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Record W4391943111 · doi:10.1080/10447318.2024.2313922

Character Alive: Designing and Evaluating a Tangible System to Support Children’s Chinese Radical and Character Learning

2024· article· en· W4391943111 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

VenueInternational Journal of Human-Computer Interaction · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicChild Development and Digital Technology
Canadian institutionsSimon Fraser University
FundersNational Social Science Fund of ChinaFundamental Research Funds for the Central Universities
KeywordsCharacter (mathematics)PsychologyAestheticsCharacter developmentComputer scienceArtMathematics

Abstract

fetched live from OpenAlex

Learning to read Chinese characters poses a considerable challenge for children, particularly those with dyslexia. We designed a tangible system, named Character Alive, to assist children aged 5 to 7 in mastering Chinese radicals and characters. The system employs animations and color cues to clarify the concepts of radicals and morphemes. It also incorporates physical radical cards that work in synergy with an artificial intelligence module to facilitate stroke tracing and character composition. We conducted a two-week within-group study involving 20 six-year-old children who used both our tangible system and an equivalent multitouch version to learn Chinese radicals and characters. The results showed that both systems significantly improved the children’s accuracy in character reading and composition. However, our tangible design outperformed the multitouch variant by increasing children’s learning motivation, enabling hands-on actions, and promoting a diverse range of beneficial learning strategies. We discuss the design implications for creating effective tangible systems to facilitate Chinese language acquisition among children.

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)0.001
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 score0.826
Threshold uncertainty score0.748

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.026
GPT teacher head0.375
Teacher spread0.349 · 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