This Small Business Innovation Research (SBIR) Phase I project seeks to create a knowledge and training system that will reliably enable trainees and students to learn more material at a faster rate in any sector of society while, in the process: 1) advancing the scientific knowledge of the pedagogical underpinnings of learning acceleration (specifically through a better understanding of the independent and combined effects of content filtering, intelligent tutoring, and increased learner engagement), and 2) creating a cybersecurity training lesson that will have immediate applications in the military, in government and in education. The intellectual contribution of the project stems from its work in two parallel domains, the first empirical, the second technological. On the empirical front, the project would likely be the first to experimentally assess the individual and combined impacts of content filtering, intelligent tutoring and physiologically-measured, gaming-induced learner engagement on speed to mastery. Technologically, the project would enhance the functionality of a learning content authoring, delivery and management system through the development of: 1) a predictive learner modeling subsystem running on a portable, extensible tool set that supports content filtering and intelligent tutoring, and 2) configuration parameters for a scenario-based gaming engine.
Learning acceleration is a fundamental and central, yet largely unattained, goal of the military, corporate and education sectors. While knowledge of the means by which learning speed can be increased is limited, there is solid agreement that major advances in learning acceleration are likely to be technology driven. The project will be conducted within the context of improving cybersecurity and cybersecurity education, thereby focusing on a threat of rapidly increasing magnitude to our national well-being and continued corporate success. Vast improvements in cybersecurity and cybersecurity training and education are widely believed to be necessary to protect the American way of life.
CySET (Cyber Security Education and Training) is an innovative solution that enables learning acceleration through content filtering, intelligent tutoring and gaming-based learner engagement, for use in cyber security training and education. This project created an initial prototype of a knowledge and training system that enables trainees and students to learn more material at a faster rate while, in the process: 1) advancing the scientific knowledge of the pedagogical underpinnings of learning acceleration, and 2) creating a cyber security training lesson that will have immediate applications in the military, in government and in education. Results from the Phase I study provided evidence that adaptive learning pathways may enable participants to learn as much material in substantially less time than those who participate in programs that cover all relevant training material regardless of each trainee's pre-existing knowledge. This result is in alignment with our own research on the need for accelerated learning. Overall, the current research suggests that adaptive learning could result in an efficient training mechanism that allows individuals to only view the information they need (depending on their pre-existing knowledge) without having to complete a full training program. This alone would result in cost savings for employers and less time and frustration for trainees. The current research also suggests partial results of additional knowledge gained when individuals are presented with feedback on their performance throughout training. These results are hopeful for our training system and our next research design in Phase II.
