Data Privacy Paradox: The Role of Higher Education Institutions Towards Building Data Privacy Awareness in the Digital Age
This study determined the perceptions (or misconceptions) of students towards data privacy. Toward this goal, 31 (8 groups with three to four members per group) third-year Information Technology students participated in a 2-day workshop. In the first part of the workshop, participants were asked to rank different five computerized systems using their self-selected software quality criteria. Presentation workshop sessions were conducted to explain their rankings on the five computerized systems (online banking, national identification, payroll, Facebook, and learning management systems). The majority of the students agreed that online banking and payroll systems are the most sensitive computerized systems since these involve money. On one hand, data gathered in a learning management system, the proposed national ID system, and Facebook are the least data-sensitive systems primarily because, according to the participants, these systems do not process financial transactions. It is worth noting that participants perceived that systems that contain and process non-financial transactions are not as sensitive as compared to the systems that handle financial transactions. These findings indicate that the students are less sensitive to the issues of a possible data breach and are not proactive in addressing possible threats. This belief contributes to the conceptions and misconceptions towards the phenomenon the authors called the data privacy paradox. Implications for data privacy awareness are offered in the paper
Authors
- Rolando R. Lansigan
- Rex P. Bringula (ORCID: https://orcid.org/0000-0002-1789-9601)
- Ma. Carmela Racelis
- Precious Leona G. Lansigan
- Patricia Lorraine G. Lansigan
Institutions
- Adamson University (PH)
- University of the East (PH)
Publication Details
- Published
- 2024-11-19
- DOI
- https://doi.org/10.1109/iceed62316.2024.10923801
- Primary Topic
- Information Retrieval and Data Mining
- Type
- article
- Field-Weighted Citation Impact
- 0.00