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Record W7132928208

Epistemic agency and pervasive knowledge building in a grade two classroom: examining the potential of handhelds in collaborative inquiry

2004· dissertation· W7132928208 on OpenAlexaff
Latika Nirula

Bibliographic record

VenueTSpace · 2004
Typedissertation
Language
FieldSocial Sciences
TopicEducation and Technology Integration
Canadian institutionsBibliographical Society of Canada
Fundersnot available
KeywordsAffordanceAgency (philosophy)Control (management)Mobile deviceKnowledge creationNetworked learningMental model
DOInot available

Abstract

fetched live from OpenAlex

The central goal of this thesis is to engage students in new pedagogies that enable them to take control of their own knowledge advancement and allow such pursuit to pervade all aspects of mental life. This study describes a design experiment examining the use of handheld computers in a grade two knowledge-building classroom. Specifically, the focal problem under investigation asks, how can the technological affordances of inexpensive handhelds be directed towards the support of pervasive knowledge building and epistemic agency? Researcher observations are documented over a six-week period as a number of innovations utilizing collaborative inquiry are designed for use within a technologically enriched grade two classroom (N = 22). Findings suggest that handhelds can be an effective technological assist in the knowledge-building classroom and there is some evidence to suggest that handhelds may have a role in fostering epistemic agency. Implications of these findings for computer-supported collaborative learning environments are explored.

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)0.010
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 score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0040.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.043
GPT teacher head0.414
Teacher spread0.371 · 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".

Quick stats

Citations0
Published2004
Admission routes1
Has abstractyes

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