This paper addresses the critical need for a holistic,evidence-based national strategy to cultivate a world-class artificial intelligence(Al)talent pool.As Al reshapes global economies,labor markets,and the geopolitic...This paper addresses the critical need for a holistic,evidence-based national strategy to cultivate a world-class artificial intelligence(Al)talent pool.As Al reshapes global economies,labor markets,and the geopolitical land-scape,national competitiveness hinges on the ability to develop,attract,and retain Al expertise.Employing a systematic scoping review methodology,this study synthesizes evidence from academic literature,government policy documents,and industry white papers to construct an integrated strategic blueprint.The analysis decon-structs the core components of a comprehensive talent development policy,proposing a multi-pillar framework that integrates a lifelong learning continuum,a differentiated talent pipeline architecture,synergistic public-private enablers,and modernized evaluation paradigms.Through a comparative analysis of divergent nationalstrategies-including the market-driven model of the United States,the governance-first approach of the Eu-ropean Union,and the state-directed models of India,Singapore,the United Arab Emirates,and Canada-this paper illuminates the trade-offs between different philosophical and tactical choices.Key findings reveal the heterogeneous nature of Al's impact on labor,the centrality of public trust as a prerequisite for adoption,and a necessary paradigm shift from credential-based to competency-based talent evaluation.The proposed blueprint,which introduces a novel"Builder-Bridger"talent model,offers a comprehensive,actionable guide for policymakers and academic leaders aiming to build a sustainable and globally competitive national Al talent base capable of navigating the complexities of the Al era.展开更多
The pedagogical promise of Competency-Based Education(CBE)has been historically undermined by pro-found challenges of scalability,creating an implementation gap between its theoretical merits and practicalapplication....The pedagogical promise of Competency-Based Education(CBE)has been historically undermined by pro-found challenges of scalability,creating an implementation gap between its theoretical merits and practicalapplication.This paper proposes a testable mechanism model wherein Artificial Intelligence(Al)enables the scaling of CBE through three interconnected pathways-diagnostic tracking,adaptive supply,and teacher or-chestration-formalized within a distributed cognition framework.To operationalize this model,this paper in-troduces novel constructs including the"Adaptive-Autonomy Curve"for systematically cultivating self-regulated learning in personalized environments,and a"Situated Performance-Based Assessment Pipeline"for authentic,scalable evaluation of complex skills.The primary contributions of this work are fourfold:first,it provides a rigorous conceptual taxonomy that delineates CBE from adjacent paradigms such as mastery learning and per-sonalized learning;second,it advances a set of falsifiable propositions to guide future empirical research;third,it formalizes the human-Al pedagogical relationship with operational design principles;and fourth,it presents an integrated governance and interoperability protocol for the responsible and effective implementation of Al in competency-based systems.展开更多
文摘This paper addresses the critical need for a holistic,evidence-based national strategy to cultivate a world-class artificial intelligence(Al)talent pool.As Al reshapes global economies,labor markets,and the geopolitical land-scape,national competitiveness hinges on the ability to develop,attract,and retain Al expertise.Employing a systematic scoping review methodology,this study synthesizes evidence from academic literature,government policy documents,and industry white papers to construct an integrated strategic blueprint.The analysis decon-structs the core components of a comprehensive talent development policy,proposing a multi-pillar framework that integrates a lifelong learning continuum,a differentiated talent pipeline architecture,synergistic public-private enablers,and modernized evaluation paradigms.Through a comparative analysis of divergent nationalstrategies-including the market-driven model of the United States,the governance-first approach of the Eu-ropean Union,and the state-directed models of India,Singapore,the United Arab Emirates,and Canada-this paper illuminates the trade-offs between different philosophical and tactical choices.Key findings reveal the heterogeneous nature of Al's impact on labor,the centrality of public trust as a prerequisite for adoption,and a necessary paradigm shift from credential-based to competency-based talent evaluation.The proposed blueprint,which introduces a novel"Builder-Bridger"talent model,offers a comprehensive,actionable guide for policymakers and academic leaders aiming to build a sustainable and globally competitive national Al talent base capable of navigating the complexities of the Al era.
文摘The pedagogical promise of Competency-Based Education(CBE)has been historically undermined by pro-found challenges of scalability,creating an implementation gap between its theoretical merits and practicalapplication.This paper proposes a testable mechanism model wherein Artificial Intelligence(Al)enables the scaling of CBE through three interconnected pathways-diagnostic tracking,adaptive supply,and teacher or-chestration-formalized within a distributed cognition framework.To operationalize this model,this paper in-troduces novel constructs including the"Adaptive-Autonomy Curve"for systematically cultivating self-regulated learning in personalized environments,and a"Situated Performance-Based Assessment Pipeline"for authentic,scalable evaluation of complex skills.The primary contributions of this work are fourfold:first,it provides a rigorous conceptual taxonomy that delineates CBE from adjacent paradigms such as mastery learning and per-sonalized learning;second,it advances a set of falsifiable propositions to guide future empirical research;third,it formalizes the human-Al pedagogical relationship with operational design principles;and fourth,it presents an integrated governance and interoperability protocol for the responsible and effective implementation of Al in competency-based systems.
