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Record W4400441972 · doi:10.55016/ojs/ajer.v52i3.55153

Using Think Alouds, Think Afters, and Think Togethers to Research Adolescents’ Inquiry Experiences

2006· article· en· W4400441972 on OpenAlexaffvenueabout
Jennifer Branch

Bibliographic record

VenueAlberta Journal of Educational Research · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Critical Thinking Development
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPsychologyPedagogyEducational researchMathematics education

Abstract

fetched live from OpenAlex

This article presents three research methods—Think Alouds, Think Afters, and Think Togethers—as ways of gathering data to describe the experiences of adolescents during instructional activities. These verbal report methods were used in two studies that examined the information-seeking processes of adolescents in Inuvik, Northwest Territories and Beaumont, Alberta. The first study revealed that participants needed both mediation (instruction and support) and practice to develop the skills and strategies needed for full-text searching of electronic encyclopedias. The second study revealed that students needed mediation (instruction and support) throughout an inquiry-based learning experience and that using Kuhlthau’s (1993) Information Search Process model as a guide for cognitive and affective mediation was useful. The Think Alouds, Think Afters, and Think Togethers allowed the researcher to collect data about the adolescents’ experiences of information-seeking; the data-gathering processes also provided the participants with a deeper understanding of their own experiences of instructional activities. I conclude the article with recommendations to enhance researchers’ use of verbal report methods with adolescents.

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)0.008
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.148
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.223
GPT teacher head0.500
Teacher spread0.277 · 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 designQualitative
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

Citations21
Published2006
Admission routes3
Has abstractyes

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