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Record W4396760183 · doi:10.1097/acm.0000000000005763

Beyond the Task: Developing a Tool to Measure Workplace Characteristics That Affect Cognitive Load and Learning

2024· article· en· W4396760183 on OpenAlexaff
Sarah Blissett, Sebastián Rodríguez, Atif Qasim, Patricia O’Sullivan

Bibliographic record

VenueAcademic Medicine · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicEducational Environments and Student Outcomes
Canadian institutionsWestern University
Fundersnot available
KeywordsAffect (linguistics)Task (project management)Measure (data warehouse)CognitionPsychologyCognitive loadCognitive psychologyApplied psychologyComputer scienceEngineeringCommunicationPsychiatry

Abstract

fetched live from OpenAlex

PURPOSE: Educators lack tools to measure the workplace characteristics that learners perceive to affect learning. Without a tool that encompasses the social, organizational, and physical components of workplace learning environments (WLEs), it is challenging to identify and improve problematic workplace characteristics. Using echocardiography WLE, this study developed a tool to measure workplace characteristics that cardiology fellows perceive to affect learning. METHOD: The Workplace-Cognitive Load Tool (W-CLT) was developed, which encompasses 17 items to measure workplace characteristics that could affect perceived cognitive load and learning. Exploratory factor analysis was used to identify the most parsimonious structure. A total of 646 cardiology subspeciality fellows were recruited from 60 cardiology fellowship programs to complete the survey between November 2020 and February 2021. Validity evidence was collected, guided by the unified model of validity. RESULTS: A total of 308 fellows (response rate, 49%) participated in the survey. The most parsimonious structure included 4 factors: (1) workplace-task, (2) workplace-environment, (3) workplace-orientation, and (4) workplace-teaching and feedback. All factors had high reliability (Cronbach α = 0.92, 0.92, 0.96, and 0.94, respectively). Social, organizational, and physical components of WLEs were represented in the items. Workplace-teaching and feedback had moderate negative correlations with workplace-environment ( r = -0.41, P < .001) and workplace-orientation ( r = -0.36, P < .001). A moderate positive correlation was found between workplace-task and workplace-teaching and feedback ( r = 0.42, P < .001). Workplace-task had weak negative correlations with workplace-environment ( r = -0.22, P < .001) and workplace-orientation ( r = -0.23, P < .001). CONCLUSIONS: The W-CLT measures workplace characteristics that cardiology fellows perceive to affect their learning. The presence of social, organizational, and physical components emphasizes how workplace characteristics can enhance or impede learning. The W-CLT provides a foundation to explore how learning can be optimized in other WLEs.

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 score0.582
Threshold uncertainty score0.368

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.363
Teacher spread0.320 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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