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Record W3020086669 · doi:10.21432/cjlt27881

Open Educational Practices Advocacy: The Instructional Designer Experience

2020· article· en· W3020086669 on OpenAlex
Michelle Harrison, Irwin DeVries

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

VenueCanadian Journal of Learning and Technology · 2020
Typearticle
Languageen
FieldComputer Science
TopicOpen Education and E-Learning
Canadian institutionsThompson Rivers University
Fundersnot available
KeywordsOpen educational resourcesInstructional designWorkloadEducational technologyProfessional developmentBest practiceOpen educationPublic relationsPedagogyOpen learningKnowledge managementPsychologySociologyPolitical scienceTeaching methodComputer scienceCooperative learning

Abstract

fetched live from OpenAlex

Instructional designers are in a unique position to provide leadership and support for advancement of new technologies and practices. There is a paucity of research on current and potential roles of Instructional designers in incorporating and advocating for open educational practices at their higher education institutions. Against the background of emerging open educational practices, a survey and interviews were conducted with instructional design professionals to establish, from their experience and practice, their roles and potential for advocacy for open educational practices (OEP) including open educational resources (OER). Among the results of the analysis, it was found that while instructional designers have a strong awareness of and desire to advocate for OEP in their institutions, their ability to move forward was limited by perceived barriers such as lack of relevant mandates and professional workload recognition, policy development and funding, awareness and leadership support. In addition, there were gaps identified between what they most valued about OEP, such as implementing innovative pedagogies, and what they could actually initiate and advocate for in practice (adopt and support OER). They pointed to a lack of formal learning opportunities around OEP and expressed that their main sources of learning and support were of an informal nature, acquired through their networks and collaborations with peers.

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)0.002
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: none
Teacher disagreement score0.940
Threshold uncertainty score0.416

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.033
GPT teacher head0.306
Teacher spread0.273 · 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