Seven student participants (n = 7, 2 men and 5 women) and six faculty members (n = 6, 4 men and 2 women) comprised the final sample. Student participants to this study were all early to mid-career radiographers from varied areas of practice: clinicians, academics, researchers, managers and representatives of professional societies/associations from the UK, Denmark, Italy, Switzerland and United Arab Emirates. All participating faculty members were UK-based, experienced clinicians, academics and/or researchers from a multidisciplinary background: radiography, radiology, computer science, and psychology.

Four themes were constructed from the interview and FGD data to provide a descriptive narrative of the participants’ experiences of the AI module, either as students or faculty members. Integrated codes from the interviews and FGD are presented in Table 3 [49]. Verbatim quotations are labelled IP to refer to student Interview Participants or FGDP to refer to faculty Participants that were part of the FGD, with a number added at the end, to differentiate participants’ contributions from each other.

Table 3 Codes, code frequency and convergence of codes to construct the themesTheme 1: Participants’ professional and educational background influenced their experience

Faculty participants approached their preparations for the lectures assuming students had no foundational knowledge of AI to provide more general insights about the fundamentals of AI and its clinical applications.

“…assume no knowledge and you’d have to start building up for them” – FGDP5

“…kept things quite general where we could raise those discussions…that were transferable between different technologies…modalities” – FGDP4

Considering this approach adopted by the faculty members, the student participants indicated that overall, the module met their expectations of an introductory module.

“…personally, [it] was an introduction. I knew very little…it met perfectly to the needs of what I needed” – IP2

“…it’s an introduction so maybe we should not know everything” – IP1

Student participants explained that their different needs could be ascribed to the different roles that they fulfil and their interests, that motivated their enrolment to this module.

“…wanted a bit more about certain modalities as the focus was more of ultrasound, MRI than it was in plain DR and CT examinations in my opinion, but I think…depending on which research you are leading and…role you are having” [sic.] – IP4

The above provided significant context to understand the variations of participants’ appraisals of the AI module and recommendations for future offerings.

Theme 2: A meaningful learning experience

Participants considered their participation in the module as a meaningful learning experience as they reflected on the module delivery, organisation, content and pedagogical approaches used to mediate teaching and learning.

“…I found it…really helped me to develop my own learning” – IP2

The module delivery was regarded an enabler of learning due to flexibility, which allowed digital, synchronous and asynchronous engagement during and outside of working hours. Participants felt that this fitted well with their working schedules, since it allowed students to catch up asynchronously if they missed sessions. Participants also regarded the online delivery more cost-effective in terms of traveling and accommodation associated with campus-based delivery.

“I like to receive the lessons, the lectures and to hear it before the session, it was very nice” – IP1

“…online is great for me, there’s no additional cost to go with it…” – IP2

“…the lessons were very well scheduled, well it was at night…so most people could attend” – IP3

“…I think it was really great that you were actually able to take it in the evenings…and your busy schedule on a daily space is not blocking the opportunity to participate [sic.] – IP4

Participants felt the module was organised well in a logical and user-friendly manner on the learning management system; this and the use of a scaffolded approach in the module, from fundamentals to more advanced clinical applications, facilitated their learning. They felt there was broad coverage of the field of AI at an introductory level. The use of different experts in the related fields associated with AI in the context of radiography and different instructional methods enhanced the learning experience further. Clarification of expectations at the start of the module further contributed to a meaningful learning experience as it set the scene for the way forward for participants, who knew what to expect. This was complemented with adequate, appropriate and timely guidance from the module lead.

“…it gave us a good insight of AI from every perspective…so it was very broad [the module lead] was very clear about everything that [they] were going to do and the way things were delivered…” – IP3

“…it was very well organised. Given that it was for the first time…it was split into a few parts and the splitting was also very good [the module lead] guide me the right way [sic.]” – IP5

“…every session…or every pedagogical approach had its own…positive impact in terms of having the different information learned in a different way…” – IP7

Participants reported that the resources that were provided and the approaches used to deliver the content (discussion boards and flipped classroom, encouraging active student engagement) contributed to a positive learning experience. The assignments were perceived as extensions of student participants’ learning and gave them an opportunity for self-assessment of their comprehension of AI relative to medical imaging practice.

“…you could do pre-reading and have your questions formulated in your mind before you went to the section…interaction with the rest of the group and also the presenters at that time…live…the chat box” – IP2

“…the way in which it was assessed, the presentation and the essay it really makes you think deeply…it really makes you dig deep into that matter [chosen topic], so it was really good” – IP3

“…the level of information was really high. It gave me new insight …about how AI is used at the moment” – IP4

“…I will think is just about right, the materials they’ve put in” [sic.] – IP6

Given the positive experiences that student participants acknowledged, they strongly agreed that they would recommend the module to colleagues. They felt it empowered one with knowledge to comprehend how AI technologies operate and it also informed respective research endeavours.

“…it’s opened a lot of research in this field also” – IP1

“…this course, if anything, you know what, if you asked me things about artificial intelligence now, I do have a good base…” – IP7

Theme 3: Barriers to learning and threats to module status

Student participants indicated that some aspects related to the module design and pedagogy, and marketing were considered to be barriers to learning and a potential threat to the module’s status. The module was offered during a time of the year that some participants felt was rather busy, although they were mindful that this may be perceived differently depending on the different roles of those enrolled. This made it difficult for some of them to fully immerse themselves with the module requirements to get the most out of it.

“…we have a lot of things…at the end of the year you know…it’s crazy” – IP1

Participants indicated a need for greater alignment in scheduling between preparations for lessons, the content of the lesson and its ultimate congruence with the expectations of the end-of-module assignments. Module length was also perceived as an exacerbating factor as some participants felt that the duration of the module, given the richness of the content, could be extended to allow them time to be prepared for the assignments, especially because this was a novel area for the participants.

“…given the nature of the information, I mean the novelty…it’s a total new concept…I needed more time” – IP7

Participants felt the digital learning and teaching space itself was a barrier, since physical contact and networking are preferred and a necessary part of their development. However, they did acknowledge this was due to the required coronavirus pandemic related restrictions at the time of delivery and that opportunities to enhance engagement among students and between students and faculty members were offered, but the physical contact would allow for more immediate interactions compared to the digital space.

“…could have been nice to meet up physically to get more network in the group…it just giving a different atmosphere when you’re looking people in the eyes” – IP4

“…you may not be able to understand because of technology…when some lecturers are delivering it, it is difficult even if you don’t understand something…in the classroom, you can easily call back, but…not possible during online” – IP6

Participants highlighted the cost of the module may be unaffordable by potential students. One student felt that better advertising of the full curriculum in detail would be an advantage for future student recruitment, as it would justify the value for money and the uniqueness of this course.

“The only issues for us is that it’s kind of pricey” – IP4

“…this certificate fails to describe the real depth of the course…people are not ready to pay this much money for an introduction…” – IP7

Theme 4: The ideal introductory AI module

Participants reflected on characteristics of an ideal introductory AI module and made recommendations for future occurrences. The first recommendation was that the module should be flexible for a varied audience, whilst being cognisant of the context in which the module is being delivered.

“…always those contextual factors that might influence what we really want…so that you can tailor it to that target audience” – IP5

Participants also suggested that an introductory module in AI should largely focus on the fundamentals of AI to explain how it works, the concept of explainability, and examples of clinical applications. Participants felt that knowledge of AI fundamentals and of some key clinical applications would enable them to more confidently use AI in clinical practice. It was also suggested by the participants that teaching students how to engage and appraise AI literature is critical to foster their understanding of the literature and assist them to critique AI applications in practice or during procurement thereof.

“…make sure that people are knowledgeable and know how AI works” – IP2

“…something about an intro to the algorithms…a session dedicated to explainability and uncertainty” – FGDP3

“…the critical appraisal of the AI literature, because this is fast moving, it’s clickbait headlines…so I think that element could be brought in a little bit because radiographers, although may not be the core decision makers about purchasing, they will be using it and they will need to be able to critique industry proposals…” – FGDP2

Participants also felt having compulsory and elective sessions incorporated in an introductory module would be beneficial for them, so that they can customise their learning in line with their needs and preferences based on their knowledge gaps and areas of interest. They recommended the materials should be available for some time after the completion of the module, so that they can be accessible when needed.

“…it’s too short to take everything, to look at everything so if we can have a longer access, it can be nice yeah” [sic.] – IP1

“…maybe for some weeks, we’ll be doing holistically the AI application of general radiology. And tailor some lectures as it relates to the individual areas depending on your modality…” – IP6

Participants suggested that learning activities and content must be purposefully selected so as to eliminate unnecessary repetition while balancing reinforcement of learning.

“Probably one thing that I didn’t enjoy much, I think one of the speciality…was a bit repetitive…” – IP3

“…make sure that there was enough overlap to reinforce learning but not…duplication” – FGDP2

The introduction of AI in undergraduate medical radiation sciences curricula was also highlighted, so that students are being prepared from an earlier stage for their future career. While acknowledging the interprofessional faculty, participants agreed that the ideal course should have a strong interprofessional education (IPE) approach, since AI occurs within an ecosystem with other healthcare professionals.

“AI is progressing … and my students need to be informed…looking into adding in our curriculum components that touch base on artificial intelligence” – FGDP7

“…we’re making a demarcation between radiology and radiographers, other aspects of imaging, whereas actually the truth is, very little about any of these tools is specific to any of our roles” – FGDP1

Participants indicated that a student-led, synchronous discussion forum using videoconferencing could extend their learning through peer-to-peer informal teaching to foster a sense of community and allow for further networking, beyond the one already established within the course.

“…let’s say, right, once every week…if anybody wants to drop in and have a discussion about what they’ve been reading about and chat to one another…” – IP2