Home > News > Company News > Astrom shows new system and CBT courseware at CATES2018
详细内容

Astrom shows new system and CBT courseware at CATES2018

May,2018,Astrom Aviation Technology Inc. has attended 8th China Aviation Training & Education Summit (CATES)2018 at Shanghai Hongqiao Airport Hotel.

CATES is an independent and biggest aviation training platform in China that regularly attracts airline personnel, government and regulatory officials, industry professionals and academics. 80% Participants come from Chinese airlines to learn, educate and exchange views on improving the efficiency and effectiveness of flight training operations and procedures. CATES2018 has attracted over 300 attendees from Emirates, Air France-KLM, Delta Airlines, Air China, China Southern Airlines, China Eastern Airlines, Hainan Airlines, PABC and so on. Highlights of this conference include Holographic Training, New Captain Training, VR Technology, Pilots Continuous Ability Improvement, CBTA&EBT, Flight Safety etc..

Astrom Aviation shows Self-Adaptive Assessment System(SAAS), Smart Simulator Assessment System(Smart Sim), A350 CBT Courseware and HoloLens at CATES2018 and attracted many experts consuling and discussing.

         

Astrom Self-Adaptive Assessment System is a web-based question management and exam generation tool with CAT algorithms. It can streamline the creation, management and deployment of assessment including question banks, quizzes, exams and surveys. Developed for growing enterprise organizations with wide-ranging date types, SAAS is a system that empowers aviation education through reliability, flexibility and usability. Smart Sim uses leading technology for simulator electronic scoring and assessment. It innovatively combines the simulator training subjects with EBT features.Instead of  scoring on the paper, instructors  can just click  the application to perform scoring operations. The system will help to collect simulator exam data, release exam results and conduct scientific analysis to generate corresponding learning analysis reports.