Technology-Enabled Hybrid Threats and Institutional Resilience in Kosovo: A Qualitative Study of Security Professionals

Refik Ramadani, Buen Bajrami — Sun, 01 Nov 2026 00:00:00 +0100

Hybrid threats exploit technological, informational, political, and organizational instruments to capitalize on existing vulnerabilities while complicating detection, attribution, and response. The current study investigates how professionals working in security-related fields in Kosovo perceive the role of digital technologies in facilitating hybrid threats, the institutional vulnerabilities that increase exposure to such threats, their implications for political stability and public trust, and the measures required to strengthen institutional resilience. An exploratory qualitative research approach was adopted with the involvement of nine purposively chosen professionals working in the fields of cybercrime investigation, prosecution, journalism, security, and other institutional sectors. Data were collected in March 2026 using an asynchronous online qualitative questionnaire with five open-ended questions. The analysis identified five thematic strands, including hybrid warfare as an evolving security challenge, technology as an enabling mechanism, institutional and informational vulnerabilities, political stability and public trust, and multidimensional priorities for strengthening institutional resilience. The framework provides a formalization of a socio-technical analytical approach where technological enablers increase the operational potential of hybrid threats, institutional and communication vulnerabilities determine the risk of being exposed to such threats, and the effects of those go beyond the technical aspect and include the issue of credibility of information and political stability. The notion of resilience, thus, requires comprehensive technological, organizational, informational, legal, educational, and cooperative efforts.

Artificial Intelligence Integration in STEM Education: An Evidence-Constrained Systems Readiness Assessment

Wed, 04 Nov 2026 00:00:00 +0100

Artificial intelligence (AI) is entering university STEM education at a pace that may exceed the capacity of curricula, professional development, infrastructure, and governance to adapt. This study develops an evidence-constrained systems-readiness framework based on two parallel surveys conducted in Albania in January 2026, comprising 664 student responses (approximately 282 substantially complete entries) and 92 academic staff responses from public and private higher education institutions. As respondent-level data were unavailable for this secondary analysis, the investigation relied on statistics that could be defensibly reconstructed from aggregate reports, including chi-square tests, Holm-adjusted one-sample tests, Welch comparisons, effect sizes, Wilson confidence intervals, denominator and covariance sensitivity analyses, and report-level qualitative triangulation. The framework integrates reported curriculum maturity, responsible AI practices, academic capacity, infrastructure, governance, student preparedness, and perceived employability alignment, while distinguishing perceptions from demonstrated competence and independently verified institutional performance. Student and staff distributions across the four levels of AI integration showed no statistically detectable difference (χ²(3) = 1.28, p = 0.734, Cramér's V = 0.069), with reported curriculum maturity scores of 34.1/100 and 30.0/100, respectively. Students reported a substantial gap between the availability of project-based learning opportunities and the perceived effectiveness of practical learning (Hedges' g ≈ 0.80). Academic staff rated existing infrastructure below the scale midpoint but projected institutional readiness over the following three years above the midpoint. The perceived demand–preparedness gap remained positive under assumed within-respondent correlations ranging from 0 to 0.6. The study contributes an implementation-agnostic and reproducible systems-readiness framework that identifies asynchronous institutional constraints, preserves uncertainty arising from aggregate data, and translates perception-based findings into testable pathways for AI integration in university STEM education.

International Journal of Innovative Technology and Interdisciplinary Sciences

Technology-Enabled Hybrid Threats and Institutional Resilience in Kosovo: A Qualitative Study of Security Professionals

Artificial Intelligence Integration in STEM Education: An Evidence-Constrained Systems Readiness Assessment