Beyond gamification: reconceptualizing game-based learning in early childhood environments
Bibliographic record
Abstract
<p>The recent promotion and adoption of digital game-based learning (DGBL) in K-12 education presents compelling opportunities as well as challenges for early childhood educators who seek to critically, equitably and holistically support the learning and play of today's so-called digital natives. However, with most DGBL initiatives focused on the increasingly standardized ‘accountability’ models found in K-12 educational institutions, the authors ask whose priorities, identities and notions of play this model reinforces or neglects. Drawing on the literatures of early childhood studies, game-based learning, and game studies, they seek to illuminate the <em>informal</em> contexts of play within the ‘hidden’ and ‘null’ curricula of DGBL that do not fit within the efficiency models of mainstream education in North America. In the absence of a common critical or theoretical foundation for DGBL, they propose a conceptual framework that challenges what they regard to be the institutionally nullified dimensions of <em>autonomy, play, affinity</em> and <em>space</em> that are essential to DGBL. They contend that these dimensions are ideally situated within the inclusive and play-based curriculum early childhood learning environments, and that the early years constitute a critically significant, yet overlooked, location for more holistic and inclusive thinking on DGBL.</p>
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How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".