K-12 schools utilize a growing number of technologies to operate effectively, ranging from technologies for learning to technologies that manage student and personnel data. We share findings from an analysis of 23 school district websites for technologies used in a number of K-12 school districts surrounding a public, research university in a southeast region of the United States. In addition, we also share findings on technologies used in K-12 school districts from interviews with 12 technology directors. We propose a technology classification framework including educational technologies, management technologies, support technologies, networking technologies, and security technologies in addition to identifying various technologies that are currently used by school districts based on this framework. This framework has implications for K-12 technology adoption and clarifying the roles of school technology personnel.
Uncovering Privacy and Security Challenges In K-12 Schools
Increased use of technology in schools raises new privacy and security challenges for K-12 students---and harms such as commercialization of student data, exposure of student data in security breaches, and expanded tracking of students---but the extent of these challenges is unclear. In this paper, first, we interviewed 18 school officials and IT personnel to understand what educational technologies districts use and how they manage student privacy and security around these technologies. Second, to determine if these educational technologies are frequently endorsed across United States (US) public schools, we compiled a list of linked educational technology websites scraped from 15,573 K-12 public school/district domains and analyzed them for privacy risks. Our findings suggest that administrators lack resources to properly assess privacy and security issues around educational technologies even though they do pose potential privacy issues. Based on these findings, we make recommendations for policymakers, educators, and the CHI research community.
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- Award ID(s):
- 2047465
- NSF-PAR ID:
- 10407360
- Date Published:
- Journal Name:
- Human factors in computing systems
- ISSN:
- 1062-9432
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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