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Record W2765274651

A Micro-View on Children's Shared Thinking on Questions Forming

2007· article· en· W2765274651 on OpenAlexaboutno aff
Peilan Chen, Wolff-Micheal Roth, Yuhtsuen Tzeng

Bibliographic record

VenueeScholarship (California Digital Library) · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Critical Thinking Development
Canadian institutionsnot available
FundersNational Science Council
KeywordsContext (archaeology)PsychologyCurriculumCognitionPedagogySocial psychologySociology
DOInot available

Abstract

fetched live from OpenAlex

A Micro-View on Children’s Shared Thinking on Questions Forming Peilan Chen (crossingthebartw@yahoo.com.tw) Institute of Curriculum Studies, National Chung Cheng University, 168, University Rd., Min-Siung, Chia-Yi, Taiwan Wolff-Michael Roth (mroth@uvic.ca) Applied Cognitive Science, University of Victoria, MacLaurin Building A548, V8W 3N4, Victoria, BC, Canada Yuhtsuen Tzeng (ttcytt@ccu.edu.tw) Center for Teacher Education & Institute of Curriculum and Instruction, National Chung Cheng University, Taiwan Keywords: microgenetics; interaction analysis questions forming process; Introduction When individuals ask questions, they really are performing speech acts in social contexts. A theory of questioning in naturalistic settings therefore must address this pragmatic level of discourse (Graesser & Murachver, 1985). In the current study, we take a close look at children’s collective processes of generating questions as a form of task designed to lead to deep learning and understanding. Such a theory should allow us to increase the ecology validity of theory of questioning. Shared Editing of Final Questions Shared editing of the questions children ultimately construct serves as a context that scaffolds children in their thinking, provides explanations to exchange individual understanding, and promotes children to justify or rethink candidate questions that should go on record. Discussions Research Design Questioning Derives from an Assumption That Leads Individual to Make Cognitive Decision Constraints offer a way of decreasing the cognitive load of individuals and facilitate children’s engagement in the search and identification of relevant knowledge. Questioning Functions as Accommodation/ Assimilation The videotaped interactions of the shared production of questions provide empirical evidence for demonstrating children’s agency in learning and represent how individual conducts accommodation and assimilation to extend their knowledge. Questioning Is an Evolutionary and Reciprocal Social Process Questioning is not a linear process. It is a social process similar with other cognitive process (e.g. designing, Roth, 2001). The dynamics of questioning reflect on children’s social editing, which promotes children concept evolution and creates a concise product. Research Context and Data Sources Enacting the precepts of a microgenetic method (e.g. Kuhn, 2002), we videotaped 2 nd , 4 th , and 6 th grade children’s interactions in questioning generating tasks over multiple sessions to observe the question generation. Data Analysis Children’s conversations were transcribed preliminarily to conduct interaction analysis (Jordan & Henderson, 1995). After reading the transcripts, we make a tentative claim, and then we discussed and reviewed other episodes to check whether our claims represent our data. Based on continually check, discussion and revision, we formulate current three claims representative of our data. Acknowledgements Results National Science Council in Taiwan Activating Questions Constraints Children on their own and with their peers construct constraints to allow some types of questions and exclude others. Activating constraints not only avoids group members’ thoughts deviating from chosen central focus, but also implies hidden assumptions about some specific perspective. Creating Candidate Questions Our study reveals that the point inconsistent or comparable with what children know is a possible start to create a candidate question. References Graesser, A. C., & Murachver, T. (1985). Symbolic procedures of question answering. In A.C. Graesser & J. B. Black (Eds.), The psychology of questions (pp.15-82). Hillsdale, NJ: Lawrence Erlbaum Associates. Jordan, B., & Henderson, A. (1995). Interaction analysis: Foundations and practice. Journal of the Learning Sciences, 4, Kuhn, D. (2002). What is scientific thinking and how does it develop? In U. Goswami (Eds.), Blackwell handbook of childhood cognitive development. Oxford: Blackwell Publishers. Roth, W.-M. (2001). Modeling design as situated and distributed process. Learning and Instruction, 11, 211-239.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0020.007
Scholarly communication0.0030.005
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.020
GPT teacher head0.280
Teacher spread0.260 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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".

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Citations0
Published2007
Admission routes1
Has abstractyes

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