Retention and Transfer of Zero-Trust Configuration Skills Following Laboratory Training: A Longitudinal Assessment
Abstract
Cloud-security skills acquired in a laboratory may decay or fail to transfer when engineers encounter unfamiliar interfaces and production constraints. We followed 94 participants for 12 weeks after a zero-trust configuration course and assessed retention at 2, 6, and 12 weeks using progressively novel tasks involving identity policy, segmentation, service-to-service authentication, and exception handling. Accuracy declined modestly between immediate post-test and week 12, but participants retained core policy concepts better than vendor-specific command sequences. Transfer performance was highest among learners who had completed spaced retrieval exercises after the course. At week 12, this subgroup achieved 81% correct configuration compared with 68% among participants without retrieval practice. Errors involving implicit trust relationships and inherited permissions persisted across all time points. Self-rated confidence correlated only weakly with actual task performance. The results indicate that zero-trust training should include delayed practice and scenario variation if the goal is durable operational competence. Retention assessment also benefits from testing underlying security principles separately from interface-specific procedural memory.
References
1. Nazir M. Effectiveness of hands-on lab training for improving zero-trust and identity-access management competencies among hybrid cloud engineers. Journal of Computing, Intelligence and Information Sciences. 2023. Available from: https://jciis.com/index.php/jciis/article/view/2023-01-02
2. Rose S, Borchert O, Mitchell S, Connelly S. Zero trust architecture. Gaithersburg (MD): National Institute of Standards and Technology. 2020;NIST SP 800-207. doi:10.6028/NIST.SP.800-207.
3. Swanson M, Bowen P, Phillips AW, Gallup D, Lynes D. Contingency planning guide for federal information systems. Gaithersburg (MD): National Institute of Standards and Technology. 2010;NIST SP 800-34 Rev. 1. doi:10.6028/NIST.SP.800-34r1.
4. Grance T, Nolan T, Burke K, Dudley R, White G, Good T. Guide to test, training, and exercise programs for IT plans and capabilities. Gaithersburg (MD): National Institute of Standards and Technology. 2006;NIST SP 800-84. doi:10.6028/NIST.SP.800-84.
5. Petersen R, Santos D, Wetzel K, Smith MC, Witte G. Workforce framework for cybersecurity (NICE Framework). Gaithersburg (MD): National Institute of Standards and Technology. 2020;NIST SP 800-181 Rev. 1. doi:10.6028/NIST.SP.800-181r1.
6. Sweller J. Cognitive load during problem solving: effects on learning. Cogn Sci. 1988;12(2):257-285. doi:10.1207/s15516709cog1202_4.
7. Salas E, Tannenbaum SI, Kraiger K, Smith-Jentsch KA. The science of training and development in organizations: what matters in practice. Psychol Sci Public Interest. 2012;13(2):74-101. doi:10.1177/1529100612436661.
8. Sitzmann T. A meta-analytic examination of the instructional effectiveness of computer-based simulation games. Pers Psychol. 2011;64(2):489-528. doi:10.1111/j.1744-6570.2011.01190.x.
9. Hart SG, Staveland LE. Development of NASA-TLX (Task Load Index): results of empirical and theoretical research. Adv Psychol. 1988;52:139-183. doi:10.1016/S0166-4115(08)62386-9.
10. Hattie J, Timperley H. The power of feedback. Rev Educ Res. 2007;77(1):81-112. doi:10.3102/003465430298487.
11. Freeman S, Eddy SL, McDonough M, Smith MK, Okoroafor N, Jordt H, et al. Active learning increases student performance in science, engineering, and mathematics. Proc Natl Acad Sci U S A. 2014;111(23):8410-8415. doi:10.1073/pnas.1319030111.
12. Salas E, DiazGranados D, Klein C, Burke CS, Stagl KC, Goodwin GF, et al. Does team training improve team performance? A meta-analysis. Hum Factors. 2008;50(6):903-933. doi:10.1518/001872008X375009.
13. Baldwin TT, Ford JK. Transfer of training: a review and directions for future research. Pers Psychol. 1988;41(1):63-105. doi:10.1111/j.1744-6570.1988.tb00632.x.
14. Arthur W Jr, Bennett W Jr, Edens PS, Bell ST. Effectiveness of training in organizations: a meta-analysis of design and evaluation features. J Appl Psychol. 2003;88(2):234-245. doi:10.1037/0021-9010.88.2.234.
15. Aguinis H, Kraiger K. Benefits of training and development for individuals and teams, organizations, and society. Annu Rev Psychol. 2009;60:451-474. doi:10.1146/annurev.psych.60.110707.163505.
16. Lakens D. Sample size justification. Collabra Psychol. 2022;8(1):33267. doi:10.1525/collabra.33267.
17. Nosek BA, Ebersole CR, DeHaven AC, Mellor DT. The preregistration revolution. Proc Natl Acad Sci U S A. 2018;115(11):2600-2606. doi:10.1073/pnas.1708274114.
18. Lakens D. Calculating and reporting effect sizes to facilitate cumulative science: a practical primer for t-tests and ANOVAs. Front Psychol. 2013;4:863. doi:10.3389/fpsyg.2013.00863.
Published
Issue
Section
License
Authors retain copyright. Articles published under the Creative Commons Attribution 4.0 International licence (CC BY 4.0) may be shared and adapted for any purpose, including commercially, provided appropriate credit is given, a link to the licence is supplied, and changes are indicated. No additional legal or technological restrictions may be imposed. Third-party material is included only where its credit line permits. Licence: https://creativecommons.org/licenses/by/4.0/. Earlier publications remain subject to their stated licence and author agreements unless the rights holder authorizes a change.
