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Record W4389793822 · doi:10.6007/ijarped/v12-i4/18984

Enhancing Children's Language Abilities through Gamified Teaching

2023· article· en· W4389793822 on OpenAlexaff
Mei Tingxian, Jie Gao, Loy Chee Luen

Bibliographic record

VenueInternational Journal of Academic Research in Progressive Education and Development · 2023
Typearticle
Languageen
FieldPsychology
TopicEducational Games and Gamification
Canadian institutionsEducation and Early Childhood Development
Fundersnot available
KeywordsMindsetCurriculumActive listeningMathematics educationThe InternetReading (process)PsychologyPedagogyComputer scienceWorld Wide WebCommunication

Abstract

fetched live from OpenAlex

This study adheres to the characteristics and patterns of language development in young children, guided by the "Guidelines for the Learning and Development of Children Aged 3-6." It encourages preschool teachers to actively develop and utilize language games, gamify instructional content, and create an integrated "curriculum + game" teaching model. Through the construction of an Internet-oriented mindset, preschool teachers establish a game database, enrich game content, and improve strategies such as game question design. These efforts aim to strengthen children's listening and expression skills, as well as their reading and writing abilities. By steering away from the trend of overly formalizing education for young children, the study seeks to address the drawbacks brought about by the "Teaching too much too soon" trend. The focus is on creating a seamless transition from preschool to elementary school by enhancing the cultivation of key skills in young children, facilitated through the integration of curriculum and game-based teaching methods.

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)0.003
metaresearch head score (Gemma)0.001
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 score0.665
Threshold uncertainty score0.442

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.085
GPT teacher head0.503
Teacher spread0.418 · 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 designObservational
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

Citations0
Published2023
Admission routes1
Has abstractyes

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