MétaCan
Menu
Back to cohort

Learning by creating and exchanging objects: The SCY experience

2010· article· en· W1503803710 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBritish Journal of Educational Technology · 2010
Typearticle
Languageen
FieldComputer Science
TopicOpen Education and E-Learning
Canadian institutionsInstitute for Christian Studies
Fundersnot available
KeywordsComputer scienceProcess (computing)Mathematics educationWorld Wide WebKnowledge managementPsychology

Abstract

fetched live from OpenAlex

Abstract Science Created by You (SCY) is a project on learning in science and technology domains. SCY uses a pedagogical approach that centres around products, called ‘emerging learning objects’ (ELOs) that are created by students. Students work individually and collaboratively in SCY‐Lab (the general SCY learning environment) on ‘missions’ that are guided by socio‐scientific questions (for example ‘How can we design a CO 2 ‐friendly house?’). Fulfilling SCY missions requires a combination of knowledge from different content areas (eg, physics, mathematics, biology, as well as social sciences). While on a SCY mission, students perform several types of learning activities that can be characterised as productive processes (experiment, game, share, explain, design, etc), they encounter multiple resources, collaborate with varying coalitions of peers and use changing constellations of tools and scaffolds. The configuration of SCY‐Lab is adaptive to the actual learning situation and may provide advice to students on appropriate learning activities, resources, tools and scaffolds, or peer students who can support the learning process. The SCY project aims at students between 12 and 18 years old. In the course of the project, a total of four SCY missions will be developed, of which one is currently available.

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.

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)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.487
Threshold uncertainty score0.461

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.006
GPT teacher head0.264
Teacher spread0.258 · 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