Have you ever been involved in the training of any Digital Research Competency? If so, I am interested in knowing about your experience: what did you teach? To whom? How did you do it? What role did you play? Beyond sheer, genuine curiosity, there’s a reason why I want to know about this and why I think others would benefit from this knowledge.

During the last decade, research has undergone a profound computational turn, as demonstrated by the proliferation of data-driven research (Crouch et al., 2013), the growing adoption of computational techniques across traditionally non-computational fields, such as social sciences and humanities, the increasing demand for Open Science and FAIR principles, and a new set of diverse academic outputs including software and datasets. The advent of AI has just accelerated this trend, while adding a new dimension of complexity.

As a result, navigating this evolving landscape requires mastering a wide range of skills and competencies — Digital Research Competencies (DRCs) as defined by the DIRECT Framework — that need to be learnt and taught. Given their extensive specialised and technical backgrounds, Digital Research Technical Professionals (dRTPs) [1] are well positioned to lead the delivery of that specialised training. At least in theory.

But what’s the reality of this training? How are dRTPs engaging with it? Are they leading or taking supportive roles? What added value do dRTPs bring to this essential component of research in comparison to other professionals or teaching platforms? These are some leading questions of “Mapping and evaluating dRTP’s contributions to computing skills pedagogies in HE”, the DisCouRSE Network+ funded project I’m leading with Timothy Monteath.

To answer them, we prepared a survey aimed at professionals involved in teaching DRC that asks two sets of questions: the first one about the respondent (role, career stage, etc.) and the second one about any training respondents have been involved with (context, role and capacity, contents, technologies involved and use of AI).

Preliminary results depict a landscape where most of the training is informal (i.e., it is not part of any degree or does not lead to an accreditation or certification), teaches a technology, software or programming language, and is aimed at PhD Students or Research Staff. This training is led by dRTPs (except when part of the curriculum, in which case dRTPs assume a support role) and provides Software Engineering and development skills, followed by Information and data technologies and professional skills (see figure below).