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Record W4403033622 · doi:10.18357/otessac.2022.2.1.419

Multi-Section Open Course Design: Design and Implications for Faculty, Sessional Instructors, and Learners

2024· article· en· W4403033622 on OpenAlexafffundvenue
Valerie Irvine, Michael Paskevicius, Colin Madland, Richard McCue, Verena Roberts

Bibliographic record

VenueThe Open/Technology in Education Society and Scholarship Association Conference · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsUniversity of Victoria
FundersUniversity of Victoria
KeywordsCourse (navigation)Section (typography)Medical educationMathematics educationPsychologyEngineeringComputer scienceMedicineOperating system

Abstract

fetched live from OpenAlex

As open course designs are being implemented in regular post-secondary credit courses (beyond massive open online courses), new issues and processes need to be considered that are fundamentally different from courses offered within the traditional learning management system. In this paper, we will review our approach to multi-section open course design and share our experiences working through emergent issues, such as content placement, intellectual property, attribution, etc. We will provide insights and recommendations for institutional leadership and administration, faculty area advisors, technical support staff, and sessional instructors.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.404
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
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 head0.139
GPT teacher head0.451
Teacher spread0.313 · 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 designObservational
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

Citations0
Published2024
Admission routes3
Has abstractyes

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