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So let’s start from the beginning: what is a Digital Twin?

A digital twin is a virtual representation of a system, that is being live updated through a continuous stream of data input.

With this in mind, we decided to create a Digital Twin in the context of learning and education.

As students, we fundamentally resonated with this topic, because we’ve experienced the ups and downs of going through the educational journey in school and university. We have questioned whether or not we were making the right decisions for our future, and often felt at the consequence of this journey, as opposed to in charge of it.

We wanted to discover if this was a widespread issue, or simply a result of our own personal bias. The results were clear: the current educational system is obsolete and in dire need of a reform.


We then carried out our user research and sought to understand if this was a prevalent problem in the real world, as our literature review had seemed to suggest.

After carrying out a survey with 90 students of  varying ages, degrees and universities, we found that there is a clear disparity between what people end up doing for their job/degree, and what people value doing the most.

Insert chart.

From this research, and carrying out multiple ideation exercises, we extracted research insights, that then became our design objectives, which were the wireframe to lay out our final concept and prototype.

Queue twin:

Our ultimate goal with this twin, is to create a companion that makes navigating your life in school and university more intuitive and less scary. Twin is a mirror reflection of yourself, that grows with you, and brings to the palm of your hands your entire educational journey, to easily understand and identify the trends in what activities correlate with making you happy, what you’re passionate about, and what you’re good at.

Using the IKIGAI model we break down the types of career paths that you can take into the following: What you love, what you’re good at, what the world needs and what you can be paid for.

Accounting for personal preferences, our learning algorithm uses a weighting system by adding a greater coefficient to the sections of greater importance to the user, to provide the true tailored experience of a twin. The aim is to then find the path that intersects all four in order to become more fulfilled, happy, and ultimately, self aware version of yourself.

Group project with Franciska Kundrak, Felix Murray, Trevor Fung and Imogen Scheel.

At our exhibition, we showed the visual representation of our brainstorming, our prototype demo, and a video with the testimonies of some of the students that we interviewed as research for this project. We simply asked them to reflect on their educational journey, and let them speak freely. Their narratives really served to show why our project is so necessary.


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