Cited by 21Perfectionism, Procrastination, Anxiety StudiesOnline and Blended LearningOnline Learning and Analytics

Predictors of course outcomes: early indicators of delay in online classrooms

McElroy, Barbara Woods, Lubich, Bruce H.·2013·Distance Education

Abstract

Studies have long shown that students who begin or submit their work later tend to have negative academic outcomes. The measures of procrastination used in those studies may not have provided information timely enough for instructor intervention. This article focuses on delay in the online environment among graduate students. We propose two new measures of delay that can be disclosed in a timely manner, enabling instructors to help students who are prone to late submissions to succeed. Date of class registration and date of initial class posting are negatively associated with final letter grades. Date of first class posting can serve to alert instructors to those with potential delay problems. The results for date of class registration are less clear.

Integrity signals

Registry

Crossref · 10.1080/01587919.2013.770433

Cites

4 of 4 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Using notification-based stimuli to reduce academic procrastination in online learning processes can contribute to improving students' self-regulation skills.

    “As a result, using notification-based stimuli to reduce academic procrastination in online learning processes can contribute to both improving students' self-regulation skills and increasing their participation in learning processes (McElroy & Lubich, 2013;van Eerde & Klingsieck, 2018).”
  • Using notification-based stimuli to reduce academic procrastination in online learning processes can contribute to increasing students' participation in learning processes.

    “As a result, using notification-based stimuli to reduce academic procrastination in online learning processes can contribute to both improving students' self-regulation skills and increasing their participation in learning processes (McElroy & Lubich, 2013;van Eerde & Klingsieck, 2018).”

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
McElroy, B. W., & Lubich, B. H.
Affiliations
  • Susquehanna University (US)
  • University System of Maryland (US)
Corresponding author
McElroy, Barbara Woods
Venue
Distance Education
Published
2013-05
Volume
34
Issue
1
Pages
84-96
ISSN
  • 0158-7919 (ISSN-L)
  • 1475-0198
OpenAlex
W2022857550
Cited by
21
References
4
Citations by year
2025: 1 · 2024: 1 · 2023: 2 · 2022: 2 · 2021: 4 · 2020: 2 · 2019: 1 · 2018: 2 · 2017: 2 · 2016: 3 · 2014: 1
FWCI
1.48
Type
journal article
Language
en
Open access
closed
Locations
Distance Education (publishedVersion)
Topics
  • Social Sciences › Psychology › Clinical Psychology › Perfectionism, Procrastination, Anxiety Studies
  • Social Sciences › Education › Online and Blended Learning
  • Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
Keywords
procrastination, late submission, online learning, graduate students, course outcomes, academic performance, instructor intervention, early indicators, letter grades

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review