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Collaborative problem solving (CPS) enables student groups to complete learning tasks, construct knowledge, and solve problems. Previous research has argued the importance of examining the complexity of CPS, including its multimodality, dynamics, and synergy from the complex adaptive systems perspective. However, there is limited empirical research examining the adaptive and temporal characteristics of CPS, which may have led to an oversimplified representation of the real complexity of the CPS process. To expand our understanding of the nature of CPS in online interaction settings, the present research collected multimodal process and performance data (i.e., speech, computer screen recordings, concept map data) and proposed a three-layered analytical framework that integrated AI algorithms with learning analytics to analyze the regularity of groups’ collaboration patterns. The results surfaced three types of collaborative patterns in groups, namely the behaviour-oriented collaborative pattern (Type 1) associated with medium-level performance, the communication-behaviour-synergistic collaborative pattern (Type 2) associated with high-level performance, and the communication-oriented collaborative pattern (Type 3) associated with low-level performance. This research further highlighted the multimodal, dynamic, and synergistic characteristics of groups’ collaborative patterns to explain the emergence of an adaptive, self-organizing system during the CPS process. According to the empirical research results, theoretical, pedagogical, and analytical implications were discussed to guide the future research and practice of CPS.

Artificial Intelligence in Education (AIEd) is an emerging interdisciplinary field that applies artificial intelligence technologies to transform instructional design and student learning. However, most research has investigated AIEd from the technological perspective, which cannot achieve a deep understand of the complex roles of AI in instructional and learning processes and its relationship with other educational elements. To fill this gap, this review research proposes a conceptual framework from complex adaptive systems theory perspective, uses a systematic literature review approach to locate and summarize articles, and categorizes the roles of AI in the educational system. The review results indicate that when AI is added into an educational system, its roles can be characterized into three categories: AI as a new subject, AI as direct mediator, and AI as a supplementary assistant to influence the instructor-student, student-self, and student-student relationships. Reviewed articles under each category are examined to understand the influences of AI applications on instruction and learning. Based on the results, this systematic review research proposes practical, theoretical, and technological implications of AIEd development.

Communities' pre-disaster resistance, disaster response, and post-disaster recovery processes are all affected by the level of resilience. This manuscript proposes a framework for the study of factors influencing the resilience of mountain communities, with the aim of clarifying the direction of transmission of the influencing relationships of the factors and identifying the key influencing factors. The study explores the characteristics of resilience influences based on community resilience and complex adaptive systems theory, uses an expert survey method to determine the binary relationships between influencing factors, and uses adversarial interpretive structural modelling and social network analysis methods to analyse influencing factors in a hierarchical and networked manner. Finally, key factors are discussed from four composite theoretical perspectives. We found that (1) infrastructure has the most fundamental impact on the factors, (2) information access is most easily influenced by other factors, (3) residents’ place attachment and sense of belonging has a significant impact on other factors in resilience-building practices, and (4) emergency planning and management organisations play a bridging role in the system of influencing factors. The results can help community managers clarify resilience management priorities, allocate management resources more rationally, and provide theoretical guidance for improving community resilience.

Traditional villages embody tangible repositories of historical, cultural, and geographical heritage, and their sustainable and authentic development poses a global challenge. By applying complex adaptive system (CAS) theory via a bottom–up approach, we analyze traditional settlements using China’s Zheshui village as a representative case. Road networks and spatial configurations were examined through image analysis (ImageJ 1.54 p, Depthmap+ Beta 1.0), integrating space syntax, box-counting dimension, and point-density analysis to decode hierarchical point-line-plane structures. Key findings reveal that building units self-similarly aggregate into courtyards under landmark constraints, with courtyards further coalescing into villages. Road systems function as adaptive agents that facilitate nodal information flow while exhibiting fluidity and diversity. The village emerges as a macro-scale complex system from the building-unit level, displaying cross-scale self-similarity, yet intrinsic diversity in architecture and roads underlies its core complexity. BTM topic modeling of tourist sentiment—identifying tourists as novel adaptive agents—predictively guides strategies for enhanced cultural dissemination and public infrastructure. By establishing a CAS-driven internal generative mechanism, this work offers a novel methodological framework for authentic conservation and sustainable development.

Identifying and quantifying ecotourism opportunities are critical processes in sustainable tourism planning, which is challenging, since ecotourism is a Complex Adaptive System (CAS). This study investigated Ecotourism Opportunities Measurements (EOMs) in the literature and mapped the research trends to provide practical implications for research in this area. A systematic quantitative literature review began with a scientometric analysis in CiteSpace to examine the existing knowledge and the state of the art in EOMs. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol was then applied to refine the initial search results, and snowballing was used to collect additional articles. The refined set was then thematically coded and quantitatively analyzed. Our findings show that existing studies on ecotourism opportunities predominantly focus on the impacts of ecotourism on the environment, stakeholders’ contributions toward ecotourism development, sustainability, and responsible behavior of local communities in ecotourism promotion. In addition, five dimensions have been identified under which ecotourism opportunities can be measured, including nature, environmental education/protection, sustainability, socio-cultural benefits, and tourist satisfaction. Existing scales or indices assess potential destinations qualitatively rather than quantitatively. In contrast, an index-based approach might help to solve the challenges of evaluating ecotourism opportunities as a CAS, as well as to quantitatively assess potential destinations to support decision-making related to ecotourism promotion.

Policy Points An onslaught of policies from the federal government, states, the insurance industry, and professional organizations continually requires primary care practices to make substantial changes; however, ineffective leadership at the practice level can impede the dissemination and scale‐up of these policies. The inability of primary care practice leadership to respond to ongoing policy demands has resulted in moral distress and clinician burnout. Investments are needed to develop interventions and educational opportunities that target a broad array of leadership attributes. Context Over the past several decades, health care in the United States has undergone substantial and rapid change. At the heart of this change is an assumption that a more robust primary care infrastructure helps achieve the quadruple aim of improved care, better patient experience, reduced cost, and improved work life of health care providers. Practice‐level leadership is essential to succeed in this rapidly changing environment. Complex adaptive systems theory offers a lens for understanding important leadership attributes. Methods A review of the literature on leadership from a complex adaptive system perspective identified nine leadership attributes hypothesized to support practice change: motivating others to engage in change, managing abuse of power and social influence, assuring psychological safety, enhancing communication and information sharing, generating a learning organization, instilling a collective mind, cultivating teamwork, fostering emergent leaders, and encouraging boundary spanning. Through a secondary qualitative analysis, we applied these attributes to nine practices ranking high on both a practice learning and leadership scale from the Learning from Effective Ambulatory Practice (LEAP) project to see if and how these attributes manifest in high‐performing innovative practices. Findings We found all nine attributes identified from the literature were evident and seemed important during a time of change and innovation. We identified two additional attributes—anticipating the future and developing formal processes—that we found to be important. Complexity science suggests a hypothesized developmental model in which some attributes are foundational and necessary for the emergence of others. Conclusions Successful primary care practices exhibit a diversity of strong local leadership attributes. To meet the realities of a rapidly changing health care environment, training of current and future primary care leaders needs to be more comprehensive and move beyond motivating others and developing effective teams.

The relationship between humans and land environment within historical settlements reflects the intricate interplay between human societies, their construction activities, and the specific geographical contexts. Inadequate research into this relationship hinders a comprehensive understanding of the social spatial intricacies inherent in historical settlements. This paper adopts the theoretical framework of complex adaptive system and takes Shawan Ancient Town in Guangfu area of China as an example. Under the geographical background of sustainable land growth in the coastal zone, this study analyzed the subtle changes in the relationship between people and land during the historical construction, and the key findings of the investigation are threefold: (1) Land resources play a central role in the construction of human-land relationships in historical settlements. The geographical environment and social institutions serve as configuring factors in the formation and evolution of human-land relationships. These factors collectively determine the formation and evolution of human-land relationships. (2) Social space emerges as a pivotal manifestation of the human–environment relationship in historical settlements, transcending mere physical dimensions. Consequently, a holistic study of this relationship necessitates a comprehensive exploration not only of spatial configurations but also of the intricate interconnections among social bonds, structural formations, societal order, and settlement spatiality. (3) Drawing on the framework of complex adaptive systems theory, the study disentangles intricate elements within the human-land relationship of historical settlements. It distills and examines the manifestations of four intricate adaptive capacities—namely aggregation, non-linearity, flow, and diversity—alongside the mechanisms of tags, internal models, and fundamental building blocks. It is believed that the study of historical settlements in coastal areas needs to grasp the invariable social-spatial objects such as geographical environment, land form, local beliefs. Take it as a clue to sort out how other elements of change have iterated and transformed in the process of historical evolution, such as the rise and fall of families, land ownership changes and social class evolution. This paper explores the value connotation of historical settlements from the perspective of dialectic thinking of change and invariance with CAS theory, which has theoretical significance for protection of settlement's human-land relationship from the perspective of \"social-spatial\".

In the context of global environmental change and continuous urbanization, enhancing urban resilience is an important way to improve urban emergency management capacity and achieve sustainable development of urban systems. It is of great significance to clarify the mechanisms and effects of urban resilience and carry out resilience measurement to improve the level of urban system resilience and alleviate the pressure of environmental disturbances on the stable operation of urban systems. As an important part of the “Belt and Road” Initiative and one of the few leading economic regions in western China, promoting the high-quality development of the Lanzhou-Xining urban agglomeration is of profound significance for strengthening ethnic unity and stabilizing the northwest and southwest regions. Based on the complex adaptive system (CAS) theory and the adaptive cycle model, this study understands urban resilience as the comprehensive result of urban system stability, self-organization, learning adaptability and transformability, constructs a multi-level open index evaluation system, and analyzes the spatio-temporal evolution characteristics of urban resilience of the Lanzhou-Xining urban agglomeration from the proposed design to the formal planning in 2010–2017. The findings are as follows: (1) Research on the urban resilience of the Lanzhou-Xining urban agglomeration verifies the applicability of the evolutionary urban resilience analysis framework and makes preliminary findings on urban resilience based on CAS theory, which provide a certain theoretical reference for the research on the spatio-temporal evolution of urban resilience. (2) From 2010 to 2017, significant differences are observed between various urban attributes. Resilience exhibits an overall upward trend, and spatial evolution changes from a double core (Lanzhou and Xining) to three cores (Lanzhou, Xining and Haidong) and polycentric modes. (3) Based on urban resilience characteristics and an urban system adaptability cycle model, this paper divides the Lanzhou-Xining urban agglomeration cities into four types (exploitation–reorganization, conservation–release, conservation–exploitation and exploitation), and proposes corresponding adaptive management countermeasures. These could be adopted as a reference to promote the high-quality development of the Lanzhou-Xining urban agglomeration.

Purpose - The purpose of this paper is to explore the emergence of resilience into the contemporary discourse of disaster risk. As a counter position to the current status quo in defining and addressing resilience, this paper introduces the theoretical lens of complex adaptive systems theory (CAS). Some of the key characterisitcs related to CAS are discussed and linkages are made to possible benefit that they might have in enhancing the understanding of disaster resilience. Design/methodology/approach - An indepth review of literature pertaining to disaster resilience and CAS was conducted to find common grounds for theoretical synergies. Findings - The inherent similarities between the concept of resilience and CAS provides ample practical and theoretical contributions to the field of disaster risk studies. Originality/value - The paper provides a different perspective to the contemporary discourse on disaster resilience. A better understanding of disaster resilience and its underlying dynamics as illuminated by the application of CAS could in future provide an effective tool to manage disaster risks and building of resilience.

PurposeOur study advances theory in supply chain resilience (SCRes) by identifying and describing the mechanisms through which interorganizational relationships (IORs) contribute to SCRes.Design/methodology/approachWe employ a multi-method conceptual development design combining structured and narrative review of the literature, supported by illustrative case studies. A four-stage refinement process was used for data reduction, and analysis was informed by complex adaptive systems (CAS) theory.FindingsOur findings identify connectivity, collectivity and scalability as key mechanisms through which relationships between organizations contribute to SCRes. These mechanisms draw on IOR elements of information sharing, decision synchronization and incentive alignment to augment self-organization and emergence, and adaptation and coevolution via modifying/advancing resilience strategies and practices.Originality/valueOur study advances theory and practice of SCRes by expounding on how connectivity, collectivity and scalability act as mechanisms that drive and diffuse the contribution of resilient strategies/practices to resilience capability. This is significant for strategic alignment between IORs and SCRes.