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Record W2173749518 · doi:10.21432/t2np62

The Challenge of Designing Blended Courses: From Structured Design to Creative Faculty Support! | Les beaux défis du design de cours hybrides : du design structuré à l’accompagnement créatif !

2015· article· en· W2173749518 on OpenAlexaffvenueabout
Catherine Carré

Bibliographic record

VenueCanadian Journal of Learning and Technology · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsCertificateInstructional designFlexibility (engineering)Blended learningClass (philosophy)Mathematics educationComputer scienceEngineering managementEngineeringMultimediaEducational technologyPsychologyManagement

Abstract

fetched live from OpenAlex

This case study deals with the implementation of an e-learning program in a business school in Canada. Cabot Business School decided to offer the program in a blended format so as to increase the flexibility of the program for clientele enrolled in the undergraduate certificate program. A pilot was initiated in 2009 starting with four hybrid courses. Now, three years later, 35 courses are being offered in blended mode by lecturers and a handful of professors who, for the most part, had no previous experience teaching online. Given the rapid development of this program, this case deals with how the instructional designer, without the benefit of any additional resources, managed to juggle both the development of the certificate program as well as parallel projects. The issues encountered deal with the extent to which the instructional designer can support faculty who are converting their courses from in-class to online, one of the main design challenges encountered by faculty. This case describes training strategies and implemented solutions provided by the instructional designer as well as the results obtained, faculty perceptions, and food for thought on the possible evolution of the role of the instructional designer.

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)0.004
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.640
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
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 head0.043
GPT teacher head0.301
Teacher spread0.258 · 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

Citations6
Published2015
Admission routes3
Has abstractyes

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