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Record W1530981237

Acceptance and Resistance to Corporate E-Learning: A Case from the Retail Sector

2006· article· en· W1530981237 on OpenAlexaffvenue
Lynne Rabak, Martha Cleveland‐Innes

Bibliographic record

VenueInternational journal of e-learning & distance education · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsAthabasca University
Fundersnot available
KeywordsBusinessResistance (ecology)MarketingSurvey researchBusiness administrationKnowledge managementComputer science
DOInot available

Abstract

fetched live from OpenAlex

The purpose of this study was to investigate what influences employees’ acceptance and resistance to a corporate e-learning initiative provided by a large retail chain. The research used a survey design to gather interview and survey data to examine the factors affecting learner interest in, and resistance to, training and e-learning. The results provided insight into the attitudes and perceptions of employees in a large retail chain about the training and identified areas for further attention to facilitate a best-practices approach for increasing participation. The research asked: What barriers and enticers in relation to e-learning are present in a group of employees offered ane-learning training opportunity? The driving and restraining forcesthat influence an individual’s fields (also defined as an individual’s life space) as indicated in Lewin’s (1997) Force Field Theory were examined and used as a framework for analysis of the findings to gain a clearer understanding of which factors support or deter these employees from participation in e-learning in the workplace. Lewin suggested that consideration of what encourages learners to embrace new methods for learning is important but equally, the factors that cause resistance to learning must be thoroughly examined. Supporting factors such a the rationale for the training being well understood and detractors like insufficient time to complete the modules were identified. Findings indicate that time, meaningful recognition for participation, and personal and technical support need to be provided for the successful implementation of e-learning initiatives. Le but de cette étude était de déterminer les facteurs qui influencent l’acceptation ou la résistance des employés à une initiative de e-learning corporatif offerte par une grande chaine de commerce au détail. La récherche a utilisé un design de sondage pour ramasser des données d’entrevues et de sondages, pour examiner les facteurs affectant l’intérêt de l’apprenant dans, ou la résistance à, la formation et au e-learning. Les résultats nous renseignent sur les attitudes et les perceptions des employés d’une grande chaîne de commerce au détail sur la formation et a permis d’identifier des façons de faciliter une approche « meilleures pratiques » pour augmenter la participation. Les questions de récherche étaient : Quelles sont les barrières et les facilitateurs en relation avec le e-learning présents dans un groupe d’employés à qui on offre une opportunité de formation? Les moteurs et les freins qui influencent les champs d’un individu (aussi défini comme l'éspace vital d’un individu), tel qu’indiqué par la théorie des champs de force de Lewin (1997), ont été examinés et utilisés comme cadre d’analyse des observations pour comprendre quels facteurs encouragent ou découragent la participation des employés à une formation e-learning au travail. Lewin suggère que considérer ce qui encourage les employés à accepter de nouvelles méthodes d’apprentissage est important, mais que les facteurs qui causent des résistances doivent aussi être examinés. Les facteurs de soutien, comme le rationnel derrière une bonne formation, et les facteurs décourageants comme le manque de temps pour compléter les modules de formation, ont éte identifiés. Les résultats indiquent que le temps, la reconnaissance significative de la participation et le soutien technique doivent être fournis pour assurer une réalisation heureuse d’initiatives e-learning.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.003
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.022
GPT teacher head0.312
Teacher spread0.290 · 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 source (direct Gemma or distilled Codex), 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

Citations31
Published2006
Admission routes2
Has abstractyes

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