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Record W1583200062 · doi:10.52634/mier/2015/v5/i1/1503

Understanding the Contribution of Visual Methods to Early Childhood Research: A Cross-Cultural Investigation

2021· article· en· W1583200062 on OpenAlexaff
Joseph Seyram Agbenyega, Sunanta Klibthong

Bibliographic record

VenueMIER Journal of Educational Studies Trends & Practices · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsEducation and Early Childhood Development
Fundersnot available
KeywordsReflexivityPositivismEarly childhoodIdeologyPoliticsEpistemologySociologyEmpirical researchEarly childhood educationPhenomenonPsychologySocial sciencePedagogyPolitical scienceDevelopmental psychologyLaw

Abstract

fetched live from OpenAlex

Research in education has previously been dominated by what Law (2007) terms the “hygienic forms” (p. 33). Hygienic forms apply to positivistic quantitative traditions which claim supremacy over other forms of knowing. In this methodological paper we report on a phenomenon auto-driven visual elicitation approach of an on going research which attempts to make sense of how children (3-5 year olds) in cross-cultural settings understand risk and safety situations in their settings. We reflect on the concern for contextual reflexivity, emanating from the notion that research activity in early childhood education is “in danger of succumbing to political ideology and methodological fashion” (Prosser & Loxley, 2007, p. 1). We argue that research into early childhood education needs to acknowledge the implicit tensions between conventional empirical research and the politics of research methodology and that researchers cannot bring to the fore everything that is there to be known about child development and learning through orthodox mechanistic means. There are quotidian aspects of children's experiences, development and learning which can best be captured by visual methods that combine other approaches like interviews and observations. The paper concludes with some reflections on the ethical dilemmas and validity issues that confront the researcher when the visual and digital are used across cultures with 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.

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)0.026
metaresearch head score (Gemma)0.149
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.435
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0260.149
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0020.001
Scholarly communication0.0000.002
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 head0.863
GPT teacher head0.750
Teacher spread0.113 · 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 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
Published2021
Admission routes1
Has abstractyes

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