International Journal of Soft Computing

Year: 2021
Volume: 16
Issue: 1
Page No. 9 - 19

Adventurism, Information Technology Self-Efficacy and Age as Predictors of Cybercrime among University Undergraduates

Authors : Nwabueze Cletus Offor

Abstract: The study investigated adventurism, information technology self-efficacy and age as predictors of cybercrime among undergraduates of Imo State University. Three hypothesis were postulated and tested. Two hundred participants were selected from four student hostel alliances: Bishop’s Court Hostel Alliance, Front Gate Hostel Alliance, Aladinma Hostel Alliance and Amawire Hostel Alliances using simple random and convenience sampling techniques. Their age ranged between 18 and 30 years with a mean age of 24.80 and a standard deviation of 2.96. Three instruments; Information Technology Self-Efficacy scale, Adventurism Scale and Cybercrime scale were used to collect data for the study. Data on age was collected using the personal data column on the instruments. The design of the study was cross-sectional survey design while multiple regression statistics was used to analyze the data. The results showed that adventurism and information technology self-efficacy significantly and inversely predict cybercrime while age directly and significantly predicts cyber crime. The result equally revealed that jointly adventurism, information technology self-efficacy and age also significantly predict cybercrime. Based on these findings, the significance of the study is that parents and education authorities should intensify efforts on ethical training and moral guidance to youths concerning their exploration with computer and internet services. The researcher recommends that government and corporate institutions need to increase enlightenment on the dangers of involvement in cybercrime to youth development.

How to cite this article:

Nwabueze Cletus Offor , 2021. Adventurism, Information Technology Self-Efficacy and Age as Predictors of Cybercrime among University Undergraduates. International Journal of Soft Computing, 16: 9-19.

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