This blog post will break down essential questions for evaluating the paper titled “Computer Self-Efficacy, Computer Anxiety, and Attitudes toward the Internet: A Study among Undergraduates in Unimas”. I was particularly interested in this paper due to how antiquated it seems and the now-irrational fears surrounding the internet. The complete allure and mystery of the internet is fascinating two decades later. Especially since many of these same woes and questions are coming back up due to the rise of large language models and more general AI. While now we can see clearly the impacts of the internet and “computer anxiety”, time will only tell for AI and LLMs.
The paper can be found on JSTOR through this link or downloaded here
1. What are the null and alternative hypotheses?
The study investigates relationships between computer anxiety, self-efficacy, and attitudes toward the Internet among undergraduates. Although the paper does not explicitly state the hypotheses, we can infer:
- Null Hypothesis: There are no significant relationships between computer anxiety, computer self-efficacy, attitudes toward the Internet, and Internet usage patterns.
- Alternative Hypothesis: There are significant relationships between these factors, and demographic factors (like gender and faculty) influence computer anxiety, self-efficacy, and attitudes toward the Internet.
These hypotheses guide the exploration of how variables such as gender, faculty, and time spent on the Internet affect attitudes toward technology.
2. Who is collecting and analyzing this data?
The data collection and analysis were conducted by Hong Kian Sam, Abang Ekhsan Abang Othman, and Zaimuarifuddin Shukri Nordin from the Faculty of Cognitive Sciences and Human Development, Universiti Malaysia Sarawak (Unimas). Their expertise lies in understanding human development in educational and technological contexts. Aside from research papers, not much about them is available online. This may be relevant later in the discussion of whether publish or perish has impacted this study and how the authors of this paper are researchers by occupation.
3. What datasets does this study reference or use? Are these datasets available to the public?
This study uses original data collected from 148 undergraduates at Unimas through surveys, including:
- Computer Anxiety Rating Scale (CARS): Measuring computer anxiety.
- Internet Attitude Scale (IAS): Assessing attitudes toward the Internet.
- Computer Self-Efficacy Scale (CSE): Gauging confidence in computer use.
The data used in this study is not publicly available, as it was collected through a specific survey for this research. The questionnaire details are included in the paper’s appendix, but the raw data remains private.
I would put the scales used here, but they are far too long and extensive to be included verbatim. Please refer to the Appendix for more details about the scales (CARS, IAS, CSE).
4. Why are they interested in this data?
The researchers are interested in understanding how students’ confidence in using computers (self-efficacy), their anxiety around technology, and their attitudes toward the Internet impact their academic behavior and outcomes. This is relevant in a world where computer literacy is crucial for professional success, especially in higher education. Especially, in 2005, when internet use and computer self-efficacy are not nearly as prevalent as they are today. The study also seeks to challenge longstanding gender biases in computer use by exploring differences between male and female students in Malaysia.
5. What data is being recorded? What data might be left out?
The study records:
- Demographics (age, gender, faculty).
- Internet usage patterns (time spent, purposes for usage like research or entertainment).
- Computer anxiety (as measured by CARS).
- Attitudes toward the Internet (via IAS).
- Computer self-efficacy (measured by CSE).
Left out data might include:
- Qualitative data about why students feel anxious or confident, and how they engage with technology in detail.
- Other psychological or social factors influencing computer use, such as personal motivations, learning styles, or socioeconomic background.
6. What evidence did they present to back up their conclusions?
The study provides statistical evidence using various measures:
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T-tests and ANOVAs to assess differences in computer anxiety, self-efficacy, and attitudes across gender and faculty.
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Chi-square tests to examine relationships between Internet usage patterns and attitudes.
For example, undergraduates from the Faculty of Computer Science showed significantly higher self-efficacy, indicating that discipline plays a role in confidence with technology. Honestly, I do not know much about these tests, so I can’t provide as much context as I would like.
7. How was this study funded?
The paper does not explicitly mention funding sources. However, given that the research is conducted by faculty at Unimas, it is likely supported by the university’s internal resources. Additionally, the journal in which the study is published (Educational Technology & Society) collaborates with JSTOR, suggesting potential access to broader academic resources. The journal is pretty well known listed #15 in Google Scholar Top Publications in Educational Technology and 22nd among 756 journals with all indexes (SSCI; SCIE; ESCI) under the category of education & educational research, placing the journal in a high position among key journals in our field (via the Educational Technology & Society website).
8. Do you think publish or perish had an effect on this study?
Publish or perish—the pressure on academics to publish work regularly to sustain their careers—might have influenced the study. While the research addresses important questions, its focus on traditional academic measures (like t-tests and chi-square tests) may reflect a goal of producing results quickly, possibly limiting the depth of analysis on underlying psychological factors. However, the study’s careful attention to a relevant and underexplored demographic (Malaysian undergraduates) suggests a genuine academic interest, beyond mere publication pressure.
Conclusion
This study provides valuable insights into how computer anxiety, self-efficacy, and Internet attitudes vary among students. While gender differences did not play a significant role, the field of study emerged as an influential factor. By exploring these dimensions, the research highlights the evolving relationship between students and technology—a crucial factor in shaping their educational and professional futures.