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Record W2562420332 · doi:10.5430/jnep.v7n5p45

Exploring nursing student and faculty perceptions of incivility in the online learning environment

2016· article· en· W2562420332 on OpenAlexvenueno aff
Jeanette McNeill, Kathleen Dunemn, Katrina Einhellig, Lory Clukey

Bibliographic record

VenueJournal of Nursing Education and Practice · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicWorkplace Violence and Bullying
Canadian institutionsnot available
Fundersnot available
KeywordsIncivilityCivilityPsychologyScale (ratio)PerceptionMedical educationLearning environmentSyllabusNursingSocial psychologyMedicinePedagogyPolitical science

Abstract

fetched live from OpenAlex

Objective : The purpose of the study was to explore student and faculty perspectives regarding what constitutes incivility in the online learning environment (OLE). Online learning is increasingly prevalent in nursing education. Scant research describes characteristics of OLEs contributing to, or inhibiting, learning or affecting civility among learners/faculty. Educators must effectively manage uncivil behavior to reduce incivility in learning and work environments. Attribution theory is helpful in examining issues related to incivility. Methods and Results : Faculty (n = 34) and students (n = 44) reported perceptions of what constitutes incivility via an online survey, the Incivility in the Online Learning Environment (IOLE), an instrument described by Clark and colleagues. The groups reported somewhat different perceptions of the extent of incivility experienced but agreed on identification of uncivil behaviors. Both groups agreed that rude comments and name calling were definitely uncivil, however, several areas of disagreement existed between faculty and student groups as to other types of behaviors. For example, lack of timely feedback on assignments and an unclear syllabus were seen as incivility by students. High internal consistency (Cronbach’s alpha of .98 on the faculty scale, and .96 on the student scale) was obtained for the IOLE in this sample. Qualitative comments regarding suggested ways to promote civility were similar from both groups, including role modeling and penalizing incivility; students emphasize the need for clearly stated course requirements. Conclusions : Best practices are essential for developing/delivering online courses and in orienting faculty and students regarding expectations for professional behavior online. Faculty development should focus on using best practices to ensure online courses incorporate essential components enabling accessibility and efficiency for students navigating through them. Attention to this unique and increasingly typical learning environment is essential to the goal of prevention of incivility in both learning environments and subsequently in workplaces.

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)0.001
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 score0.610
Threshold uncertainty score0.266

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.230
GPT teacher head0.483
Teacher spread0.253 · 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

Citations12
Published2016
Admission routes1
Has abstractyes

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