Programma della conferenza

In the field of linguistic education, the application of generative artificial intelligence (AI) technologies, such as ChatGPT, is opening new avenues for enhancing language learning. This study focuses on a literature review and exploration of generative AI tools for developing linguistic competencies in the teaching of Spanish as a foreign language (ELE). Through an exhaustive review of existing literature, the main trends, applications, and effectiveness of these technologies in the educational context are identified. It examines how generative AI tools can personalize learning, provide interactive practices, and enhance the acquisition of linguistic skills in vocabulary, grammar, reading comprehension, and communicative competence.

Furthermore, the pedagogical and technical challenges associated with integrating AI into the ELE curriculum are explored, including the need to adapt these tools to specific learning objectives and ensure the cultural and linguistic relevance of the generated content. This analysis is complemented by the exploration of case studies and practical examples illustrating the effective application of generative AI in ELE learning environments.

The review emphasizes the importance of a well-defined pedagogical strategy that incorporates generative AI as a complement to traditional teaching methodologies, rather than as a substitute. Implications for the design of teaching materials, teacher training, and the assessment of linguistic competencies are discussed. The study concludes by highlighting the transformative potential of generative AI in ELE learning and suggests future directions for research and educational practice in this emerging field.

First-year Computer Science students often struggle to learn Java programming, and this condition can have a negative impact on their academic progress. Recently, an online tutoring system has been developed to help students learn Java programming. It allows students to execute and check Java code, making the learning process easier. Although the use of this tool has led to improvements in learning, it has been observed that the system has some weaknesses that need to be improved. The gap consists in the lack of specific and personalised feedback for the students. Therefore, a specific software has been developed, with an innovative approach based on machine learning using auto-clustering and neural networks. The new online tutoring system offers a better personalisation thanks to a graph model which personalises the study plan based on individual performance, optimising educational effectiveness through video tutorials and Java code evaluations. This system aims not only to increase the academic success of the students, but also to provide professors with a more precise assessment tool during exams.

The role of the e-tutor, considered strategically important in distance digital education, has taken on over the years multiple characteristics and roles, both due to the need to adapt to innovative and emerging technologies and to effectively integrate with evolving learning modalities and styles. The professional identity and competencies of the e-tutor are, to date, very fluid and still evolving. In the perspective of a strong push towards the digitalization of training processes, bearing in mind the functions and roles of the last two decades, what new identities might the e-tutor assume? The article aims to provide a narrative literature review, starting from Salmon's seminal text in 2000 up to the most recent scientific contributions on the topic, focusing on the evolution of this figure in a university context, with the intent of identifying new areas of study and exploration, especially considering recent applications of generative AI to automated tutoring systems and the significant European investments in the field of digital education.

This paper delves into the application of AI generative tools as co-designers for Master's students specializing in communication design. It builds upon the preceding research undertaken at the Department of Design at the Politecnico di Milano and subsequently presented at Isyde 2023. This exploration seeks to evaluate the efficacy and pedagogical implications of incorporating artificial intelligence in the creative process.

The first part of the paper offers an in-depth analysis of the genealogical evolution of Artificial Intelligence in Education (AIeD), contextualizing it - Jordan & Mitchell (2015), Agrawal, Gans, & Goldfarb (2018), Chui, Manyika, & Miremadi (2016) - thereby underpinning the efficacy of AI as a pivotal tool in learning experience (Di Rosario, Ferri, 2023).

The second part analyses two case-studies. Last year, an initial experiment was carried out with a class, which uncovered various methods and activities designed for assignment objectives within the Digital Culture course. Students were tasked with creating ten digital culture products, utilizing Generative AI as co-designers.

The ongoing research has been enhanced with the integration of another case study. In this case, particular emphasis was placed on the use of generative techniques in the development of programs and concepts that could be integrated into various types of monographic courses, from those dealing with media aesthetics to those concerning privacy and security.

Both experiments aimed to integrate advanced AI technology into the educational framework, providing insights into the collaborative dynamics between students and AI in the design process.