MétaCan
Menu
Back to cohort
Record W2339544710 · doi:10.12973/iji.2015.8111a

The Impact of Culture on Instructional Design and Quality

2015· article· en· W2339544710 on OpenAlex
Afsaneh Sharif

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueInternational Journal of Instruction · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsQuality (philosophy)Mathematics educationInstructional designPsychologyPedagogyEpistemologyPhilosophy

Abstract

fetched live from OpenAlex

The purpose of this study was to investigate the effect of cultural differences, i.e. different contexts and backgrounds, on instructional designers' perspectives of quality in online environments. Using a questionnaire developed based on the Quality Matters rubric, we found designers in Canada focus slightly more on Learner Support strategies than designers in Spain. Despite differences in their contexts and some responsibilities, instructional designers in both countries consider the same features important and pay attention to them in their practices in order to develop good quality online courses. These features are institutional commitment, faculty support, student support, technology, course structure/instructional design, and assessment/evaluation and accessibility. Future research is required to improve the generalization of the results of the existing study while identifying other factors, such as budget and technology literacy that influence instructional designers' approaches in developing high-quality online learning materials.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.846
Threshold uncertainty score0.117

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.067
GPT teacher head0.423
Teacher spread0.356 · 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