How do people Â Learn? How do people process information? How do people remember? and if they do, what and how much do they remember? These were some of the initial questions that drove mine and Ahrianâ€™s research.
Quite often we find ourself dealing with information we donâ€™t really know how to handle. A description of an object found at a museum, a news article explaining the latest discoveries in physics or a book drawing out a map of the neural connection in our brain. Incredibly big and infinitely small numbers, unnecessarily complex words that describe scientific events and canâ€™t be represented with a 3D drawing are just some of the challenges we are set to face while learning a new piece of information.
What if there would be another way of learning and acquiring information?
Our first idea was to create a mixed reality installation where a complex topic such us the space and black holes was explained through a virtual reality helmet which was integrated into a character narrative. The user would also move through the installation in order to uncover hidden pieces of information, the space would help in this by providing a haptic sensation and feedback in relation to the video in the VR helmet.
Soon it became clear that an installation wasnâ€™t the right method to approach our questions. What we really needed was a Learning Framework.
We started looking at classic ways of learning such as classroom learning and what factors influence us. It became very clear that a more pleasant environment in which we feel at ease or a particular position (rather than the classic sitting) is affecting what we remember and how keen we are on learning. Different people also prefer different methods of learning, meaning text, image, video or sound based. Another crucial bit of our research was how exactly people build mnemonics and memory palaces as a way of storing and accessing information.
Our initial proposal was a modular futuristic structure with embedded technology that would allow the user to create a comfortable and cozy place similar to a â€œfortâ€ like shape. Once inside, the infrared cameras and projectors would detect the user and their gesture. Inside the â€œfortâ€ the user would be able to navigate a 3D visual environment, where they could explore and learn about any subject and topic. An AI driven machine would create a temporal and spatial map of the different topics and the depths of the research. The user would then create visual mnemonics to re-experience them in a second moment. This second part was aimed at increasing the sense of curiosity in the user and unconsciously invite them to learn more about the topics experienced outside the â€œfortâ€ or start learning about connected topics, entering an endless loop of learning and interconnected subjects.
Our final proposal encompassed all the research done through the previous iterations and a demo test of what we have done. More similar to a game than a physical structure for leaning, the user is free to wander around a small digital 3D world which encapsulates a theory relative to a subject. While walking around the user is prompted to engage, play and discover objects relevant to the narrative and the learning experience thanks to shaders which highlight and fade objects as the user is moving. In order to unlock Â certain stages and and help the user remember particular facts we have embedded movement into theory by either mimicking or interpreting the meaning of a fact. In this way different types of memories can be triggered simultaneously (procedural, semantic and declarative memory) and should help the user to learn in a more fun way and remember for a longer period of time. Another very important factor in this Â project is the possibility to change three basic â€œworld rulesâ€ such as scale, time and point of view. These changes allow the user to change scale, time and point of view relative to the world and objects they are discovering, all factors that will arise curiosity and help understand a theory better.
Reverse Labs is a company that me and Ahrian founded in order to make this “possible future” a reality.
We are currently working on realizing a full working demo of the project, especially focusing on game interactions in relation to embodied learning and haptic responses but also graphics and different methods of rappresentations and abstraction.