Survey Dataset on Face to Face Students' intention to use Social Media and Emerging Technologies for Continuous Learning

Published: 22 June 2020| Version 3 | DOI: 10.17632/vb2m5x5xhr.3
Akande Oluwatobi,


One of the sectors that felt the impact of the Corona Virus Disease 2019 (COVID-19) pandemic was the educational sector. The outbreak led to the immediate closure of schools at all levels thereby sending billions of students away from their various institutions of learning. However, the shut down of academic institutions was not a total one as some institutions that were solely running online programmes were not affected. Those who were running face to face and online modes quickly switched over to the online mode. Unfortunately, institutions that have not fully embraced online mode of study were greatly affected. 85% of academic institutions in Nigeria are operating face to face mode of study, therefore, majority of Nigerian students at all levels were affected by the COVID-19 lockdown. Social media platforms and emerging technologies were the major backbones of institutions that are running online mode of study, therefore, this survey uses the unified theory of acceptance and use of technology (UTAUT) model to capture selected Face to face Nigerian University students accessibility, usage, intention and willingness to use these social media platforms and emerging technologies for learning. The challenges that could mar the usage of these technologies were also revealed. Eight hundred and fifty undergraduate students participated in the survey. The dataset 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 and the descriptive statistics for all the variables captured. This second version contains the reliability statistics of the UTAUT variables using Cronbach's alpha. This measured the reliability as well as the internal consistency of the UTAUT variables. This was measured in terms of the reliability statistics, inter-item correlation matrix and item-total statistics. Authors believed that 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. In this version 3, the SPSS file in SAV format was made available in csv format. Also, the .rar file was made opened to make data accessibility easier.


Steps to reproduce

1. Upload the designed dataset online preferably using Google forms 2. Send the links to targeted audience 3. Download responses and charts when the desired number of respondents is met 4. Use SPSS to fine tune the uploaded data 5. Analyze your results using descriptive statistics or any other statistics that you desire


Ladoke Akintola University of Technology


Educational Technology, Social Media, University Student, Online Learning, Online Teaching, Distance Education, Undergraduate Education, Undergraduate Teaching, Distance Learning System Design, Academic Learning, Social Media Analytics