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.

翻译：动手实践的计算机教育需要一个真实的学习环境，使学生能够获得并深化技能。现有的学习环境（包括虚拟和物理实验室）为学生提供真实的计算机系统，但很少能根据学生不同的技能水平和背景进行个性化调整。我们设计了一种独特新颖的智能环境，用于网络安全技能的适应性训练。该环境收集学生的多种数据，为其分配合适的学习路径。为实现这种适应性，我们提出、开发并部署了一种新的导师模型和训练模式。我们通过两次不同的适应性训练对该学习环境进行了评估，共有114名不同技能水平的学生参与。结果表明，学生被分配了难度更合适的任务，从而能够成功完成训练。学生反馈称，他们享受训练过程，认为训练难度设计合理，并愿意参加更多类似训练。教师可将该环境用于教授任何涉及真实计算机网络和系统的主题，因其并非针对特定训练而定制。我们已免费发布该软件及示例训练，以便其他教师在教学实践中借鉴这些创新。