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Record W4383722445 · doi:10.21125/edulearn.2023.0278

TEACHER TRAINING ON MOBILE AND GAME-BASED LEARNING: LITERATURE REVIEW AND TRAINING PROGRAM PROPOSAL

2023· article· en· W4383722445 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEDULEARN proceedings · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicTechnology-Enhanced Education Studies
Canadian institutionsnot available
FundersFundação para a Ciência e a TecnologiaUniversity of Illinois at Urbana-ChampaignHumanitas UniversityLiverpool John Moores UniversityUniversidade de AveiroUniversity College CorkHaute école Spécialisée de Suisse OccidentaleAix-Marseille UniversitéUniversity of HertfordshireGrand Valley State UniversityUniverza v LjubljaniUniwersytet Marii Curie-SkłodowskiejKhalifa University of Science, Technology and ResearchUniversity of BristolHelsingin YliopistoFlorida Gulf Coast UniversityUniversity of AlbertaUniversity of CyprusGeorgia Southern UniversityUniversity of HuddersfieldUniversità degli Studi di MilanoUniversity of WolverhamptonSwansea UniversityCyprus University of TechnologyUniversity of Waikato
KeywordsTraining (meteorology)Computer scienceGame based learningMultimediaMathematics educationMedical educationPsychologyMedicineGeography

Abstract

fetched live from OpenAlex

Welcome to the conference proceedings of EDULEARN23. This compilation of papers and research findings were written by a diverse array of education experts and scholars who participated in the 15th EDULEARN conference, held in Palma, Spain from the 3rd to the 5th of July 2023. The conference brought together academics and researchers from the field of education to exchange knowledge, inspire new ideas and share their insights.

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)0.002
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.856
Threshold uncertainty score0.702

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.036
GPT teacher head0.362
Teacher spread0.326 · 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