Enhance learning with My Learning Talk @Polimi
Artificial intelligence for personalized, autonomous, and transdisciplinary learning
Context
In a learning environment with a large number of students, artificial intelligence enables an unprecedented level of personalization in the educational experience.
It can adapt content and activities to individual needs, fostering meaningful and transdisciplinary learning that addresses the educational demands of today’s complex context.
MyLearningTalk: Artificial intelligence enhancing Politecnico di Milano courses
Conversational exploration of content
MLT supports learning through a conversational approach, offering suggestions and related insights, encouraging active exploration of content in various directions.
Concrete examples and tailored feedback
MLT provides concrete examples based on students preferences and attitudes and personalized feedback related to the level of the interaction
Curated content produced by Politecnico di Milano Faculty
MLT uses course-specific content as the primary basis for the answers. It provides specific links to resources (handouts, videos, etc.) for further useful insights.
A new learning approach
MLT supports innovative learning methods that leverage all the opportunities provided by Large Language Models and the wide range of available resources, addressing the complex challenges of today’s educational context.
The content and activities proposed by MLT are tailored to meet the unique needs and interests of each individual, bridging knowledge gaps and strengthening skills.
MLT promotes active and independent exploration of educational materials, enabling deeper engagement with topics of interest through conversational interaction.
MLT promotes the exploration of connections within the content of an individual course and across various disciplines, fostering the development of a comprehensive and interconnected perspective
Dynamic and Flexible Exploration
An early version of MLT was tested in two courses at Politecnico di Milano: Teaching Strategies (PhD program) and Algorithmic Game Theory (Master’s program).
MLT facilitates the creation of connections between course content and external resources, promoting an integrated and cohesive understanding of knowledge while encouraging students to explore topics of individual interest.
Future developments
Interface extension
MLT will continuously introduce new features designed to stimulate students’ curiosity and enhance their ability to analyze, understand, and consolidate knowledge and skills. These features include visual mapping of explored content, suggested prompting questions, and process-oriented feedback.
Scalable architecture
Future phases will focus on enhancing MLT’s scalable architecture to handle a growing number of university courses and simultaneous users more efficiently.
Integration with Massive Open Online Courses Platforms
Building on its current integration with videos created for Polimi Open Knowledge, the next steps of the project will focus on connecting with MOOC platforms. This will enable the creation of AI-enhanced learning pathways designed to help students achieve their learning goals more effectively.
News and papers
MLT articlesEmbracing the EdTech Revolution
Ambition, n° 76, ottobre 2024Unlocking the power of AI to deliver next generation learning
University World News, giugno 2024Polimi: 160 anni di innovazione guardando al futuro con l’Intelligenza Artificiale
Il Sole 24 ORE, novembre 2023MyLearningTalk: la chat con intelligenza artificiale per gli studenti del Politecnico
milanotoday.it, novembre 2023