Dynamic notes acrossing layers

Many challenges in note-taking during the learning process stem from limitations in cognitive abilities and working memory capacity, which often prevent notes from achieving their intended effectiveness. AI-driven contextual support can effectively address these limitations while fostering active engage-ment in learning.

The core idea of this diploma project is leveraging AI’s context-building capabilities to create easy and accessible context support for learners to better engage with their studies and navigate freely along the learning chain.



This system offers three levels of information tailored to different stages of learning:
--Full Text Mode, Designed to establish a comprehensive framework of the topic, it provides a rich learning context as its foundation. It is ideal for users preparing for or actively engaging in lectures, helping them dive deeply into the subject matter.

--Extend Mode, Focused on strengthening the connection between notes and their background context, it promotes deeper learning by uncovering and creating meaningful links. It is best suited for users seeking to maintain a continuous encoding process throughout their learning journey.

--Review Mode, Simplifying the topic to its core essentials, it is designed for efficient and engaging content presentation, coupled with opportunities for self-reflection. It is perfect for users who have diverse purposes for their notes, such as quick reviews or targeted revisions.



For practical use, the system is designed for versatile use, integrating with iOS and being a part of apple intelligence to let users gather and incorporate materials from anywhere and anytime. It is not limited to browsers or specific software, which also lowers the threshold to access and enhances flexibility.


 

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Tianyi Shi / tianyi.shi@stud.aho.no