Abstract
SecTutor is a tutoring system that uses adaptive testing to select instructional modules that allow users to pursue secure programming knowledge at their own pace. This project aims to combat one of the most significant cybersecurity challenges we have today: individuals’ failure to practice defensive, secure, and robust programming. To alleviate this, we introduce SecTutor, an adaptive online tutoring system, to help developers understand the foundational concepts behind secure programming. SecTutor allows learners to pursue knowledge at their own pace and according to their own interests, based on assessments that identify and structure educational modules based on their current level of understanding.
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Acknowledgements
This work was supported by grants DGE-1934279 and DGE-2011175 from the National Science Foundation to the University of California Davis, grant DGE-1934269 from the National Science Foundation to Purdue University, and grant DGE-1934285 to the California State University Sacramento. The opinions, findings, and conclusions, or recommendations expressed are those of the author(s) and do not necessarily reflect the views of the National Science Foundation, the California State University, Purdue University, and the University of California Davis.
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Ngambeki, I. et al. (2022). SecTutor: An Intelligent Tutoring System for Secure Programming. In: Drevin, L., Miloslavskaya, N., Leung, W.S., von Solms, S. (eds) Information Security Education - Adapting to the Fourth Industrial Revolution. WISE 2022. IFIP Advances in Information and Communication Technology, vol 650. Springer, Cham. https://doi.org/10.1007/978-3-031-08172-9_2
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DOI: https://doi.org/10.1007/978-3-031-08172-9_2
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