e‐commerce platform for online stores. Students experienced the entire entrepreneurship process from ideation to launch of a real business and beyond. A live leaderboard allows tracking of team performance and provides a competitive element to the experiential learning. The gamification involved the creation and operation of online ventures by 269 undergraduate students during a trimester‐long undergraduate entrepreneurship course. The assessment of student learning outcomes shows that the gamified approach enhanced students’ experience, engagement, and entrepreneurial self‐efficacy. I conclude with pedagogical observations to assist instructors in implementing a gamified approach.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it