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Open Access 01-12-2023 | Artificial Intelligence | Original Article

Artificial intelligence education for radiographers, an evaluation of a UK postgraduate educational intervention using participatory action research: a pilot study

Authors: Riaan van de Venter, Emily Skelton, Jacqueline Matthew, Nick Woznitza, Giacomo Tarroni, Shashivadan P. Hirani, Amrita Kumar, Rizwan Malik, Christina Malamateniou

Published in: Insights into Imaging | Issue 1/2023

Abstract

Background

Artificial intelligence (AI)-enabled applications are increasingly being used in providing healthcare services, such as medical imaging support. Sufficient and appropriate education for medical imaging professionals is required for successful AI adoption. Although, currently, there are AI training programmes for radiologists, formal AI education for radiographers is lacking. Therefore, this study aimed to evaluate and discuss a postgraduate-level module on AI developed in the UK for radiographers.

Methodology

A participatory action research methodology was applied, with participants recruited from the first cohort of students enrolled in this module and faculty members. Data were collected using online, semi-structured, individual interviews and focus group discussions. Textual data were processed using data-driven thematic analysis.

Results

Seven students and six faculty members participated in this evaluation. Results can be summarised in the following four themes: a. participants’ professional and educational backgrounds influenced their experiences, b. participants found the learning experience meaningful concerning module design, organisation, and pedagogical approaches, c. some module design and delivery aspects were identified as barriers to learning, and d. participants suggested how the ideal AI course could look like based on their experiences.

Conclusions

The findings of our work show that an AI module can assist educators/academics in developing similar AI education provisions for radiographers and other medical imaging and radiation sciences professionals. A blended learning delivery format, combined with customisable and contextualised content, using an interprofessional faculty approach is recommended for future similar courses.

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Title: Artificial intelligence education for radiographers, an evaluation of a UK postgraduate educational intervention using participatory action research: a pilot study
Authors: Riaan van de Venter
Emily Skelton
Jacqueline Matthew
Nick Woznitza
Giacomo Tarroni
Shashivadan P. Hirani
Amrita Kumar
Rizwan Malik
Christina Malamateniou
Publication date: 01-12-2023
Publisher: Springer Vienna
Keyword: Artificial Intelligence
Published in: Insights into Imaging / Issue 1/2023
Electronic ISSN: 1869-4101
DOI: https://doi.org/10.1186/s13244-023-01372-2

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Artificial intelligence education for radiographers, an evaluation of a UK postgraduate educational intervention using participatory action research: a pilot study

Abstract

Background

Methodology

Results

Conclusions

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Background

Methodology

Results

Conclusions

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