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Record W2731493669 · doi:10.5944/openpraxis.9.2.519

Conceptualizing Open Educational Practices through the Lens of Constructive Alignment

2017· article· en· W2731493669 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.

Bibliographic record

VenueOpen Praxis · 2017
Typearticle
Languageen
FieldComputer Science
TopicOpen Education and E-Learning
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsAffordanceOpen learningOpen educational resourcesConstructiveEducational technologyOpen educationWork (physics)Best practiceComputer sciencePedagogyInstructional designEducational resourcesMathematics educationDistance educationTeaching methodKnowledge managementSociologyPsychologyCooperative learningEngineeringPolitical scienceHuman–computer interactionProcess (computing)

Abstract

fetched live from OpenAlex

The act of instruction may be conceptualized as consisting of four elements: learning outcomes, learning resources, teaching and learning activities, and assessments and evaluation. For instructors in higher education, the way they manage the relationships between these elements is what could be considered the core of their instructional practice. For each of the elements, this paper seeks to identify open educational practices, their affordances, and evidence of their utility in supporting the work of teachers in shifting from existing teaching and learning practices to more open educational practices. The literature reviewed and model proposed may provide educational developers or proponents of open education a lens with which to discuss open educational practices with faculty specifically related to their teaching and learning design practices.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication, Open science
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.950
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0030.006
Open science0.0060.003
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 head0.114
GPT teacher head0.415
Teacher spread0.301 · 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