TY - JOUR
T1 - SCIPS
T2 - A serious game using a guidance mechanic to scaffold effective training for cyber security
AU - O'Connor, Stuart
AU - Hasshu, Salim
AU - Bielby, James
AU - Colreavy-Donnelly, Simon
AU - Kuhn, Stefan
AU - Caraffini, Fabio
AU - Smith, Richard
N1 - Publisher Copyright:
© 2021 Elsevier Inc.
PY - 2021/11
Y1 - 2021/11
N2 - Training effective simulation scenarios presents numerous challenges from a pedagogical point of view. Through application of the Conceptual Framework for e-Learning and Training (COFELET) as a pattern for designing serious games, we propose the use of the Simulated Critical Infrastructure Protection Scenarios (SCIPS) platform as a prospective tool for supporting the process of providing effective cyber security training. The SCIPS platform is designed to run different scenarios, such as examples in financial forecasting and business infrastructures, with an initial scenario developed in collaboration with industrial partners focusing on an electricity generation plant. Focus groups from these sources were conducted to identify design and developmental considerations for the platform. As an extension from the COFELET framework, we propose an intelligence scaffolding practice as a guidance mechanic taking the form of an agent within the scenario. The agent represents a major innovation in the system and we envisage a deep learning-based augmentation to further adapt towards the behavioural aspects of learners.
AB - Training effective simulation scenarios presents numerous challenges from a pedagogical point of view. Through application of the Conceptual Framework for e-Learning and Training (COFELET) as a pattern for designing serious games, we propose the use of the Simulated Critical Infrastructure Protection Scenarios (SCIPS) platform as a prospective tool for supporting the process of providing effective cyber security training. The SCIPS platform is designed to run different scenarios, such as examples in financial forecasting and business infrastructures, with an initial scenario developed in collaboration with industrial partners focusing on an electricity generation plant. Focus groups from these sources were conducted to identify design and developmental considerations for the platform. As an extension from the COFELET framework, we propose an intelligence scaffolding practice as a guidance mechanic taking the form of an agent within the scenario. The agent represents a major innovation in the system and we envisage a deep learning-based augmentation to further adapt towards the behavioural aspects of learners.
KW - Collaborative learning
KW - Cooperative learning
KW - Incident training
KW - Serious games
KW - Simulations
UR - http://www.scopus.com/inward/record.url?scp=85118766042&partnerID=8YFLogxK
U2 - 10.1016/j.ins.2021.08.098
DO - 10.1016/j.ins.2021.08.098
M3 - Article
AN - SCOPUS:85118766042
SN - 0020-0255
VL - 580
SP - 524
EP - 540
JO - Information Sciences
JF - Information Sciences
ER -