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Record W7020753823

MakerArcade : Using Gaming and Physical Computing for Playful Making, Learning, and Creativity

2019· article· en· W7020753823 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

VenueLancaster EPrints (Lancaster University) · 2019
Typearticle
Languageen
FieldComputer Science
TopicTeaching and Learning Programming
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsVariety (cybernetics)Physical computingCreativityStrict constructionismConstructionismProgramming by demonstrationCyber-physical system
DOInot available

Abstract

fetched live from OpenAlex

The growing maker movement has created a number of hardware and construction toolkits that lower the barriers of entry into programming for youth and others, using a variety of approaches, such as gaming or robotics. For constructionist-like kits that use gaming, many are focused on designing and programming games that are single player, and few explore using physical and craft-like approaches that move beyond the screen and single player experiences. Moving beyond the screen to incorporate physical sensors into the creation of gaming experiences provides new opportunities for learning about concepts in a variety of areas in computer science and making. In this early work, we elucidate our design goals and prototype for a mini-arcade system that builds upon principles in constructionist gaming - making games to learn programming - as well as physical computing

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.535
Threshold uncertainty score0.976

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 science0.0000.001
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 head0.020
GPT teacher head0.267
Teacher spread0.247 · 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