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Record W2733310550 · doi:10.18747/phsg-coll3/id/482

Using structural domain and learner models to link multiple data sources for learning analytics

2017· article· en· W2733310550 on OpenAlexaboutno aff
Michael Kickmeier-Rust, Dietrich Albert

Bibliographic record

VenueDas Repository der Padagogischen Hoschule St. Gallen (Padagogischen Hoschule St. Gallen) · 2017
Typearticle
Languageen
FieldComputer Science
TopicIntelligent Tutoring Systems and Adaptive Learning
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceDomain (mathematical analysis)AnalyticsData analysisLearning analyticsData scienceLink (geometry)Artificial intelligenceData miningMathematicsComputer network

Abstract

fetched live from OpenAlex

Joint Proceedings of the Sixth Multimodal Learning Analytics (MMLA) Workshop and the Second Cross-LAK Workshop, 14 March 2017, Vancouver, Canada, pp. 82-88

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 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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.588
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0060.000
Scholarly communication0.0040.005
Open science0.0070.006
Research integrity0.0010.002
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 head0.174
GPT teacher head0.357
Teacher spread0.183 · 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; both teacher heads agree on what is shown here.

Study designSimulation or modeling
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

Citations2
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueDas Repository der Padagogischen Hoschule St. Gallen (Padagogischen Hoschule St. Gallen)Same topicIntelligent Tutoring Systems and Adaptive LearningFrench-language works237,207