Kavian, Rokhsareh (2025) To explore strategies of personalised AI based e-learning to add value through training and development for healthcare staff: a case study of a care home in the UK. Doctoral thesis, University of Wales Trinity Saint David.
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Abstract
Personalised e-learning empowered by Artificial Intelligence (AI) holds promise for tailoring e-learning experiences to the specific needs and preferences of healthcare professionals to enhance the efficacy of e-learning and thereby delivery of care within healthcare and social care organisations. However, the full potential of personalised AI based e-learning remains largely untapped in healthcare organisations in the UK, as issues and challenges caused barriers to the adoption of this advanced technology. The critical aspect often overlooked is the understanding of staff perceptions, expectations, and needs regarding the adoption of personalised AI-based e-learning. Also, as people live longer to the older age in the UK and the need for more complex treatment is also increasing, healthcare staff need to be updated and well-trained to the latest knowledges and technologies in order to respond vigilantly to the patients’ needs. Therefore, it is important to understand healthcare staff perceptions, expectations and challenges to adopt an effective e-learning system that is personalised to their learning styles. The aim of this research is: • to explore strategies of personalised Artificial Intelligence based e-learning to add value through training and development for healthcare staff in the UK. Employing qualitative research methods, data was collected through interviews with healthcare professionals from a selected care home in the UK using purposive sampling techniques. A case study research approach was adopted to provide insightful responses to the research question and achieve the study's objectives. Thematic analysis was conducted on the collected data to explore the challenges faced by healthcare staff in the selected care home and to propose potential solutions for the adoption of personalised AI-based e-learning. Therefore, by applying thematic analysis, the analysed data is matched against proposed framework that identifies the barriers and incentives to the adoption of personalised AI based e-learning. The barriers and incentives are categorised into 'Technology,' 'Organization,' and 'Environment' contexts which they are aligned with the proposed conceptual framework of this doctoral study. This research contributes to the body of knowledge of personalised AI-based e-learning and its integration into healthcare environments by reviewing a comprehensive literature review focused on identifying the obstacles of adopting personalised AI based e-learning. Also, this study developed two frameworks based on incentives and barriers of adopting personalised AI based e-leaning; identified from interviewing healthcare staff of the selected care home in the UK. In addition, an innovative conceptual framework is introduced to assist healthcare organisations and ICT specialists in comprehending the underlying challenges associated with the adoption of personalised AI-based e-learning. Additionally, a roadmap is formulated to guide healthcare organisations in adopting personalised AI-based e-learning, bridging the gap between theoretical insights and practical application. Keywords: Artificial Intelligence, E-learning, Personalisation, Healthcare organisations in the UK
| Item Type: | Thesis (Doctoral) |
|---|---|
| Uncontrolled Keywords: | Artificial Intelligence, E-learning, Personalisation, Healthcare organisations in the UK |
| Subjects: | H Social Sciences > H Social Sciences (General) L Education > L Education (General) T Technology > T Technology (General) |
| Divisions: | Theses and Dissertations > Doctoral Theses |
| Depositing User: | Rokhsareh Kavian |
| Date Deposited: | 09 May 2025 10:12 |
| Last Modified: | 09 May 2025 10:12 |
| URI: | https://repository.uwtsd.ac.uk/id/eprint/3707 |
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