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Record W4399195372 · doi:10.1017/9781009253994.008

Emoji in General Education

2024· book-chapter· en· W4399195372 on OpenAlexaff
Omonpee W. Petcoff, Janice C. Palaganas, Marcel Danesi

Bibliographic record

VenueCambridge University Press eBooks · 2024
Typebook-chapter
Languageen
FieldComputer Science
TopicDigital Communication and Language
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEmojiComputer scienceWorld Wide WebSocial media

Abstract

fetched live from OpenAlex

Using both the Petcoff and Palaganas studies as a point of departure, this chapter looks at the more general educational implications of bringing emoji into pedagogical practices. The underlying premise is that emoji not only are highly understandable images, aiding learning but also can create a positive environment, making teaching and interaction congenial and open to all learners, no matter their backgrounds or learning capacities, since emoji give them an equal voice. Emoji allow for a destigmatized approach, especially for disadvantaged learners who might not be able to adequately speak for themselves. Emoji are a psychological conduit that can easily open up lines of interaction to virtually everyone. Once this is achieved, any subject matter, from English to mathematics, can be imparted broadly through any type of learning style.

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 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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.987
Threshold uncertainty score0.923

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 science0.0010.001
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 head0.018
GPT teacher head0.215
Teacher spread0.197 · 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 teacher head, not a consensus.

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

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

Citations0
Published2024
Admission routes1
Has abstractyes

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