Researchers from Clemson University with expertise in mathematics education, human-centered artificial intelligence (AI) and cybersecurity have received funding from the National Science Foundation (NSF) to teach middle school students from a rural school district in South Carolina about the AI-related cybersecurity risks that are a part of their everyday online activities.
Researchers will use metaphors grounded in mathematics as a strategy to provide accessible entry points to complex concepts for middle school students. Researchers hope this approach will aid students in the development of AI-related cybersecurity literacies and help them adopt positive changes in their online privacy and security practices.
According to Nicole Bannister, associate professor in the College of Education and principal investigator on the project, it is crucial for adolescents to develop AI-related cybersecurity literacies so that they may effectively and responsibly take ownership of their digital identities. Bannister said that can be accomplished when teachers connect AI and cybersecurity principles to their mathematical underpinnings.
“AI is very good at posing as a human or inferring things about you that you didn’t tell it and yet we don’t connect the dots,” Bannister said. “We take unnecessary risks with our online privacy and security practices all the time—even when we know better or have had ‘best practices’ training—because the relationship between our practices and the inner workings of these advanced technologies can seem more like magic than science.”
Bannister and her fellow researchers hope to illustrate to students that this “magic” is just science that they don’t yet understand. They will work with teachers to examine math concepts middle school students are studying and introduce metaphors that explain cybersecurity risks in ways that are meaningful and relevant to students, thus bridging these ideas together.
Bart Knijnenburg, assistant professor in the Clemson University School of Computing and co-principal investigator on the project, finds it helpful to start with the cybersecurity and AI concepts teachers want to get across to students and help them work their way to a corresponding math concept, metaphor and example. If the team wants to communicate the importance of risky data sharing, for example, they would communicate this using the metaphor of a spreading infection, which also can explain the math concept of exponential growth.
“The ‘light bulb’ moment for students can occur after they’ve gained an understanding of these concepts and are given the example of the mounting cybersecurity risk posed to them when their data is shared,” Knijnenburg said.
Kelly Caine, Dean’s Associate Professor in the Human-Centered Computing Division of the School of Computing, said she is enthusiastic about working with both Bannister and Knijnenburg because all three of them bring very different expertise to the project. While Bannister brings knowledge of student learning and math curriculum and Knijnenburg brings AI expertise, Caine’s area of expertise involves cybersecurity and communicating those concepts to a variety of audiences.
“Before this, I hadn’t gotten the opportunity to really dig into how metaphors may help people understand the issues AI compounds in cybersecurity,” Caine said. “Cybersecurity issues are already so pressing and consequential that we don’t always get the opportunity to be so forward-looking. If we find that metaphors help a student population, the same approach may very well help older users understand the risks AI poses to their own cybersecurity.”
The team has been working closely with partner educators to prepare for the first phase of the study, which involves identifying students’ interests and their baseline understandings of AI, cybersecurity and mathematics. The team’s analyses of this data will inform the development of the modules that address these ideas in depth in the next phase of the study that is set to launch at the beginning of the next school year. The research team set an ambitious timeline for the two-year project and has been working steadily since the summer to get the project underway while also supporting the graduate researchers working on the team.
The research team foresees some challenges in data collection in schools simply because the future related to student attendance during the COVID-19 pandemic is, by definition, up in the air. However, Caine said the researchers are eager to get started because of the potential to “answer a question that hasn’t been answered before” and to positively affect a population that would carry with it a long-term impact in the area of cybersecurity.
“It’s exciting to think broadly about how people learn core ideas in mathematics and complex AI-related cybersecurity practices, as well as to investigate what gets in the way of students’ learning and enacting these practices,” Bannister said. “This research is considered high-risk-high-reward because attending to all three concepts at once has not been done before. However, with an evidence-based, integrated approach, students are expected to learn fundamental math ideas and gain an understanding of cybersecurity threats that could protect them for the rest of their lives.”
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