Artificial Intelligence Use and Perceptions in Communication Programmes in Ecuador: Student and Academic Leadership Perspectives

Abstract

Background: The integration of artificial intelligence (AI) within higher education ecosystems is moving at a faster pace than operational or pedagogical understanding. In emerging fields such as communication studies, where digital media frameworks are continually developing, complex technological shifts and evolving professional competencies persist, heavily shaping institutional priorities and profoundly influencing the strategic deployment of academic resources.

Objective: This study examines the specific areas of application and qualitative perceptions of artificial intelligence in communication education by contrasting student experiences with academic leadership perspectives across undergraduate communication degree programmes in Ecuador.

Methodology: The empirical analysis utilises a non-experimental, mixed-methods explanatory design with descriptive and correlational scope to capture fundamental operational realities. Quantitative data were operationalised through a structured digital survey administered to a purposively sampled group of communication students, with statistical validity assessed using Pearson's chi-square and Spearman's rho. Concurrently, qualitative insights were gathered through semi-structured interviews with academic programme leaders, with data management and theme extraction systematically executed using ATLAS.ti software to ensure analytical rigour.

Results: The findings indicate that while most students demonstrate a basic foundational knowledge of AI tools within strategic communication contexts, advanced technical proficiency remains exceptionally scarce. Furthermore, the distribution of this technological knowledge exhibits significant structural variations when analysed by sex across distinct application categories. From an administrative perspective, academic leaders describe routine AI utilisation across institutional planning, programmatic management, and educational support systems, whilst heavily highlighting the critical absence of formal ethical frameworks. Triangulation of the datasets reveals a pronounced implementation gap between macro-level institutional adoption narratives and effective, day-to-day student uptake.

Conclusion: The study concludes that internal managerial frameworks and student-level digital competencies work jointly in driving successful technology adoption. Structural focus on institutional policy yields suboptimal educational outcomes when communication programmes face an active knowledge transfer divide and pedagogical mediation breakpoints.

Unique Contribution: This research advances digital literacy and educational management literature by providing an integrated empirical framework that explicitly maps the divide between managerial intent and student reality within an emerging economy context, offering critical analytical insights into how gender-based variations and structural transfer gaps disrupt uniform AI adoption within contemporary communication curricula.

Key Recommendation: It is recommended that university regulation boards, curriculum designers, and higher education authorities in Latin America design comprehensive academic reforms that incorporate mandatory AI literacy modules and standardised digital competence training. Additionally, policymakers should implement context-sensitive academic change management strategies and establish clear, institutional ethical guidelines to safeguard data transparency, close the access divide, and enhance the long-term viability of AI-augmented media education.