Digital Literacy and Public Pedagogy: Notes on the Digital Game as a Form of Literacy and Learning
Bibliographic record
Abstract
Digital games are both an exponent and a vehicle of cultural transformation. Not only do they form a rapidly growing part of the popular culture industry, they also instigate transformations in other cultural domains such as education. Played in a multi-player fashion, online digital games engender new forms of social relationships and new forms of shared participation in cultural literacy and modes of learning. As games are used for instructional purposes in schools, industry, and the army or airforce for training purposes, the playing of games is no longer constricted to a sphere outside normal adult life but forms part of the "serious" world of production and consumption, knowledge, and education. This suggests that digital technologies may have changed the characteristics and cultural significance of learning and what it means to be literate-not to mention the nature of play itself. This significance may be broader than the acquisition of cognitive skills. Through the act of play, computer games prepare and "train" the general public for a "culture of real virtuality" in which we require digital literacy skills for decoding and understanding media simulations in our environment and how to relate to them as public forms of learning or public pedagogy. Digital games constitute a strategic research site because they exemplify the transformations in perception and participation that are characteristic for digital culture of learning and literacy. Digital games as a form of digital literacy enact a public pedagogy through a means of educational and cultural transformation. About the Author Peter Trifonas is a professor of Social and Cultural Studies in Education at the Ontario Institute for Studies in Education, the University of Toronto. He is the author of Revolutionary Pedagogies, Pedagogies of Difference, and Ethics, Institutions, and the Right to Philosophy (with Jacques Derrida), and The Ethics of Writing among other books.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.033 |
| Scholarly communication | 0.012 | 0.014 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".