In an era defined by complex,interconnected challenges like climate change,pandemics,and resource depletion,the traditional siloed approach to science education is proving increasingly insufficient.Interdisciplinary p...In an era defined by complex,interconnected challenges like climate change,pandemics,and resource depletion,the traditional siloed approach to science education is proving increasingly insufficient.Interdisciplinary project-based learning represents a promising path forward in science education,fostering integrated and holistic learning experiences that move beyond isolated subject learning.Grounded in philosophical ideas of holism,pragmatism,constructivism,and transcendentalism,this article presents a case project illustrating the practical application of interdisciplinary project-based learning.This project engages students in integrating concepts from biology,chemistry,earth science,engineering,and social studies.Through phased activities-research and planning,data collection,implementation,and presentation-students develop a decent understanding of real-world problems while fostering skills in collaboration,problem-solving,and a sense of civic responsibility.Additionally,strategies are proposed to navigate the challenges associated with implementing interdisciplinary project-based learning,including aligning projects with standards,investing in professional development,leveraging community resources,and building support from stakeholders.展开更多
Artificial intelligence(AI)has evolved at an unprecedented pace in recent years.This rapid advancement includes algorithmic breakthroughs,cross-disciplinary integration,and diverse applications—driven by growing comp...Artificial intelligence(AI)has evolved at an unprecedented pace in recent years.This rapid advancement includes algorithmic breakthroughs,cross-disciplinary integration,and diverse applications—driven by growing computational power,massive datasets,and collaborative global research.This special issue of Emerging Artificial Intelligence Technologies and Applications was conceived to provide a platformfor cuttingedge AI research communication,developing novel methodologies,cross-domain applications,and critical advancements in addressing real-world challenges.Over the past months,we have witnessed a remarkable diversity of submissions,reflecting the global trend of AI innovation.Below,we synthesize the key insights from these works,highlighting their collective contribution to advancing AI’s theoretical frontiers and practical applications.展开更多
Introduction:As challenges to biodiversity mount,land-use policies have been implemented to balance human needs and the integrity of ecological systems.One such program,Payments for Ecosystem Services(PES),incentivize...Introduction:As challenges to biodiversity mount,land-use policies have been implemented to balance human needs and the integrity of ecological systems.One such program,Payments for Ecosystem Services(PES),incentivizes resource users to protect ecosystem services and has been implemented around the world to reduce soil erosion,create or improve wildlife habitats,and improve water quality and other environmental goals.The PES policy,at its core,is a concept that aims to capture the reciprocal relationships between human systems and ecological function and process.As such,PES epistemologically embodies a coupled human and natural systems approach.Outcomes:Yet,despite this conceptual alignment,the on-the-ground implementation or evaluation of PES typically does not adopt this coupled approach and PES programs have little integration between socioeconomic,sociocultural,human demographic,and ecological elements.To advance the evolution of PES,we consider what and how socioeconomic and ecological factors have been incorporated into PES program implementation and evaluation.We also present a conceptual model to articulate how PES research can capture the reciprocal relationships among socioeconomics,demography,and ecology and discuss the quantitative modeling approaches that can support this conceptual development,i.e.,structural equation and agent-based modeling,and latent trajectory models.Conclusions:By strengthening the conceptual framework for PES within a coupled human and natural systems approach and identifyinganalytical approaches that can be used to quantify and characterize these complex cross-disciplinary relationships,we aim to support the evolution and advancement of PES,in service of more meaningful and positive outcomes for human well-being and ecological sustainability.展开更多
基金supported by the Anhui Provincial Education Science Research Program titled“Research on the Construction and Application of Evaluation Frameworks for Interdisciplinary Practical Activities in Primary School Science”(JKT25114)the Humanities and Social Sciences Research Program of Anhui Higher Education Institutions(2022AH052117).
文摘In an era defined by complex,interconnected challenges like climate change,pandemics,and resource depletion,the traditional siloed approach to science education is proving increasingly insufficient.Interdisciplinary project-based learning represents a promising path forward in science education,fostering integrated and holistic learning experiences that move beyond isolated subject learning.Grounded in philosophical ideas of holism,pragmatism,constructivism,and transcendentalism,this article presents a case project illustrating the practical application of interdisciplinary project-based learning.This project engages students in integrating concepts from biology,chemistry,earth science,engineering,and social studies.Through phased activities-research and planning,data collection,implementation,and presentation-students develop a decent understanding of real-world problems while fostering skills in collaboration,problem-solving,and a sense of civic responsibility.Additionally,strategies are proposed to navigate the challenges associated with implementing interdisciplinary project-based learning,including aligning projects with standards,investing in professional development,leveraging community resources,and building support from stakeholders.
文摘Artificial intelligence(AI)has evolved at an unprecedented pace in recent years.This rapid advancement includes algorithmic breakthroughs,cross-disciplinary integration,and diverse applications—driven by growing computational power,massive datasets,and collaborative global research.This special issue of Emerging Artificial Intelligence Technologies and Applications was conceived to provide a platformfor cuttingedge AI research communication,developing novel methodologies,cross-domain applications,and critical advancements in addressing real-world challenges.Over the past months,we have witnessed a remarkable diversity of submissions,reflecting the global trend of AI innovation.Below,we synthesize the key insights from these works,highlighting their collective contribution to advancing AI’s theoretical frontiers and practical applications.
基金This work was supported by the National Science Foundation under the Dynamics of Coupled Natural and Human Systems program:[Grant Number DEB-1212183].
文摘Introduction:As challenges to biodiversity mount,land-use policies have been implemented to balance human needs and the integrity of ecological systems.One such program,Payments for Ecosystem Services(PES),incentivizes resource users to protect ecosystem services and has been implemented around the world to reduce soil erosion,create or improve wildlife habitats,and improve water quality and other environmental goals.The PES policy,at its core,is a concept that aims to capture the reciprocal relationships between human systems and ecological function and process.As such,PES epistemologically embodies a coupled human and natural systems approach.Outcomes:Yet,despite this conceptual alignment,the on-the-ground implementation or evaluation of PES typically does not adopt this coupled approach and PES programs have little integration between socioeconomic,sociocultural,human demographic,and ecological elements.To advance the evolution of PES,we consider what and how socioeconomic and ecological factors have been incorporated into PES program implementation and evaluation.We also present a conceptual model to articulate how PES research can capture the reciprocal relationships among socioeconomics,demography,and ecology and discuss the quantitative modeling approaches that can support this conceptual development,i.e.,structural equation and agent-based modeling,and latent trajectory models.Conclusions:By strengthening the conceptual framework for PES within a coupled human and natural systems approach and identifyinganalytical approaches that can be used to quantify and characterize these complex cross-disciplinary relationships,we aim to support the evolution and advancement of PES,in service of more meaningful and positive outcomes for human well-being and ecological sustainability.
