In this set of articles, we will elaborate (and give concrete examples) on the questions of the R&D Advance Assurance.

One of the questions you will be asked to answer is: 'What are the scientific or technological uncertainties involved in the project?'

Note that a scientific or technical uncertainty exists when a competent professional or expert in the industry is not sure if the product or process you’re trying to build through the R&D is possible to achieve or not, or else, is not sure as to how to achieve it in practice. There should be no off the shelf solution for what you’re trying to build.

You will need to provide evidence showing the project's aim to address a scientific or technological uncertainty. This includes:

• where it is uncertain whether something is scientifically possible or technologically

feasible

• situations where a competent professional working in the field is uncertain, on the basis of current knowledge, how to achieve in practice the scientific or technological advance that is being sought

• situations where something has been established as scientifically possible, but there is an uncertainty about how to turn that theoretical knowledge into a cost-effective, reliable and reproducible process, product or service.

Example of an answer to the question: 'What are the scientific or technological uncertainties involved in the project?'

In order to implement the real-time learning analytics platform, B Games will need a

service which gathers data to demonstrate how effectively a player is learning. The

research, conducted by B Games’ team, concluded that in the existing analytical products and services available, there is no service focussed on helping users achieve learning outcomes, instead, they are mostly concerned with product performance. The team will therefore spend a great amount of time in researching, developing, and implementing this platform.

One of the technical difficulties we expect to encounter in the implementation of the

learning analytics platform is designing an algorithm which could draw insights about the progress of the player based only on the way they play the game. This functionality is technically challenging as it requires constant monitoring of the actions of the user and picking a set of actions which are significant in the context of learning.

Another technical challenge we expect to face will be when the user-base of the

application will grow and the database requests from the users will become too much for the existing configuration. In this situation, the number of users and the huge amount of request they make while playing the game, will lead to latency in visualisation. Aiming to provide immediate real-time results to its users, the team will focus on solving this problem.

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