VYKOPAL, Jan, Pavel ŠEDA, Valdemar ŠVÁBENSKÝ and Pavel ČELEDA. Smart Environment for Adaptive Learning of Cybersecurity Skills. IEEE Transactions on Learning Technologies. 2023, vol. 16, No 3, p. 443-456. ISSN 1939-1382. Available from: https://dx.doi.org/10.1109/TLT.2022.3216345.
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Basic information
Original name Smart Environment for Adaptive Learning of Cybersecurity Skills
Authors VYKOPAL, Jan (203 Czech Republic, guarantor, belonging to the institution), Pavel ŠEDA (203 Czech Republic, belonging to the institution), Valdemar ŠVÁBENSKÝ (703 Slovakia, belonging to the institution) and Pavel ČELEDA (203 Czech Republic, belonging to the institution).
Edition IEEE Transactions on Learning Technologies, 2023, 1939-1382.
Other information
Original language English
Type of outcome Article in a journal
Field of Study 10201 Computer sciences, information science, bioinformatics
Country of publisher United States of America
Confidentiality degree is not subject to a state or trade secret
WWW URL
Impact factor Impact factor: 3.700 in 2022
RIV identification code RIV/00216224:14610/23:00130180
Organization unit Institute of Computer Science
Doi http://dx.doi.org/10.1109/TLT.2022.3216345
UT WoS 001012684000012
Keywords in English adaptive and intelligent educational systems; intelligent tutoring systems; learning environments; virtual labs; security
Tags rivok
Tags International impact, Reviewed
Changed by Changed by: doc. Ing. Pavel Čeleda, Ph.D., učo 206086. Changed: 11/9/2023 09:47.
Abstract
Hands-on computing education requires a realistic learning environment that enables students to gain and deepen their skills. Available learning environments, including virtual and physical labs, provide students with real-world computer systems but rarely adapt the learning environment to individual students of various proficiency and background. We designed a unique and novel smart environment for adaptive training of cybersecurity skills. The environment collects a variety of student data to assign a suitable learning path through the training. To enable such adaptiveness, we proposed, developed, and deployed a new tutor model and a training format. We evaluated the learning environment using two different adaptive trainings attended by 114 students of various proficiency. The results show students were assigned tasks with a more appropriate difficulty, which enabled them to successfully complete the training. Students reported that they enjoyed the training, felt the training difficulty was appropriately designed, and would attend more training sessions like these. Instructors can use the environment for teaching any topic involving real-world computer networks and systems because it is not tailored to particular training. We freely released the software along with exemplary training so that other instructors can adopt the innovations in their teaching practice.
Links
EF16_019/0000822, research and development projectName: Centrum excelence pro kyberkriminalitu, kyberbezpečnost a ochranu kritických informačních infrastruktur
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