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Record W2756801394 · doi:10.19173/irrodl.v18i6.3093

Evaluation of Student Learning in Remotely Controlled Instrumental Analyses

2017· article· en· W2756801394 on OpenAlex
Chris Meintzer, Frances Sutherland, Dietmar Kennepohl

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.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueThe International Review of Research in Open and Distributed Learning · 2017
Typearticle
Languageen
FieldEngineering
TopicExperimental Learning in Engineering
Canadian institutionsAthabasca UniversityNorthern Alberta Institute of Technology
Fundersnot available
KeywordsRemote laboratorySet (abstract data type)Class (philosophy)PerceptionPsychologyComputer scienceMathematics educationMultimediaThe InternetWorld Wide WebArtificial intelligence

Abstract

fetched live from OpenAlex

<p class="3">The Canadian Remote Sciences Laboratories (CRSL) website (<a href="http://www.remotelab.ca">www.remotelab.ca</a>) was successfully employed in a study of the differences in the performance and perceptions of students’ about their learning in the laboratory (in-person) versus learning at a remote location (remote access). The experiment was completed both in-person and via remote access by 70 students, who performed essentially the same, academically, in the two modes. One set of students encountered the in-person laboratory first and then did the remote laboratory, while the other set of students did the activities in the reverse order. The student perception survey results (n = 46) indicated that the students found both experimental scenarios to be at appropriate levels of difficulty, clear to understand, and did not overall prefer one way of completing the experiment over the other. However, they felt that they learned more about the theory of the experiment, more hands-on skills, and more about the operation of the instrument when they performed the experiment in the laboratory in the presence of an instructor. They also believed that they learned more about the instrument operation from their laboratory partner when they completed the experiment in the laboratory, but learned more from their partner about the operation of the instrument software when they completed the procedure from a remote location.</p>

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)0.010
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.104
Threshold uncertainty score0.433

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.189
GPT teacher head0.521
Teacher spread0.331 · 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