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Live Long and Educate

2021· book-chapter· en· W4200404053 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAdvances in game-based learning book series · 2021
Typebook-chapter
Languageen
FieldPsychology
TopicEducational Games and Gamification
Canadian institutionsDalhousie University
Fundersnot available
KeywordsDebriefingRubricSituatedComputer scienceConstructivism (international relations)Mathematics educationPsychologyMultimediaArtificial intelligenceSocial psychologyPolitical science

Abstract

fetched live from OpenAlex

Using the lenses of Vygotskian constructivism, situated cognition, the antecedents of flow, and a pedagogy interwoven with the multiliteracy framework, the authors present a COVID-19 simulation game. The game has multiple levels, challenges, disrupters, and allows for student player groups to work together (i.e., collaborate within and across player groups) to achieve the strategic objectives of the game. The player groups have an overall goal to minimize loss of life, while other parameters need to be optimized, depending on the stakeholder group that the player group is role-playing. While the game can be digitized, it is presented in a manner that allows instructors to implement the game simulation right away in their classrooms. Assessment rubrics, decision matrix templates, and debriefing notes are provided to allow for student learners to reflect on their decisions (based on course concepts) both individually and as a player group.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.987
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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.

Opus teacher head0.014
GPT teacher head0.300
Teacher spread0.286 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it