Mindset theory tells us what motivates and demotivates learners. When you teach using mindset theory, you see a sparkle in students’ eyes and hear excited comments as they become more engaged in learning activities.
In 2016 Dr Vernitski and Dr Saker taught two modules in the Department of Mathematical Sciences using the mathematical mindsets approach (mathematical mindsets is mindset theory applied to learning mathematics). Should you, too, use activities based on mindset theory in your teaching?
The aim of this project is to generate direct evidence of improved motivation when using learning activities informed by mindset theory. To our knowledge, the neural mechanisms associated with such activities have not previously been investigated. Combining Dr Vernitski’s expertise in applying mindset theory and Dr Daly’s expertise in neurophysiology, we shall conduct a series of experiments to establish how neural processes related to motivation and learning differ between traditional mathematical problem solving and the mathematical mindsets approach. We hypothesize that, first, participants will report greater motivation during the mathematical mindsets problems and, second, they will exhibit greater levels of EEG indices of motivation (e.g. pre-frontal asymmetry, theta band-power in the prefrontal cortex, and gamma power in the central cortex) while solving these problems.
The BCMI-MIdAS (Brain-Computer Music Interface for Monitoring and Inducing Affective States) is a collaborative project between the Universities of Plymouth and Reading. The work is funded by two 54-month EPSRC grants, with additional support from the host institutions. The project aims to use coupled EEG-fMRI to inform a Brain-Computer Interface for music.
ABC aims at increasing human capabilities by means of Brain/Neural Computer Interfaces (BNCI). The project will develop applications addressed primarily to persons with Dyskinetic Cerebral Palsy (DCP). Due to DCP particular conditions, BNCI-based systems present a huge potential for the improvement of the quality life and the promotion the independent living of this target group. In particular, project outcomes will specifically focus the augmentation of capabilities related to communication, learning, social participation and control of devices. ABC system will be composed by four independent modules based on the latest advancements in BNCI signal processing, Affective Computing, Augmented Communication and Biosignal Monitoring. The reference European Research Institutions in each field will lead the R&D work.
TOBI is a large European integrated project which will develop practical technology for brain-computer interaction (BCI) that will improve the quality of life of disabled people and the effectiveness of rehabilitation.
TOBI will design non-invasive BCI prototypes that will be combined with existing assistive technologies and rehabilitation protocols. In such a hybrid approach users can couple brain interaction with muscle-based interaction or can naturally switch between the different ways of interacting.
Severe cognitive or physical disabilities from any origin have a dramatic effect on autonomy, intimacy or dignity, and, by extension, on quality of life. A person with a severe brain injury resulting from a car collision or those suffered a brain stroke are examples of disabilities of neurologic nature. For years, the severely disabled have learned to cope with their restricted autonomy, restricting their daily activities like moving around or turning on the lights and limiting their social interaction.
The BrainAble project is about empowering them to mitigate this barriers of the everyday life to which those individualsare confronted. BrainAble has researched, designed and validated an ICT-based HCI (Human Computer Interface) based on BNCI (Brain Neural Computer Interface) sensors combined with affective computing to control smarthome services and virtual environments.