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Record W3008310589 · doi:10.1097/nne.0000000000000813

Impact of Electronic Reminders on Student Grades and Attitudes in Online Courses

2020· article· en· W3008310589 on OpenAlexaff
Carol A. O'Neil, Kathleen M. Buckley

Bibliographic record

VenueNurse Educator · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsNatural Sciences and Engineering Research Council of Canada
Fundersnot available
KeywordsMedical educationPsychologyGraduate studentsScale (ratio)Medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Reminders guide students in meeting course expectations for submitting assignments. PROBLEM: Variables linked to the effective use of reminders are unclear. The purpose of this study was to evaluate the impact on student grades and attitudes of using routine reminders for assignments in an online course. APPROACH: Students enrolled in online graduate and undergraduate nursing courses were emailed weekly reminders for discussion board assignments. Students received reminders for half of the semester and served as their own control to evaluate the impact of reminders on grades. OUTCOMES: There was no significant impact of reminders on grades or overall attitude. However, when undergraduate and graduate students were compared on individual questions on an attitude toward reminders' scale, undergraduate students reported that reminders were necessary, had a positive impact on their grades, and should be included in all courses. CONCLUSIONS: Reminders should be routinely used in undergraduate online courses.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.299

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.029
GPT teacher head0.420
Teacher spread0.391 · 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 designObservational
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

Citations2
Published2020
Admission routes1
Has abstractyes

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