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Dataset to support the adoption of social media and emerging technologies for students’ continuous engagement

The recent advancements in ICT have made it possible for teaching and learning to be conducted outside the four walls of a University. Furthermore, the recent COVID-19 pandemic that has crippled educational activities in all nations of the world has further revealed the urgent need for academic inst...

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Autores principales: Akande, Oluwatobi Noah, Badmus, Taofeeq Alabi, Akindele, Akinyinka Tosin, Arulogun, Oladiran Tayo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7316039/
https://www.ncbi.nlm.nih.gov/pubmed/32665968
http://dx.doi.org/10.1016/j.dib.2020.105926
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author Akande, Oluwatobi Noah
Badmus, Taofeeq Alabi
Akindele, Akinyinka Tosin
Arulogun, Oladiran Tayo
author_facet Akande, Oluwatobi Noah
Badmus, Taofeeq Alabi
Akindele, Akinyinka Tosin
Arulogun, Oladiran Tayo
author_sort Akande, Oluwatobi Noah
collection PubMed
description The recent advancements in ICT have made it possible for teaching and learning to be conducted outside the four walls of a University. Furthermore, the recent COVID-19 pandemic that has crippled educational activities in all nations of the world has further revealed the urgent need for academic institutions to embrace and integrate alternative modes of teaching and learning via social media platforms and emerging technologies into existing teaching tools. This article contains data collected from 850 face to face University students during the COVID-19 pandemic lockdown. An online google form was used to elicit information from the students about their awareness and intention to use these alternative modes of teaching and learning. The questions were structured using the Unified Theory of Acceptance and Use of Technology (UTAUT) model. This data article includes the questionnaire used to retrieve the data, the responses obtained in spreadsheet format, the charts generated from the responses received, the Statistical Package of the Social Sciences (SPSS) file, the descriptive statistics, and reliability analysis computed for all the UTAUT variables. The dataset will enhance understanding of how face to face students use social media platforms and how these platforms could be used to engage the students outside their classroom activities. Also, the dataset exposes how familiar face to face University students are to these emerging teaching and learning technologies. The challenges that could inhibit the adoption of these technologies were also revealed.
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spelling pubmed-73160392020-06-25 Dataset to support the adoption of social media and emerging technologies for students’ continuous engagement Akande, Oluwatobi Noah Badmus, Taofeeq Alabi Akindele, Akinyinka Tosin Arulogun, Oladiran Tayo Data Brief Computer Science The recent advancements in ICT have made it possible for teaching and learning to be conducted outside the four walls of a University. Furthermore, the recent COVID-19 pandemic that has crippled educational activities in all nations of the world has further revealed the urgent need for academic institutions to embrace and integrate alternative modes of teaching and learning via social media platforms and emerging technologies into existing teaching tools. This article contains data collected from 850 face to face University students during the COVID-19 pandemic lockdown. An online google form was used to elicit information from the students about their awareness and intention to use these alternative modes of teaching and learning. The questions were structured using the Unified Theory of Acceptance and Use of Technology (UTAUT) model. This data article includes the questionnaire used to retrieve the data, the responses obtained in spreadsheet format, the charts generated from the responses received, the Statistical Package of the Social Sciences (SPSS) file, the descriptive statistics, and reliability analysis computed for all the UTAUT variables. The dataset will enhance understanding of how face to face students use social media platforms and how these platforms could be used to engage the students outside their classroom activities. Also, the dataset exposes how familiar face to face University students are to these emerging teaching and learning technologies. The challenges that could inhibit the adoption of these technologies were also revealed. Elsevier 2020-06-25 /pmc/articles/PMC7316039/ /pubmed/32665968 http://dx.doi.org/10.1016/j.dib.2020.105926 Text en © 2020 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Computer Science
Akande, Oluwatobi Noah
Badmus, Taofeeq Alabi
Akindele, Akinyinka Tosin
Arulogun, Oladiran Tayo
Dataset to support the adoption of social media and emerging technologies for students’ continuous engagement
title Dataset to support the adoption of social media and emerging technologies for students’ continuous engagement
title_full Dataset to support the adoption of social media and emerging technologies for students’ continuous engagement
title_fullStr Dataset to support the adoption of social media and emerging technologies for students’ continuous engagement
title_full_unstemmed Dataset to support the adoption of social media and emerging technologies for students’ continuous engagement
title_short Dataset to support the adoption of social media and emerging technologies for students’ continuous engagement
title_sort dataset to support the adoption of social media and emerging technologies for students’ continuous engagement
topic Computer Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7316039/
https://www.ncbi.nlm.nih.gov/pubmed/32665968
http://dx.doi.org/10.1016/j.dib.2020.105926
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