In deliverable D7.2, which was the initial version of the tailoring process, we defined the RTP and described how the RTP can be applied in the development process of the aeronautics domain. Deliverable D7.4 was built upon the initial version by refining the tailoring steps and updating the whole process based on experiments and inputs from the preceding work packages (mainly the tailoring rules derived in WP1, D1.5). The current version of the tailoring process applied to the AdCoS is described in section 2 of this document.
The main objective of this deliverable is to describe the current tailoring process in each of the two AdCoS composing the use case of the aeronautics domain.
The first AdCoS is the DivA (Diversion Assistant), whose intended function is to provide the user with all necessary information in order to choose an appropriate alternate airport. Some degree of automation in the data pre-arranging process will be involved, but the final decision is expected to be made by the crew. The functionality will provide the crew with only relevant data presented in a way that will ease the crew’s decision making process.
The second AdCoS is the EATT (Enhanced Adaptive Transition Training), which is an adaptive, model-based transition training tool that accounts for the trainees’ previous experience. Based on cognitive task models, learning theory-based models and system comparisons, EATT provides training that emphasizes the differences between two aircraft types (e.g. B737 and A320), identifies areas of higher training requirements (e.g. when procedures significantly differ or only “mask” to be identical), areas of less effort and also allows for an enhanced learning curve by redistributing training tasks to an optimum level. This tailoring process is referred to the HF-RTP, to the MTTs chosen to improve each AdCoS development and to the interoperability between MTTs.