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Record W4401718405 · doi:10.21432/cjlt28177

Virtual Labs for Postsecondary General Education and Applied Science Courses: Faculty Perceptions

2024· article· en· W4401718405 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.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCanadian Journal of Learning and Technology · 2024
Typearticle
Languageen
FieldEngineering
TopicExperimental Learning in Engineering
Canadian institutionsDurham CollegeGeorge Brown College
Fundersnot available
KeywordsFocus groupAffordanceCurriculumScience educationMedical educationVirtual learning environmentFaculty developmentMathematics educationVocational educationPerceptionPsychologyComputer sciencePedagogyProfessional developmentSociologyMedicine

Abstract

fetched live from OpenAlex

General education science courses at a Canadian postsecondary institution implemented Beyond Labz virtual science labs. Faculty members teaching vocational science-related courses tested this resource. This qualitative study explores faculty member and learner perceptions of the efficacy of these virtual labs in terms of ease of use, designing hands-on activities, student engagement, and accessibility. Data are collected via a focus group, surveys, meetings, and interview notes. The study found that learners and faculty members may have different perceptions of the importance of virtual labs for the development of various skills. From the data, five themes emerge related to addressing the needs of diverse learners and utilizing multiple affordances of virtual labs. Although science virtual labs are perceived as a useful tool for teaching and learning science, faculty members identify barriers such as the need to develop digital literacy skills and initial training and institutional support when introducing new tools. Recommendations for effective science virtual labs curriculum integration are included.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.773
Threshold uncertainty score0.332

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.004
GPT teacher head0.244
Teacher spread0.240 · 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