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Innovation in the Learning Management System (LMS)

2021· book-chapter· en· W4240148777 on OpenAlexaff

Bibliographic record

VenueIGI Global eBooks · 2021
Typebook-chapter
Languageen
FieldSocial Sciences
TopicHigher Education and Employability
Canadian institutionsRoyal Roads University
Fundersnot available
KeywordsWorkforceScope (computer science)Knowledge managementWorkplace learningFront lineBusinessQualitative researchSoft skillsWorkforce planningMarketingProcess managementComputer scienceEngineeringMedical educationMedicineSociologyWork (physics)

Abstract

fetched live from OpenAlex

This qualitative study identifies design principles and delivery methods best suited for the retail industry with a focus on training front-line workers. This research identifies key design elements to aid retail organizations in choosing an effective online learning solution for their workforce. To provide clear and relevant design recommendations specific to the retail workforce, the scope of the research focused on learner characteristics, e-learning in the workplace, adult learning theory, as well as current design and delivery features available on the market. Through a meta-synthesis of qualitative research, findings indicate a need for soft skill development related to customer interactions. A list of design principles targeting soft skill development of the front-line retail worker is recommended based on both industry and academic research.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.908
Threshold uncertainty score0.508

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.039
GPT teacher head0.323
Teacher spread0.284 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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
Published2021
Admission routes1
Has abstractyes

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