GAINS - Gender-Sensitive Artificial Intelligence-Supported Learning

Initial situation: Current technical developments in the area of artificial intelligence (AI) and mixed-reality devices open up new opportunities to convey complex teaching content in a gender-sensitive and remotely accessible manner. This means that there is a great potential to improve the communication of technical contents and thus, to make the training for pilots and technicians gender-sensitive. With less than 10% female pilots worldwide, women are severely underrepresented in aviation. At the same time, there is a global shortage of pilots, which will increase sharply in the coming years. In addition, gender-sensitive differences/obstacles in the area of training are also described such as biased treatment and feedback by instructors, which could be addressed through standardized and partially automated forms of AI-based training and feedback. However, the development of new AI-supported forms of training also brings with it challenges in the areas of avoiding gender bias and complying with ethical standards. Current software quality frameworks insufficiently cover AI-specific aspects. Thus, there is need for research in the area of assessing the quality in use of AI-based software systems. Goals/Results: The aim of this project is to investigate modern and gender-sensitive training options that are supported by AI. The project GAINS focuses on the gender-sensitive research of preferences and needs for AI-supported training materials for conveying technical contents in the area of adult education. The aviation domain was chosen because it is representative both in terms of the existing gender gap in technology and, in terms of the high teaching standards. Therefore, this project in the aviation domain can initiate research, technology and innovation with gender-relevant content. Based on a systematic literature analysis, expert workshops and the Use Case Technology Mapping (UCTM) framework, relevant use cases for AI-supported teaching of technical content in the field of aviation will be identified and evaluated based on their gender-sensitive, social, economic, and ecological potential (WP2). Furthermore, a survey will be carried out with different age and gender groups of pilots, instructors and student pilots on the topics of acceptance, preferences, ethical and gender-relevant aspects of AI-supported training, with particular attention to the previously identified potential use cases (WP4). Based on the systematic survey and multi-dimensional evaluation of potential use cases (WP2) for AI and the intersectional study on acceptance and preferences of AI in the teaching of technical content (WP4), future-relevant gender-sensitive research areas will be derived and a proof-of-concept for possible teaching concepts with a specific gender dimension will be evaluated (WP5). In order to enable the evaluation of future AI-based applications in terms of their software quality in use, existing software development standards will be examined and a new framework will be proposed that addresses AI-specific aspects such as ethics, gender sensitivity and software quality metrics (WP3). The use of an improved software quality in use frameworks is intended to increase the quality of future developments of AI-based applications.