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Record W3199622825 · doi:10.5430/ijhe.v10n7p96

Evidence-Based Course Modification to Support Learner-Centered and Student-Driven Teaching in A Pandemic: Leveraging Digital and Physical Space for Accessible, Equitable, and Motivating Experiential Learning and Scientific Inquiry in A First-Year Biology Course

2021· article· en· W3199622825 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.

Bibliographic record

VenueInternational Journal of Higher Education · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicInnovative Teaching Methods
Canadian institutionsUniversity of GuelphYork University
Fundersnot available
KeywordsExperiential learningPandemicSpace (punctuation)Active learning (machine learning)Course (navigation)Instructional designCoronavirus disease 2019 (COVID-19)Teaching methodMathematics educationEducational technologyExperiential educationVirtual learning environmentMedical educationPsychologyComputer sciencePedagogyMedicineEngineeringArtificial intelligence

Abstract

fetched live from OpenAlex

The COVID-19 pandemic posed, and continues to pose, many challenges to teaching and learning, most notably the need to pivot from traditional in-person course instruction and experiences to entirely virtual course delivery while maintaining course rigor and quality. Our guiding principle for course modification was the critical need for an equitable, accessible, engaging, and motivating learning experience for students that maintained the learning outcomes and objectives of the course in a fully virtual and digitized format. This paper illustrates the evidence-based approach that the instructional team of a first-year biology experiential learning course took in response to the need for instruction to occur in virtual space and time for the Fall 2020 (September to December 2020) semester.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.506

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.153
GPT teacher head0.505
Teacher spread0.352 · 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