The boarding process of an aircraft is one of the identified bottlenecks in the turnaround when aircraft arrives to an airport.
In this article, we elaborate on the role of dialogical learning in identity formation in the context of environmental education. First, we distinguish this kind of learning from conditioning and reproductive learning. We also show that identity learning is not self-evident and we point out the role of emotions. Using Dialogical Self Theory, we then suggest that individuals do not have an “identity hierarchy” but a dialogical self that attaches meaning to experiences in both conscious and unconscious ways. We describe the learning process that enables the dialogical self to develop itself, and we elaborate on the characteristics of a good dialogue. We conclude with some remarks expanding room for a dialogue that would foster identity learning. https://doi.org/10.3390/resources5010011 https://www.linkedin.com/in/helenkopnina/
MULTIFILE
This paper presents a comprehensive study on assisting new AI programmers in making responsible choices while programming. The research focused on developing a process model, incorporating design patterns, and utilizing an IDE-based extension to promote responsible Artificial Intelligence (AI) practices. The experiment evaluated the effectiveness of the process model and extension, specifically examining their impact on the ability to make responsible choices in AI programming. The results revealed that the use of the process model and extension significantly enhanced the programmers' understanding of Responsible AI principles and their ability to apply them in code development. These findings support existing literature highlighting the positive influence of process models and patterns on code development capabilities. The research further confirmed the importance of incorporating Responsible AI values, as asking relevant questions related to these values resulted in responsible AI practices. Furthermore, the study contributes to bridging the gap between theoretical knowledge and practical application by incorporating Responsible AI values into the centre stage of the process model. By doing so, the research not only addresses the existing literature gap, but also ensures the practical implementation of Responsible AI principles.
MULTIFILE
