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Record W111364048

Dynamic concept maps as knowledge representation tools for learning

2005· dissertation· en· W111364048 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

VenueSummit (Simon Fraser University) · 2005
Typedissertation
Languageen
FieldPsychology
TopicVisual and Cognitive Learning Processes
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsRepresentation (politics)Computer scienceData scienceArtificial intelligenceMachine learningPolitical science
DOInot available

Abstract

fetched live from OpenAlex

The purpose of this thesis is to extend research on educational node-link displays with animated multimedia presentation. The thesis focuses on an empirical study of the learning effectiveness of a dynamic concept map synchronized with audio presentation. 133 undergraduates, who were randomly assigned to four groups, participated in this experiment. The two experimental groups viewed plain and graphically enhanced concept maps that were semantically equivalent to the narration. These animated concept maps were synchronized with the audio track. The two control groups viewed text versions of the narration, one synchronized with the audio track and another version preceding the audio track. All visual presentations were incremental and cumulative. Both map groups outperformed the text groups on a free recall test. The plain map group outperformed the text groups on a comprehension test. Implications of this work are discussed with respect to cognitive and multimedia theories of learning.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.855
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
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.028
GPT teacher head0.333
Teacher spread0.305 · 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