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Record W3184012846 · doi:10.26522/brocked.v30i2.866

Experiencing the shift: How postsecondary contract and continuing faculty moved to online course delivery

2021· article· en· W3184012846 on OpenAlexaffvenue
Patricia Danyluk, Amy Burns

Bibliographic record

VenueBrock Education Journal · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Practises and Engagement
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsNoticeTimelineMedical educationDistance educationParadigm shiftWork (physics)PsychologyOnline coursePedagogyEngineeringPolitical scienceMedicine

Abstract

fetched live from OpenAlex

The shift to online learning that occurred in March of 2020, created an unprecedented period of intense work for faculty and sessional instructors at the post-secondary level. This shift necessitated courses be adapted under short timelines, new technology be integrated into course design and teaching strategies and assessment methods be adapted for an online environment (Van Nuland et al., 2020). This study examines how sessional instructors, referred to in this chapter as contract faculty, and continuing full-time faculty members delivering the same online courses experienced this shift. While the demands of a continuing faculty position call for balancing of teaching, research and service responsibilities, contract instructors have their own unique stressors (Karram Stephenson et al., 2020). Contract faculty lack job security, are paid by the course and often receive their teaching assignments with short notice. By examining their perspectives on delivering the same courses online, we learn that the shift to online teaching resulted in additional work in order to adapt courses to the online environment, with faculty describing the challenges of balancing the additional work with other responsibilities of their position. Concerns of participants focused on a perceived inability to develop relationships with students in an online environment.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.319
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.036
GPT teacher head0.362
Teacher spread0.325 · 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 designQualitative
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

Citations5
Published2021
Admission routes2
Has abstractyes

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