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Remote Teaching Laboratories in Science and Engineering

2009· book-chapter· en· W2787309639 on OpenAlexaff
Dietmar Kennepohl

Bibliographic record

VenueIGI Global eBooks · 2009
Typebook-chapter
Languageen
FieldEngineering
TopicExperimental Learning in Engineering
Canadian institutionsAthabasca University
Fundersnot available
KeywordsPracticumRemote laboratoryComputer scienceRemote controlEngineeringEngineering managementThe InternetElectrical engineeringMathematics educationWorld Wide WebPsychology

Abstract

fetched live from OpenAlex

For scientists and engineers, the idea of remote controlled experiments is not a new. Remote control is often used when an experiment or instrument is physically inaccessible by virtue of location or danger. It is also an excellent method for sharing expensive equipment and facilities with other researchers. However, employment of remote laboratory access to deliver the practicum components of distance science courses is much more recent and certainly not as common. Historically, the complexity and technology involved has often dissuaded universal adoption of this method in regularly run laboratory courses. However with the increasing availability and robustness of new technologies, the use of remote laboratories is being explored by many distance educators in the sciences as a viable method of offering a first-class laboratory experience for the student.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.986
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.005
GPT teacher head0.215
Teacher spread0.210 · 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 teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreOther

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
Published2009
Admission routes1
Has abstractyes

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