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Record W1016715629 · doi:10.5642/jhummath.201502.03

E-Brock Bugs©: An Epistemic Mathematics Computer Game

2015· article· en· W1016715629 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

VenueJournal of Humanistic Mathematics · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicMathematics Education and Teaching Techniques
Canadian institutionsBrock UniversityUniversité de Montréal
Fundersnot available
KeywordsVideo gameMathematical gameMathematics educationGame art designAvatarComputer scienceVideo game designSelection (genetic algorithm)Ideal (ethics)Combinatorial game theoryVideo game developmentMathematical proofMetagamingGame mechanicsGame designGame theorySequential gameMathematical economicsMathematicsArtificial intelligenceMultimediaHuman–computer interactionEpistemologySimultaneous game

Abstract

fetched live from OpenAlex

Devlin in [7] argues that video games are an ideal medium for the teaching and learning of mathematics, though he points out that very few ’good’ mathematics video games exist. Building on a probabilistic board game developed in the 1980s, we created a mathematics computer game, E-Brock Bugs. The design of the game carefully follows Devlin’s principles of a good mathematics video game, including a well-developed storyline, the selection of an in-game avatar, and an environment where mathematics arises in a natural and meaningful way. As a result, we argue that E-Brock Bugs is an epistemic computer game [1]; it goes beyond teaching basic facts and skills, and may encourage the players’ development of mathematical thinking as ‘working mathematicians’.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.378
Threshold uncertainty score0.714

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.120
GPT teacher head0.391
Teacher spread0.272 · 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