MétaCan
Menu
Back to cohort
Record W2029763320 · doi:10.1145/1054972.1055089

Testing the media equation with children

2005· article· en· W2029763320 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
FieldSocial Sciences
TopicChild Development and Digital Technology
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsPraiseStructural equation modelingSocial mediaSoftwareValue (mathematics)Computer sciencePsychologySocial psychologyWorld Wide Web

Abstract

fetched live from OpenAlex

Designers of children's technology are often more interested in user motivation than those who design systems for adults. Since children's technology often has aims such as education or practice, keeping the user engaged and interested is an important objective. The Media Equation - the idea that people respond socially to computers - shows potential for improving engagement and motivation. Studies have shown that people are more positive about both themselves and the computer when software exhibits certain social characteristics. To explore the possible value of the Media Equation as a design concept for children's software, we replicated two of the original Media Equation studies, concerning the effects of praise and team formation. Our results, however, were contrary to our expectations: we did not find evidence that children were significantly affected by social characteristics in software, and adults were influenced in only a few cases. These results raise questions about using the Media Equation as a design principle for children's software.

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: none
Teacher disagreement score0.726
Threshold uncertainty score0.173

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 science0.0000.000
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 head0.044
GPT teacher head0.267
Teacher spread0.223 · 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

Citations28
Published2005
Admission routes1
Has abstractyes

Explore more

Same topicChild Development and Digital TechnologyFrench-language works237,207