Towards a Digital Twin for Lifelong Learning

Abstract

With time, most people spend their lives in a digital world, hooked up to different services provided by various internet companies. This is great for companies or organizations to display ads based on their user behavior. However, this has an adverse effect on user productivity by spending a lot of time on social media for momentary pleasures. Many organizations have taken additional steps to address this problem, like Apple introduced a new feature in IOS 14, Focus to disable application notifications so people can focus on their work. Similarly, Google added a feature in YouTube to show how much time is spent on YouTube for personal reflection. However, other organizations aren't as socially responsible compared to the above, and they're enticing users to spend more time in the digital world. To address this problem, the same technology empowering ads personalization can be utilized to provide digital learning personalization based on individuals' behavior metrics. This can enable the users of such technology to spend their time based on their own self-improvement goals as part of life-long learning. Therefore in this work, we propose a framework of a conversational digital twin agent that can assist in personalized learning.