ABSTRACT: Higher education continues to face a persistent gap between academic outcomes and workforce demands, a problem intensified by the limited explanatory value of traditional transcripts. In response, digital badges and micro-credentials have emerged as tools for documenting verifiable competencies. However, the existing evidence base remains fragmented and methodologically constrained. To address this, this narrative review synthesizes recent empirical research on the integration, utility, and impact of digital credentials. A comprehensive search of EBSCOhost, PubMed, and Google Scholar was conducted, capturing literature published between 2017 and 2025. Following a structured screening protocol, 14 peer-reviewed empirical studies were selected and evaluated using a hybrid inductive and deductive thematic analysis. The synthesized findings demonstrate that well-designed badge systems extend beyond gamified incentives to function as sophisticated pedagogical tools supporting self-regulated learning and professional identity formation. Key results indicate a complex duality in learner motivation, where initial extrinsic engagement must transition into perceived intrinsic value for sustained persistence. Additionally, while stackable frameworks provide transparent alternatives to traditional grading, poorly integrated systems risk inducing cognitive overload and grade anxiety without active instructor mediation. Effective implementation requires balancing standardized labor market recognition with contextual flexibility through sustained collaboration between higher education institutions and industry stakeholders. The review concludes by highlighting the critical need for objective longitudinal and cross-cultural research to determine long-term pedagogical impacts and promote equitable educational outcomes.

ABSTRACT: Artificial intelligence (AI) is rapidly reshaping school leadership within Education 4.0, offering enhanced decision-making and organisational efficiency while intensifying ethical concerns regarding transparency, bias, and accountability. Existing research has largely treated these opportunities and risks as separate phenomena, overlooking the relational processes through which AI is enacted in practice. This paper advances a process-based conceptualisation by positioning trust as the central mediating mechanism in AI-enabled school leadership. It argues that AI does not produce outcomes directly; rather, its effects are contingent on how it is accepted, interpreted, and enacted within school contexts. The proposed framework shows that trust shapes whether AI leads to constructive outcomes, including ethical use, professional engagement, and improvement, or to disruptive consequences such as resistance and mistrust. Leadership is conceptualised as a key antecedent of trust, highlighting the centrality of relational governance in the effective and responsible integration of AI in schools.