A new questionnaire helps higher education institutions find out where staff need training in data and AI.
Carita Kujala’s recently published master’s thesis has produced a practical tool for identifying staff competence development needs in data literacy, data management and artificial intelligence (AI). The work was carried out within the UNINOVIS Data for L.I.F.E. alliance project and supports the alliance’s efforts to advance the digital transition in higher education. TAMK has been part of UNINOVIS since the beginning of 2025.
Why the instrument was needed
Data and AI are becoming increasingly important in teaching, research and administration. As their role grows, higher education institutions need effective ways to understand how confident staff are in these areas and where training would make the biggest difference.
The need for such a tool came directly from within the UNINOVIS alliance. At the start of the project, no existing instrument comprehensively covered data literacy, data management and AI competences in an international higher education context. Without a shared way of measuring these competences, it is difficult for partner institutions to plan training that fits their staff’s actual needs.
How it was developed
The thesis, “Development of a Questionnaire Instrument for Identifying Data and AI Competence Development Needs among Higher Education Staff”, was written by Kujala in the Master’s Degree Programme in Information and Knowledge Management at Tampere University. The study set out to answer how a questionnaire can be developed to support the identification of competence development needs related to data and AI among higher education staff.
Kujala used a design science research approach, which focuses on building and testing a practical solution to a real-world problem. The resulting questionnaire allows institutions to assess staff members’ perceived competence levels and to identify the areas where further training is needed. The instrument was refined through multiple review rounds, expert testing and international pilot phases involving partners from seven UNINOVIS countries, so it reflects perspectives from across the alliance rather than a single institution.
Supporting staff development across the alliance
The thesis was facilitated by TAMK’s Principal Lecturer, D.Sc. (Tech.) Toni Luomaranta, who is involved in the UNINOVIS work on promoting the green and digital transition and strengthening staff capabilities in these areas. The questionnaire developed through the thesis will support future competence development activities and training planning within UNINOVIS partner institutions.
By providing a structured way to identify development needs related to data and AI, the thesis contributes to the alliance’s mission of strengthening data-related capabilities and supporting lifelong learning in European higher education.
Kujala’s thesis is available in Tampere University’s Open Institutional Repository Trepo.