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‘Geoliteracy’, ‘Cartology’, Cognitive Development, and a Mobile Game

2018· article· en· W3091627005 on OpenAlexaff
Yaïves Ferland

Bibliographic record

VenueAnekumene · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicGeography Education and Pedagogy
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsGeospatial analysisCognitive mapContext (archaeology)Reading (process)CurriculumCourseworkSpatial intelligenceExperiential learningComputer scienceMathematics educationCognitionPsychologyCartographyGeographyPedagogyArtificial intelligence

Abstract

fetched live from OpenAlex

Some researches in education science develop educative games on mobile devices for letting elementary school students play outdoor to learn geographic facts, concepts, and patterns. The challenge is about improving their geographic literacy and fluency, or ‘geoliteracy’, and their map-reading competencies, called cartology, before adolescence. There a critical stumbling ‘threshold’ can impede their geospatial cognitive development, which result in a majority of adults being not geographically literate neither efficient, in real-life context, for reading and using maps. Designing a mobile educative serious game implies applying conceptual and pragmatic methods for both learning and teaching geospatial competencies accordingly to school curriculum. The theoretical framework presented links maps to cartographical semiology, the children’s cognitive development stages for geospatial representation, and an experiential learning cycle model. The latter sequentially supports three main cartographic processes of map-making: reflexive visualization, and map-reading, which sustain any geographical reasoning. The mobile game proposed combines components of increasing complexity where the map plays the main role in the course of different activities: scenarios of typical “rounds” and rules of the game within local terrain; types of geometrical and geospatial trajectories to trace and follow while playing; and specific themes relevant to school subjects. Thus, geographical discussions stop worrying about where, to worry about the reason of situations and the occurrence of phenomena.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.920
Threshold uncertainty score1.000

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)0.0010.000

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 head0.030
GPT teacher head0.386
Teacher spread0.356 · 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.

Study designNot applicable
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
Published2018
Admission routes1
Has abstractyes

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