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Modeling undergraduates' selection of course modality: A large sample, multi-discipline study
Scholarly understanding is limited with regard to what influences students' choice to take a particular course fully online or in-person. We surveyed 650 undergraduates at a public Canadian university who were enrolled in courses that were offered in both modalities during the same semester, fo...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7571457/ https://www.ncbi.nlm.nih.gov/pubmed/33100824 http://dx.doi.org/10.1016/j.iheduc.2020.100776 |
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author | O'Neill, Kevin Lopes, Natália Nesbit, John Reinhardt, Suzanne Jayasundera, Kanthi |
author_facet | O'Neill, Kevin Lopes, Natália Nesbit, John Reinhardt, Suzanne Jayasundera, Kanthi |
author_sort | O'Neill, Kevin |
collection | PubMed |
description | Scholarly understanding is limited with regard to what influences students' choice to take a particular course fully online or in-person. We surveyed 650 undergraduates at a public Canadian university who were enrolled in courses that were offered in both modalities during the same semester, for roughly the same tuition cost. The courses spanned a wide range of disciplines, from archaeology to computing science. Twenty-five variables were gauged, covering areas including students' personal circumstances, their competence in the language of instruction, previous experience with online courses, grade expectations, and psychological variables including their regulation of their time and study environment, work avoidance and social goal orientation. Two logistic regression models (of modality of enrolment and modality of preference) both had good fit to the data, each correctly classifying roughly 75% of cases using different variables. Implications for instructional design and enrolment management are discussed. |
format | Online Article Text |
id | pubmed-7571457 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-75714572020-10-20 Modeling undergraduates' selection of course modality: A large sample, multi-discipline study O'Neill, Kevin Lopes, Natália Nesbit, John Reinhardt, Suzanne Jayasundera, Kanthi Internet High Educ Article Scholarly understanding is limited with regard to what influences students' choice to take a particular course fully online or in-person. We surveyed 650 undergraduates at a public Canadian university who were enrolled in courses that were offered in both modalities during the same semester, for roughly the same tuition cost. The courses spanned a wide range of disciplines, from archaeology to computing science. Twenty-five variables were gauged, covering areas including students' personal circumstances, their competence in the language of instruction, previous experience with online courses, grade expectations, and psychological variables including their regulation of their time and study environment, work avoidance and social goal orientation. Two logistic regression models (of modality of enrolment and modality of preference) both had good fit to the data, each correctly classifying roughly 75% of cases using different variables. Implications for instructional design and enrolment management are discussed. Elsevier Inc. 2021-01 2020-10-19 /pmc/articles/PMC7571457/ /pubmed/33100824 http://dx.doi.org/10.1016/j.iheduc.2020.100776 Text en © 2020 Elsevier Inc. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article O'Neill, Kevin Lopes, Natália Nesbit, John Reinhardt, Suzanne Jayasundera, Kanthi Modeling undergraduates' selection of course modality: A large sample, multi-discipline study |
title | Modeling undergraduates' selection of course modality: A large sample, multi-discipline study |
title_full | Modeling undergraduates' selection of course modality: A large sample, multi-discipline study |
title_fullStr | Modeling undergraduates' selection of course modality: A large sample, multi-discipline study |
title_full_unstemmed | Modeling undergraduates' selection of course modality: A large sample, multi-discipline study |
title_short | Modeling undergraduates' selection of course modality: A large sample, multi-discipline study |
title_sort | modeling undergraduates' selection of course modality: a large sample, multi-discipline study |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7571457/ https://www.ncbi.nlm.nih.gov/pubmed/33100824 http://dx.doi.org/10.1016/j.iheduc.2020.100776 |
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