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Cited by 135Online and Blended LearningOnline Learning and AnalyticsEvasion and Academic Success Factors

The DOI matches its Crossref record; 14 of the 16 references it cites were found in a registry or an index.

Identifying at‐risk students in videoconferencing and web‐based distance education

Osborn, Viola·2001·American Journal of Distance Education
DOI 10.1080/08923640109527073
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Abstract

Based on the multivariate framework of student attrition developed by leading researchers in the field of distance education and instructional technology, this study centers on a method of assessing the ability of a student to complete a distance learning course. The focus of the investigation is construction and validation of a brief survey instrument to identify at‐risk students enrolled in Web‐based and videoconferencing courses.

Overview

Integrity signals

Registry

Crossref · 10.1080/08923640109527073

Cites

14 of 14 references verified0 citation errors · 0 not checkable

Statistics

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

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Citations

Cites

Research works printed but not linked: 5

  1. Billings D. M., 1989, Readings in distance learning and instruction, 66
  2. Canfield A. A., 1976, Learning styles inventory, Form S‐A
  3. Kennedy D., 1976, Teaching at a Distance, 7, 61
  4. Powell R., 1990, Journal of Distance Education, 5, 5
  5. Tinto V., 1975, Review of Educational Research, 45, 89, 10.3102/00346543045001089 · DOI · Paper page

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Metadata

Authors
Osborn, V.
Affiliations
Baylor University (US)
Corresponding author
Osborn, Viola
Venue
American Journal of Distance Education
Publisher
Informa UK Limited
Published
2001-01
Volume
15
Issue
1
Pages
41-54
ISSN
  • 0892-3647 (ISSN-L)
  • 1538-9286
DOI
10.1080/08923640109527073
OpenAlex
W1966767041
Cited by
135
References
16
Citations by year
2026: 1 · 2025: 1 · 2024: 4 · 2023: 3 · 2022: 7 · 2021: 10 · 2020: 6 · 2019: 5 · 2018: 6 · 2017: 4 · 2016: 12 · 2015: 7 · 2014: 8 · 2013: 6 · 2012: 7
FWCI
20.97
Type
journal article
Language
en
Open access
closed
Locations
American Journal of Distance Education (publishedVersion)
Topics
  • Social Sciences › Education › Online and Blended Learning
  • Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
  • Social Sciences › Education › Evasion and Academic Success Factors
Keywords
at-risk students, student attrition, distance education, videoconferencing, web-based learning, course completion prediction, questionnaire development, instrument validation

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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.

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