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Record W3152753273 · doi:10.5430/wje.v11n2p1

Using Behaviour Change as a Critical Frame of Reference to Understand the Adoption of Learning Design Methodologies in Higher Education

2021· article· en· W3152753273 on OpenAlexvenueno aff
Maria Toro-Troconis, Julie Voce, Jesse Alexander, Santanu Vasant, Manuel Frutos‐Perez

Bibliographic record

VenueWorld Journal of Education · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsnot available
FundersCity, University of LondonQueen Mary University of London
KeywordsInstructional designContext (archaeology)PsychologyBlended learningKnowledge managementEducational technologyMultimethodologyIntervention (counseling)Applied psychologyMedical educationPedagogyComputer scienceMedicine

Abstract

fetched live from OpenAlex

This paper introduces the COM-B model (Capabilities-Opportunities-Motivation:Behaviour) and its use in combination with the Behaviour Change Wheel (BCW) in developing an intervention which aims to promote the adoption of learning design methodologies by academic staff working with learning technologists in Higher Education (HE). Qualitative structured interviews were conducted among members of staff from five UK universities based on the COM-B model to identify the main behavioural determinants for the use and implementation of learning design methodologies. The analysis suggests that the implementation of learning design methodologies/frameworks might be more likely to occur if academic staff and learning technologists’ psychological capability, physical and social opportunities, and intrinsic and extrinsic motivations are addressed. The COM-B model and the BCW have been effective in the context of learning design to analyse the behaviour of academic staff and learning technologists when engaging in the design of online/blended learning programmes.

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)0.002
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.573
Threshold uncertainty score0.428

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.477
GPT teacher head0.511
Teacher spread0.034 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations8
Published2021
Admission routes1
Has abstractyes

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