MétaCan
Menu
Back to cohort
Record W2010034907 · doi:10.1145/1878450.1878455

Solar scramble

2010· article· en· W2010034907 on OpenAlexaff
Ashley Rose Kelly, James R. Wallace, Katie Cerar, Neil Randall, Phillip McClelland, Amanda Mindy Seto

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicUsability and User Interface Design
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsComputer scienceProcess (computing)Key (lock)MultimediaHuman–computer interactionSoftwareWork (physics)Educational softwareDesign processWork in processEngineering

Abstract

fetched live from OpenAlex

Our experience report describes the design and development of an educational game for interactive, multi-touch tabletop displays. The game has been designed for children aged 5-10 on the SMART Tabletop platform. This experience report describes the process, design and development of our application and the implications we have drawn from this work in the design of educational technologies for interactive multi-touch tabletops. To investigate the effectiveness of our design, and to identify potential issues in deploying our software, we conducted participant interviews. Based on our design and development process, as well as our participant feedback, we have identified several key issues regarding the development of educational software for K-5 aged (5-10 years old) children on digital tabletops. This research was conducted at the University of Waterloo jointly by the Collaborative Systems Laboratory and the Critical Media Lab.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.042
Threshold uncertainty score0.139

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0420.014

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 head0.239
Teacher spread0.224 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2010
Admission routes1
Has abstractyes

Explore more

Same topicUsability and User Interface DesignFrench-language works237,207