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Record W4287889744 · doi:10.1007/978-3-030-99634-5_11

Open, Flexible, and Serving Others: Meeting Needs during a Pandemic and beyond

2022· book-chapter· en· W4287889744 on OpenAlexaff
Vanessa P. Dennen, Ji Yae Bong

Bibliographic record

VenueEducational communications and technology: issues and innovations · 2022
Typebook-chapter
Languageen
FieldComputer Science
TopicOpen Education and E-Learning
Canadian institutionsConcordia University
Fundersnot available
KeywordsOpen educational resourcesFlexibility (engineering)Plan (archaeology)Class (philosophy)Medical educationDistance educationCoronavirus disease 2019 (COVID-19)Service-learningPandemicComputer sciencePsychologyKnowledge managementMathematics educationPedagogyMedicineManagement

Abstract

fetched live from OpenAlex

Abstract In the early days of the COVID-19 pandemic when in-person courses were switching to emergency remote learning formats, even students online needed flexibility. This case study describes how a graduate-level online class on open learning and open educational resources (OER) was redesigned to both allow students to apply their course-related knowledge and skills in the service of others and accommodate students whose other life responsibilities had changed. Findings show that these online students experienced great stress during Spring 2020, and many had increased job duties related to the shift to remote learning. These students appreciated the flexible redesign and used it as an opportunity to help integrate OER in their own remote teaching and assist others to do the same. They provided their colleagues and the field at large with educational resources about finding, using, creating, and sharing OER, all while meeting course objectives. Even students who were not employed as educators or instructional designers embraced the opportunity to be helpers and deploy their new knowledge and skills. Student learning outcomes were assessed using reflective portfolios, and course objectives were met whether students followed the original course plan or took advantage of the course redesign.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.777
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0010.005
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 head0.039
GPT teacher head0.317
Teacher spread0.278 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations1
Published2022
Admission routes1
Has abstractyes

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