AI evidence extraction

Academic roles and competences in transition: digital transformation and university governance

Emanuela Proietti · Frontiers in Education · 2026

AI-generated evidence extraction, verified across multiple analytical personas. Not a substitute for the peer-reviewed original.

7/10

Relevance

3/4

Quality (LMQS)

Evidence

Citations

0.00

FWCI

This is an AI analysis. Read the peer-reviewed original at the publisher: https://doi.org/10.3389/feduc.2026.1841892

Methodology & findings

Study design

Sequential comparative mixed-methods design combining: (1) ECOLHE project (2020-2023): multiple case study across six universities in five European countries using document analysis, in-depth interviews, focus groups (18 focus groups with 121 total participants during acute pandemic phase), and online surveys; (2) Follow-up qualitative study: semi-structured interviews with purposively sampled Italian university faculty (7 completed interviews from Roma Tre University; target 60+ across multiple Italian universities by 2026).

Sample

N = 128, 13 groups

Primary method

Qualitative content analysis combining systematic coding procedures with interpretive approach. Mixed logic: deductive categories derived from theoretical framework and research hypotheses; inductive categories emerged from data through iterative reading of transcripts. Analysis focused on units of meaning—themes and statements—interpreted considering discursive context. Future analysis planned using IRaMuTeQ software for quantitative text analysis (frequency distributions, co-occurrence networks, lexical clustering) once sufficient corpus assembled.

Main result

The study found that "digitalization confirms itself as a social force that reconfigures professional identities, everyday practices, and organizational cultures," with "work intensification, cognitive overload, and the blurring of boundaries between work and non-work" now representing "stabilized conditions" rather than temporary emergency responses. A central finding is that "universities underwent rapid digital transition without a prior or accompanying process of digital transformation: without, that is, a strategic vision, a conscious organizational reconfiguration, or a shared cultural reorientation," and "transition arrived first, driven by emergency rather than by design."

Reports effect sizes.

Research paradigm

Interpretive/critical realist with qualitative empirical grounding

Author conclusions

The authors conclude: "Digital transformation cannot be reduced to a merely technological process. As the combined evidence from ECOLHE and the follow-up study suggests, it constitutes a cultural, organizational, and institutional shift that profoundly reshapes academic work, university governance, and the public mission of higher education." They further state: "To remain faithful to its public mission, the university must place knowledge, not technology, at the center of transformation—actively governing digitalization in ways that preserve the spaces of meaning, time, and relationship that are essential to the development of individuals, communities, and critical thought."

Risk of bias

Selection bias: Purposive sampling of faculty with specific disciplinary affiliations (sociology, pedagogy, psychology, philosophy) may overrepresent researchers with existing interest in organizational/educational transformation themes; Temporal bias: ECOLHE data collected during acute pandemic phase (March-June 2021) may not represent normal digitalization processes; emergency context acted as powerful accelerator; Methodological inconsistency: Two phases differ in instrument (focus groups vs. semi-structured interviews), scale (6 European universities vs. 1 Italian university in preliminary phase), and analytical basis, limiting direct comparability; Interviewer bias: Semi-structured interviews vulnerable to interviewer interpretation and follow-up question biasing; Participant reactivity: Faculty aware of research focus may provide socially desirable or theoretically aligned responses; Attrition/incomplete data: Follow-up study only 7 of target 60 interviews completed; preliminary analysis phase; Geographic/cultural context bias: Italian context-specific findings have limited transferability; pandemic response varied significantly across European systems; Disciplinary sampling: Initial 7 interviewees drawn from humanities and social sciences; not representative of STEM faculty or technical staff perspectives; Selection bias: Purposive sampling of faculty with explicit research sensitivity to themes of educational quality, governance, and professional identity may overrepresent reflective, critically-oriented scholars; Non-random sampling: Focus groups and interviews not randomly selected from entire academic population; Temporal confounding: Phase 1 (ECOLHE) conducted during acute pandemic phase vs. Phase 2 in post-pandemic context—confounds interpretation of change; Methodological heterogeneity: Different instruments (focus groups vs. semi-structured interviews), scales (six European universities vs. one Italian university), and analytical bases (local team reports vs. direct transcript analysis) limit internal comparability; Observer effects: Semi-structured interviews subject to social desirability bias and interviewer influence; Discipline bias: Preliminary interviews limited to faculty in sociology, pedagogy, psychology, philosophy—disciplines with particular sensitivity to organizational themes; Attrition: Follow-up study in preliminary phase with only 7/60 target interviews completed; Selection bias in purposive sampling of faculty in follow-up study; Self-selection bias in voluntary participation; Potential observer-expectancy effects in interviews; Limited generalizability due to intensive, context-specific Italian focus; Temporal confounding: ECOLHE conducted during acute pandemic phase while follow-up in post-pandemic normalization; Methodological differences between phases limit direct comparability; Preliminary nature of follow-up data (only 7 interviews completed); Selection bias: Purposive sampling of faculty may overrepresent those with research interests aligned with the study themes (sociology, pedagogy, psychology, philosophy); Attrition/Incomplete sampling: Follow-up study is in preliminary phase with only 7 completed interviews out of planned 60+; Contextual bias: Focus groups in ECOLHE conducted during acute pandemic phase (March-June 2021), which may not represent normal university conditions; Self-selection bias: Participants selected as 'privileged observers' may have heightened awareness of transformation issues; Researcher positionality not explicitly disclosed: Author/team perspective on digitalization and neoliberalism not stated; Limited institutional diversity in follow-up phase (Roma Tre University only in preliminary phase); Methodological inconsistency: Different instruments between ECOLHE (focus groups) and follow-up (semi-structured interviews) may introduce comparability issues; Selection bias in follow-up study: purposive sampling of faculty in 'sensitive' disciplines (sociology, pedagogy, psychology, philosophy) may not represent broader academic perspectives; Attrition/incompleteness: only seven interviews completed in preliminary Italian phase of planned 60+ national sample; Recall bias: interviews conducted retrospectively about pandemic experience and post-pandemic consolidation; Researcher positionality: ECOLHE involved action-research approach with organizational empowerment component, potentially influencing interpretation; Context specificity: Italian higher education system may have distinct institutional features limiting generalizability; Methodological heterogeneity: comparison between focus groups (ECOLHE) and semi-structured interviews (follow-up) rests on 'theoretical consistency' rather than methodological equivalence

Limitations

The authors state: "The main limitations of the study concern: the methodological differences between the two phases, as described above
the exploratory and preliminary stage of the follow-up research
the partial coverage of the academic community in the current phase, as not all staff groups (e.g., technical and administrative personnel) have yet been included
the intensive and context-specific nature of the Italian inquiry, which limits the direct transferability of findings to other national systems
and the inherent complexity of digital transformation processes, which may generate context-dependent variations that are difficult capture fully."

Open questions raised

Most existing studies focus either on technological dimension of digitalization or effects during pandemic emergency phase, with limited attention to longer-term institutionalization
Comparative longitudinal perspectives tracking continuities and discontinuities across different phases of digitalization remain infrequent, particularly within Italian context
Limited integration of literature on digital transformation, sociological approaches to technology, and academic professionalism under neoliberal governance
Need for explicit institutional frameworks and ethical guidelines for AI use in academic work
Insufficient study of how digital transformation affects educational quality, inclusion, and public mission of universities
Future research requires expansion to 60 interviews across multiple Italian universities with broader disciplinary and institutional coverage

Data: No datasets available; only aggregate/anonymized qualitative data referenced. Full interview guide provided in Supplementary Material/Appendix A (referenced but not provided in excerpt); No datasets are stated as publicly available. ECOLHE project data referenced but availability not indicated.Code: None mentioned; future quantitative text analysis planned using IRaMuTeQ software but no repository mentioned; None mentioned.Extracted from: pdfAgreement 50%

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Institutional Policy AI Governance Mixed Methods