Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
97,883
result(s) for
"Organization Theory"
Sort by:
Learning at the Boundaries of Research and Practice: A Framework for Understanding Research—Practice Partnerships
Given the rapid growth of research—practice partnerships (RPPs), we need a framework that helps the field understand how RPPs can facilitate organizational learning in service of local educational improvement and transformation. Drawing on sociocultural and organizational learning theories, we argue that learning can happen for the organizations engaged in RPPs at the boundaries of research and practice. Such learning is evident when there are changes in collective knowledge, policies, and routines of participating organizations, with implications for longer-term outcomes of educational improvement and transformation locally and more broadly. The degree to which organizations can make use of the ideas from the RPP is dependent, in part, on the presence and design of boundary infrastructure and the preexisting organizational capacities and conditions. We conclude with implications for those engaging in RPPs and future research.
Journal Article
Handbook on the economics and theory of the firm
The title of the handbook makes reference to the economics of the firm and the theory of the firm, two areas which are traditionally treated separately in the literature. The novel idea of this authoritative volume is to demonstrate that these two areas closely interact.
Book
Education as a Complex System: Conceptual and Methodological Implications
Education is a complex system, which has conceptual and methodological implications for education research and policy. In this article, an overview is first provided of the Complex Systems Conceptual Framework for Learning (CSCFL), which consists of a set of conceptual perspectives that are generally shared by educational complex systems, organized into two focus areas: collective behaviors of a system, and behaviors of individual agents in a system. Complexity and research methodologies for education are then considered, and it is observed that commonly used quantitative and qualitative techniques are generally appropriate for studying linear dynamics of educational systems. However, it is proposed that computational modeling approaches, being extensively used for studying nonlinear characteristics of complex systems in other fields, can provide a methodological complement to quantitative and qualitative education research approaches. Two research case studies of this approach are discussed. We conclude with a consideration of how viewing education as a complex system using complex systems' conceptual and methodological tools can help advance education research and also inform policy.
Journal Article
The Multiple Meanings of Scale: Implications for Researchers and Practitioners
Interest in the study of scale has grown over the past three decades, yet it still suffers from a lack of conceptual clarity. Despite attempts at conceptualizing scale, there is still wide diversity in how the term “scale” is used. These differences matter. They impact how scale is studied, the strategies used to achieve scale, and the lessons we can draw across studies of the scale of innovations. In this article, we argue that scale is a polysemic and dynamic phenomenon. There are multiple, legitimate definitions of scale, and such definitions can shift over time, depending on the goals and needs of reformers. Drawing upon an extensive review of the literature, we present a typology of scale comprising four predominant conceptualizations in the literature. We detail the conceptualizations and discuss the affordances and challenges of each. We conclude by offering implications of the polysemic, dynamic nature of scale for researchers and reformers. Presenting this typology, we aim to spark new conversations about scale and to help guide future scale research and practice.
Journal Article
Goal Directedness, Chemical Organizations, and Cybernetic Mechanisms
In this article, we attempt at developing a scenario for the self-organization of goal-directed systems out of networks of (chemical) reactions. Related scenarios have been proposed to explain the origin of life starting from autocatalytic sets, but these sets tend to be too unstable and dependent on their environment to maintain. We apply instead a framework called Chemical Organization Theory (COT), which shows mathematically under which conditions reaction networks are able to form self-maintaining, autopoietic organizations. We introduce the concepts of perturbation, action, and goal based on an operationalization of the notion of change developed within COT. Next, we incorporate the latter with notions native to the theory of cybernetics aimed to explain goal directedness: reference levels and negative feedback among others. To test and refine these theoretical results, we present some examples that illustrate our approach. We finally discuss how this could result in a realistic, step-by-step scenario for the evolution of goal directedness, thus providing a theoretical solution to the age-old question of the origins of purpose.
Journal Article
Revealing the hierarchical structure of microbial communities
Measuring the dynamics of microbial communities results in high-dimensional measurements of taxa abundances over time and space, which is difficult to analyze due to complex changes in taxonomic compositions. This paper presents a new method to investigate and visualize the intrinsic hierarchical community structure implied by the measurements. The basic idea is to identify significant intersection sets, which can be seen as sub-communities making up the measured communities. Using the subset relationship, the intersection sets together with the measurements form a hierarchical structure visualized as a Hasse diagram. Chemical organization theory (COT) is used to relate the hierarchy of the sets of taxa to potential taxa interactions and to their potential dynamical persistence. The approach is demonstrated on a data set of community data obtained from bacterial 16S rRNA gene sequencing for samples collected monthly from four groundwater wells over a nearly 3-year period (n = 114) along a hillslope area. The significance of the hierarchies derived from the data is evaluated by showing that they significantly deviate from a random model. Furthermore, it is demonstrated how the hierarchy is related to temporal and spatial factors; and how the idea of a core microbiome can be extended to a set of interrelated core microbiomes. Together the results suggest that the approach can support developing models of taxa interactions in the future.
Journal Article