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
type: CreativeWork
description: 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 t…
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 t…
author: Kavian, Rokhsareh
keywords: H Gwyddorau Cymdeithasol (Cyffredinol), L Addysg (Cyffredinol), T Technoleg (Cyffredinol)
date published: 2025-04
date modified: 2026-07-24T05:53:05Z
provider: University of Wales Trinity Saint David
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of Wales Trinity Saint David

PropertyValue
property ID: DOI
value: 10.82227/repository.uwtsd.ac.uk.00003707