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Record W2183593220

Exploring Evolutionary Concepts with Immersive Simulations

2013· article· en· W2183593220 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

VenueComputer Supported Collaborative Learning · 2013
Typearticle
Languageen
FieldPsychology
TopicAnimal and Plant Science Education
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsComputer scienceVariation (astronomy)CurriculumEmbodied cognitionKey (lock)Space (punctuation)Human–computer interactionField (mathematics)MultimediaArtificial intelligencePsychologyPedagogyMathematics
DOInot available

Abstract

fetched live from OpenAlex

This paper presents two iterations of our design of an immersive simulation and inquiry activity for exploring evolutionary concepts in a Grade 11 Biology course. Interacting with large projected displays of animated rainforest flora and fauna, students worked as field researchers to observe changes in life forms occurring over a 200 million year span. Students gathered evidence of evolution using networked tablet computers that scaffolded their interactions with peers and with the room itself. Improvements from the first to the second design iteration focused on (1) improving content-focused interactions within the simulation; (2) improving the integration of the simulation activity into the overall curriculum; (3) improving embodied interactions of students working within the physical space. Student explanations from the second implementation demonstrated increased variation in evolutionary topics compared to those in the first iteration. Key design features from the two iterations are discussed with respect to the observed interaction patterns.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.253
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.059
GPT teacher head0.310
Teacher spread0.250 · 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