Augmented reality (AR) is revolutionising education by integrating virtual elements into physical environments, enhancing interactivity and participation in learning processes. This study analyses the impact of AR in higher education, examining its influence on ease of adoption, student interaction, academic motivation and educational sustainability. A quantitative and explanatory design was employed, applying structural equation modelling (SmartPLS) to a sample of 4900 students from public and private universities. The results indicate that AR significantly improves the ease of adoption (β = 0.867), favouring its implementation. In addition, student interaction increases academic motivation (β = 0.597), impacting on perceived academic performance (β = 0.722) and educational sustainability (β = 0.729). These findings highlight the need to design effective learning experiences with AR to maximise their impact. However, challenges such as technological infrastructure, teacher training and equitable access must be addressed to ensure sustainable adoption. This study provides empirical evidence on the potential of AR to enhance motivation, learning and educational transformation. Future research should explore its effectiveness in diverse contexts to optimise pedagogical strategies and institutional policies.

The study aimed to interpret how citizen participation mechanisms contribute to rebuilding public trust in the Peruvian state, considering how citizens evaluate transparency, institutional legitimacy, and state responsiveness. A qualitative approach with an explanatory-interpretive scope was developed, based on a phenomenological-hermeneutic method, and included 4124 participants selected through purposive sampling, whose semi-structured interviews were analyzed through open and axial coding in Atlas.ti v23. The results showed that public trust is mainly shaped by the perceived consistency between institutional discourse and action, clarity of information, accessibility of services, ethical conduct of officials, and responsiveness to social demands. Likewise, it was identified that citizen participation is valued positively when it produces verifiable results, feedback, and continuity, while it is perceived as symbolic when it does not influence decision-making, there is one-way communication, or bureaucratic and technological barriers persist. In conclusion, the study shows that public trust is rebuilt when institutions guarantee transparency, clear communication, and participatory mechanisms with real impact, shaping governance oriented toward openness, shared responsibility, and democratic legitimacy.

This study examines the relationship between social media use for political information, digital citizen participation, and media credibility in Arequipa, Peru's second-largest city. The sample consisted of 4,769 adults residing in urban areas of four provinces. A quantitative, non-experimental, cross-sectional design with a correlational-explanatory scope was used. Data were collected using a structured questionnaire administered in person between November and December 2024. The analysis was performed using structural equation modeling with Partial Least Squares (PLS-SEM) using SmartPLS 4.0. The main findings are: (1) the use of social media for political information is positively associated with digital citizen participation (β = 0.614, p < 0.001); (2) the use of social media is negatively associated with media credibility (β = -0.312, p < 0.001); (3) digital citizen participation is negatively associated with media credibility (β = -0.418, p < 0.001); (4) digital citizen participation partially mediates the relationship between social media use and media credibility (VAF = 45.2%); (5) age moderates platform preference, with young users adopting TikTok and Instagram more intensely; and (6) socioeconomic status moderates the relationship between social media use and media credibility, being more negative in lower socioeconomic strata. Facebook dominates with 75.1% among social media and 42% among all information sources, while 66% of respondents report a negative image of journalists. The results show changes in information consumption patterns, with digital platforms replacing traditional media and eroding media credibility.

University students' ability to identify deepfakes and AI-generated content has become educationally relevant, yet the mechanisms through which AI literacy translates into detection competence are not well understood outside North American and European contexts. This study investigated those mechanisms in a sample of 7,259 undergraduate students from 18 Peruvian universities using a mediation and moderation model. PROCESS Model 4 and Model 58 were applied with bias-corrected bootstrapping (5,000 resamples). AI literacy had a significant direct effect on deepfake identification ability (β = 0.524, p < .001). Deepfake awareness (indirect effect = 0.140, 95% CI [0.113, 0.168]) and verification strategies (indirect effect = 0.075, 95% CI [0.056, 0.095]) both mediated this relationship significantly. Prior AI exposure strengthened detection performance, while high digital media consumption without critical training weakened it (β = −0.089, p < .001). The model accounted for 51.0% of the variance in identification ability. AI literacy alone does not produce reliable detection competence; structured training in synthetic content awareness and active verification habits is required, and these findings carry direct implications for curriculum design in Peruvian and broader Latin American higher education.

Public organizations in Peru have committed substantial resources to artificial intelligence over recent years, yet evidence on whether these investments produce measurable returns has remained scarce. This study evaluated the causal impact of AI adoption on administrative efficiency across 20 Peruvian national public organizations, using a quasi-experimental design combining Difference-in-Differences with Propensity Score Matching, complemented by XGBoost version 1.7.6, Random Forest, GPT-4, and SHAP explainability analysis. The sample comprised 428 civil servants across treatment and control organizations. Results showed significant efficiency gains as perceived by civil servants through validated Likert instruments: work absenteeism decreased by 9.4%, processing times by 8.7%, and administrative costs by 18.2%, all at p < 0.001 with Cohen’s d ranging from 0.55 to 0.90. The convergence between DiD and PSM estimates supports a causal reading of these effects. Four of five hypotheses were supported. AI delivered comparable efficiency gains regardless of institutional complexity, so H2 was not confirmed. Digital infrastructure significantly moderated AI effectiveness (H3: r = 0.198, p = 0.004). Higher resistance to change was significantly associated with lower efficiency outcomes (H5: r = −0.256, p < 0.001), reinforcing the role of proactive change management as a positive moderator of AI effectiveness. SHAP analysis revealed that training investment, specialized IT personnel, and resistance management together explained 51% of predictive importance, outweighing structural variables such as budget size or geographic location. These findings provide the first systematic causal evidence on AI efficiency in Peruvian public administration and offer actionable benchmarks for comparable middle-income public sectors.

Augmented reality (AR) is revolutionising education by integrating virtual elements into physical environments, enhancing interactivity and participation in learning processes. This study analyses the impact of AR in higher education, examining its influence on ease of adoption, student interaction, academic motivation and educational sustainability. A quantitative and explanatory design was employed, applying structural equation modelling (SmartPLS) to a sample of 4,900 students from public and private universities. The results indicate that AR significantly improves the ease of adoption (β = 0.867), favouring its implementation. In addition, student interaction increases academic motivation (β = 0.597), impacting on perceived academic performance (β = 0.722) and educational sustainability (β = 0.729). These findings highlight the need to design effective learning experiences with AR to maximise their impact. However, challenges such as technological infrastructure, teacher training and equitable access must be addressed to ensure sustainable adoption. This study provides empirical evidence on the potential of AR to enhance motivation, learning and educational transformation. Future research should explore its effectiveness in diverse contexts to optimise pedagogical strategies and institutional policies.