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Record W3195329478 · doi:10.32920/ryerson.14661339.v1

Technology readiness, attitude towards computers and computer literacy among first year nursing students : A Canadian perspective

2021· preprint· en· W3195329478 on OpenAlex
Rita Wilson

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicTechnostress in Professional Settings
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsPreparednessComputer literacyPerspective (graphical)Sample (material)Medical educationLiteracyPsychologyComputer technologyNursingMedicineMathematics educationPedagogyComputer scienceMultimedia

Abstract

fetched live from OpenAlex

This descriptive correlational study used a convenience sample (n=30) recruited from one Canadian School of Nursing to investigate first year nursing students' preparedness for technology use. It examined the students' general technology readiness, attitudes toward computer use in general and in nursing as well as their general computer literacy. Most students were average "techno-ready", had positive attitudes toward computer use in general and in nursing and had low self-perceived proficiency in various computer applications. There was beginning evidence in support of statistically significant positive relationships among the students' technology readiness, their attitude towards computers and their computer literacy. The findings did not support correlations between the students' attitude towards computers and their computer literacy or between their technology readiness and their computer literacy. These findings suggest that some first year nursing students may need additional supports to enhance their preparedness to work in today's technology-rich health care environment.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.128
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.357
Teacher spread0.344 · 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

Quick stats

Citations1
Published2021
Admission routes2
Has abstractyes

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