The key aim of the Personalised Preference Profile (3Ps) project is to better detect the interests/preferences of learners with Severe Learning Difficulties (SLD) and Profound and Multiple Learning Disabilities (PMLD) and provide the ability to create personalised content that is automatically and dynamically tailored to them. It can be a hugely complex task to find out what stimulates children with SLD/PMLD. This project uses a novel technical approach to detect the child’s interaction with content and couples this with real time & off-line data analytics to tailor the experience to their interests. This provides a unique market opportunity and innovation based upon: 1) Creating an authoring tool that can be used by teachers to create educational self-tailoring content for learners with PMLD from fixed and authored content. Specific visual and sensory content packs will be created and the tool will be available on any online computer/tablet device. 2) Creating an application that presents the content generated and analyses feedback from the individual user’s interaction with it (via eye tracking – a technology already used in ITL’s product offering) to detect what is of interest. This will drive the real time content tailoring for individual users and the longer term tailoring in the authoring tool. 3) Research into how virtual reality technologies (e.g. headsets, sensory room software) might in the future be able to be integrated with this application and learning process. If the application can be successfully developed then its impact to learners and teachers will be: 1) The ability to build up learning interests and preferences/personalised profiles for individual learners and produce student friendly reports that can form the foundation of a communication passport. 2) Information that allows teachers, guardians and designers to create focused learning content that provides more engagement resulting in the learning experience being enhanced

The key aim of the LAPS (Learning Analytics for the PMLD Sector) Project is to demonstrate that it is possible to significantly improve the learning effectiveness of content that is delivered to learners with Profound and Multiple Learning Disabilities (PMLD). The use of learning analytics to improve the learner experience in standard education has increasing importance. There is no equivalent approach for people who suffer PMLD. Novel electronic delivery coupled with activity-derived analytics for each individual learner provides a first-to market opportunity. The innovation in the LAPS Project is based upon the creation of the new: a) Set of data analytics that will be used to interpret the raw information obtained from the learning activities. Standard analytics techniques will be used but the interpretation will be based upon detailed knowledge of low incidence accessibility learning activities and achievements; b) Intelligently sequenced learning for low incidence accessibility-oriented content, based upon insights that have been gained from the learning analytics obtained from the use of prior learning activities. There is no agreed content pedagogy to meet the needs of those suffering PMLD and there is no way to measure the learning effectiveness of that content. If learning analytics can be acquired, suitable recommendations for the design and use of such content can be established. The significant societal impacts that will accrue to users from this new approach are: a) Personalised Learning Activities where content is tailored to the specific learning objectives and needs of the individual learner. This will enable the learner to receive the best learning experience available at the point and time of delivery. b) Personalised Learning Reports that allow teachers, guardians and content designers to create and support more focused and timely learning activities that can be tuned at the point of delivery to match the needs of each individual learner.