The Creation and Evaluation of the Cybersecurity Measurement Instrument used for
Undergraduate Students
Introduction
The Article I have chosen to review is and article from “cybercrimejournal.com”. The title
of it is “Development and Evaluation on Cybersecurity Behavior Measurement
Instruments for Undergraduate Students”. It was written by Pannika Ngamcharoen,
Naksit Sakdapat, and Duchduen Emma Bhanthumnavin. In the article it covers many
different points of research and data that revolves around the overall topic.
Relations to the principles of social sciences
The Article explores undergraduates’ perception of cyber threats using data and
multiple sources. It demonstrates principles of social science, including Determinism,
Ethical Neutrality, and objectivity. Determinism is evident in the researchers’ focus on
self-protection and cybersecurity behaviors. Ethical Neutrality emphasizes the
importance of cybersecurity awareness without bias. Objectivity is demonstrated
through the methods used to gather statistics and date, supporting the conclusions
drawn.
The Studies questions and hypotheses
The research questions asked in the article are: “Are the measurement instruments
used in the research reliable?”, and “How is the reliability of measurement
instruments?”. The Hypotheses that were made by the researchers in the article are: 1.
“Exploratory Factor Analysis (EFA) can effectively evaluate the cybersecurity behavior
measurement instrument, requiring a minimum of four items per component.” (Pannika
Ngamcharoen et al., 2024). 2.” Exploratory Factor Analysis can account for more than
60% of the variance in cybersecurity behavior (Tucker et al.,1997). 3. “CFA will Validate
that the model satisfactory fits the empirical data” (Pannika Ngamcharoen et al., 2024).
The Research method
The research method used is a quantitative research method. In the text it is said that
this research study” seeks to develop and evaluate a robust measurement instrument
for assessing cybersecurity behavior”. So, the overall goal of this method is to create
the measurement instrument for assessing behavior revolving around cybersecurity
while also using data gathered to evaluate whether or not it is validated.
Types of data
The Types of data Used in the article are Preliminary information of the samples they
had, Cybersecurity Behavior Measurement, and Inferential Statistics: Parametric
Statistics. The analysis shown in the research are three distinct types that revolve
around the statistics. As stated in the text the three are: “Assessing the quality of
individual items, specifically utilizing independent-Sample t-test (Sedgwick,2010) a
Pearson’s Correlation Coefficient Analysis (Obilor et al., 2018). The second type
consisted of Factor Analysis aimed at exploring the dimensions or structures of specific
characteristics of the items, which included both Exploratory Factor Analysis and
Confirmatory Factor Analysis and Confirmatory Factor Analysis. The third type involved
Inferential Statistics, with a particular focus on SEM Analysis (Stein et al., 2012).)
Concept relationships with the PowerPoints
The article discusses the concepts of understanding and learning cybersecurity through
module threes slides, like focusing on multi-method research (combining multiple types
of research). While also using module twos principles of social science. Lastly it also
covers Human Factors from Module four.
Challenges, Concerns, and Contributions
The Challenges that this article of research is the continuous evolution of cybersecurity
and cyberthreats as it continuously becomes more and more sophisticated. Another is
the validation of the results gathered from the research. The concerns of this are the
ethical neutrality as it is crucial when it comes to developing the instrument, another is
the way the instrument is made as its intended for undergraduates and not students of
different grades. The Contribution of this article is the measurement tool, The
awareness that the article spreads, and the future impacts that it might spark for
research on the topic.
Conclusion
So as seen and was explained the article explains well how the measurement tool used
to help with and evaluate Undergraduates behavior on cybersecurity with the help of the
data that was used to help the tool.
References
Ngamcharoen, P., Sakdapat, N., & Bhanthumnavin, D. E. (2024). Development and
Evaluation on Cybersecurity Behavior Measurement Instruments for Undergraduate
Students [Review of Development and Evaluation on Cybersecurity Behavior
Measurement Instruments for Undergraduate Students]. International Journal of Cyber
Criminiology, 18(1), 139–156.
https://cybercrimejournal.com/menuscript/index.php/cybercrimejournal/article/view/351/
103
Tucker, L. R., & MacCallum, R. C. (1997). Exploratory factor analysis. Unpublished
manuscript, Ohio State University, Columbus,1-
459.https://www.ffzg.unizg.hr/psihologija/phm/nastava/Book_Exploratory%20Factor%20
Analysis.PDF
Sedgwick, P. (2010). Independent samples t test. Bmj, 340,1-
2.https://doi.org/10.1136/bmj.c2673
Obilor, E. I., & Amadi, E. C. (2018). Test for significance of Pearson’s correlation
coefficient. International Journal of Innovative Mathematics, Statistics & Energy Policies,
6(1),11-23.https://www.researchgate.net/profile/Esezi-IsaacObilor/publication/343609693_Test_for_Significance_of_Pearson’s_Correlation_Coeffici
ent_r/links/5f33ebbf458515b72918a25b/Test-for-Significance-of-Pearsons-CorrelationCoefficient-r.pdf
Stein, C. M., Morris, N. J., & Nock, N. L. (2012). Structural Equation Modeling. In R. C.
Elston, J. M. Satagopan, & S. Sun (Eds.), Statistical Human Genetics: Methods and
Protocols(pp. 495-512). Humana Press. https://doi.org/10.1007/978-1-61779-555-8_27