How and when does artificial intelligence use enhance student creativity? The mediating role of knowledge-based dynamic capabilities.

The demand for housing adaptation for older adults and disabled individuals is growing due to population ageing and the increasing prevalence of disabilities with age []. Massive delays in housing adaptations for the elderly and disabled people are putting them at risk of being forced into residential care when most of them would like to live independently at home. About 16 million people, 24% of UK population have a disability in 2021/22, over 1.6 million people had complex disabilities, and 57% more adults were expected to require care in 2038 compared to 2018 []. The increasing demand leads to long waiting time that can be over 573 days/19 months [] when statutorily, assessment and approval should not take more than 6 months []. The leading causes of delay can be broadly categorised under the decision-making process in assessment, assistive technology, and design customisation for people with complex disabilities. The Royal College of Occupational Therapists (RCOT) acknowledged these problems in its reports, guiding principles for the assessment and provision of equipment [], and adaptations without delay []. Waiting for a social care assessment is cited by RCOT [] as a key factor contributing to delays in the delivery of adaptations. This is because the need for an adaptation has been defined by the solution’s type or cost rather than the situation’s complexity. This prevents occupational therapists from concentrating their specialist skills on working with individuals whose circumstances are most complex and where they would have the greatest impact on the individual’s health and wellbeing. This indicates a need to enhance the complex housing adaptation process to reduce pressure on the OT, peoples in care homes and the National Health Service (NHS) in the UK There is recognition that the sooner housing adaptations are made, the greater the preventative benefits [], e.g. reducing the risk of falls and associated costs. Hip fractures have adverse effects on daily living activities, account for around £2 billion of fragility fractures costs and increase one-year mortality between 18 and 33% in the UK []. This study presents a feasibility assessment conducted prior to development of an AI-Driven Decision Support System for Personalised Housing Adaptations and Assistive Technology (HomeAI-Enable). HomeAI-Enable system is developed to improve how housing adaptations and assistive technologies are recommended for older adults and people with disabilities. This feasibility study explored a range of smart and practical methods that use Artificial Intelligence (AI), Machine Learning (ML), Natural language Processing (NLP), Fuzzy and interactive tools to speed up the process of decision making by recommending suitable housing adaptation and assistive technologies for different types of diseases and symptoms. Each method looked at the problem from a different angle, and together they offer a clear path for building a system that is helpful, efficient, and easy to use. The HomeAI-Enable system is designed to match diseases and symptoms with corresponding housing adaptation and assistive technology needs. It comprises one integrated expert-AI decision support system/platform with three modules: