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

Authors
  • Akande, Oluwatobi Noah1, 2
  • Badmus, Taofeeq Alabi3, 2, 4
  • Akindele, Akinyinka Tosin5, 2
  • Arulogun, Oladiran Tayo5, 2
  • 1 Computer Science Department, Landmark University, Kwara State, Nigeria
  • 2 Open and Distance Learning Centre, Ladoke Akintola University of Technology, Ogbomoso, Oyo State Nigeria
  • 3 Resilient Engineering Research Group, Faculty of Engineering, University of Nottingham, England, United Kingdom
  • 4 Department of Computer Engineering, Federal University of Oye-Ekiti, Ekiti State, Nigeria
  • 5 School of E-learning Projects, Kampala International University, Kampala, Uganda
Type
Published Article
Journal
Data in Brief
Publisher
Elsevier
Publication Date
Jun 25, 2020
Volume
31
Identifiers
DOI: 10.1016/j.dib.2020.105926
PMID: 32665968
PMCID: PMC7316039
Source
PubMed Central
Keywords
License
Unknown

Abstract

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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