Abstract
The purpose of this study was to develop and validate the ICT Self-Efficacy Scale and the association of cyberbullying and victimization with ICT self-efficacy. Sample 1 (436 university students) was used to identify the factor structure of the Scale, and sample 2 (1115 university students) provided the data to confirm the factor structure (CFA), and to compute the internal consistency reliability, and convergent validity of the scale. Findings demonstrate that the new scale is a reliable and valid domain-specific measure to assess ICT Self-Efficacy for university students. Suggestions for further research with the scale are provided.
Highlights
The proliferation of Information and Communication Technology (ICT) and its utilization in higher education has brought drastic changes to various aspects of the learning environment, while facilitating easy online communication with peers
O’Connor [53] recommended more robust statistical procedures to determine the number of factors with higher precision—parallel analysis and Velicer’s minimum average partial (MAP) test
A confirm the factor structure (CFA) was conducted with the second sample using MPlus version 7.0 (Muthén & Muthén, 2012), with Maximum Likelihood (ML) estimator
Summary
The proliferation of Information and Communication Technology (ICT) and its utilization in higher education has brought drastic changes to various aspects of the learning environment, while facilitating easy online communication with peers. The changing trends in the use of World Wide Web following the delivery of web 2.0 technologies (websites that are interactive and include user-generated material) have revolutionized the ways in which ICT is used for learning and communication purposes [1]. Examples of web 2.0 sites that are increasingly used by students in higher education include social media (e.g., Facebook), wikis, blogs, video sharing sites (e.g., YouTube) folksonomies Cyberbullying behaviors include sending intimidating or derogatory messages, spreading rumors, posting unwanted images or videos, revenge porn, posting offensive comments about someone, creating fake accounts using someone’s identity, and excluding someone out of an online communication with a malicious intent to hurt someone
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