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Record W2115163316 · doi:10.1145/2037373.2037388

Exploring display techniques for mobile collaborative learning in developing regions

2011· article· en· W2115163316 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicICT in Developing Communities
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsComputer scienceMobile phoneMobile deviceMultimediaHuman–computer interactionCollaborative learningPhoneCollaborative softwareMobile technologyMobile computingContext (archaeology)World Wide WebKnowledge managementTelecommunications

Abstract

fetched live from OpenAlex

The developing world faces infrastructural challenges in providing Western-style educational computing technologies, but on the other hand observes very high cell phone penetration. However, the use of mobile technology has not been extensively explored in the context of collaborative learning. New projection and display technologies for mobile devices raise the important question of whether to use single or multiple displays in these environments. In this paper, we explore two mobile-based techniques for using co-located collaborative game-play to supplement ESL (English as a Second Language) education in a developing region: (1) Mobile Single Display Groupware: a pico-projector connected to a cell phone, with a handheld controller for each child to interact, and (2) Mobile Multiple Display Groupware: a phone for each child. We explore the types of interaction that occur in both of these conditions and the impact on learning outcomes.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.831
Threshold uncertainty score0.492

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.178
GPT teacher head0.302
Teacher spread0.124 · 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

Quick stats

Citations20
Published2011
Admission routes1
Has abstractyes

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