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Record W2568220302 · doi:10.5539/jel.v6n2p155

Process-Oriented Measurement Using Electronic Tangibles

2017· article· en· W2568220302 on OpenAlexvenueno aff
Jochanan Veerbeek, Janneke Verhaegh, Wilma C. M. Resing

Bibliographic record

VenueJournal of Education and Learning · 2017
Typearticle
Languageen
FieldPsychology
TopicInnovative Teaching and Learning Methods
Canadian institutionsnot available
Fundersnot available
KeywordsTask (project management)Process (computing)Measure (data warehouse)Computer scienceRestructuringInformation gapRepresentation (politics)PsychologyData mining

Abstract

fetched live from OpenAlex

This study evaluated a new measure for analyzing the process of children’s problem solving in a series completion task. This measure focused on a process that we entitled the Grouping of Answer Pieces (GAP) that was employed to provide information on problem representation and restructuring. The task was conducted using an electronic tangible interface, to allow for both natural manipulation of physical materials by the children, and computer monitoring of the process. The task was administered to 88 primary school children from grade 2 (M=8.2 years, SD=0.50). GAP was a moderate predictor of accuracy on the series completion task. Averaged over multiple items, GAP, verbalizations and time measures were related to accuracy. On an item level, however, GAP was the only process measure related to item solving success, and this relationship was mediated by item difficulty. Further research is needed to investigate the precise relationship between problem solving and GAP.

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)0.004
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.025
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
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 head0.086
GPT teacher head0.459
Teacher spread0.373 · 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 designBench or experimental
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

Citations5
Published2017
Admission routes1
Has abstractyes

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