Knowledge production in a constructed field: reflections on comparative and international education

Adopting Maria Manzon’s theoretical framework, which draws on Foucault and proposes that comparative education as an academic field is socially constructed, I suggest that the field is neither stable nor well defined. To demonstrate this, I conduct a content analysis of the Comparative Education Review, using Klaus Krippendorff’s methodological framework to study comparative and international education (CIE) researchers’ understanding of the national—and of their related knowledge production in the field. Many comparativists express interests in multiple countries, and their knowledge production takes the form of individual country studies. The countries are habitually studied using a “problem approach” focusing on one specific aspect of the country under investigation and using an associated social science methodology deemed appropriate. Few comparativists are making explicit use of or reference to any methodology that is unique to comparative education. Efforts to catalog and systematize CIE research have demonstrated that the field is becoming so inclusive that it hardly is distinguishable from educational studies as a whole. Hence, I suggest that instead of speaking about unifying features of the field, it may be more relevant to speak about frequent elements, such as a focus on the national, and a knowledge production characterized by the academic practitioner who desires to improve the education systems studied. A third frequent element may be the focus on educational development, thus justifying the label of “comparative, international, and development education.” One challenge of the field is its dependence on Western social science discourses, which may be marginalizing other voices.     

A Classroom Exercise to Examine the Trade‐off between Mission Capacity and Life Cycle Cost

This article presents a classroom exercise, centered on a simulation that has been used for 4 years in an MBA program to help students develop an understanding of the trade‐offs involved in managing capital assets in the public sector. Though often ignored in business schools, mission is a key criterion that must be considered when managing such assets, and acts as a surrogate for profit. The case presents a rich environment in which the impact of cost reductions (or additional investments) on mission can be quantified, and trade‐offs can be assessed and discussed. It gives students a chance to develop creative ideas for process improvement, and provides sufficient data for them to analyze the impact of their suggestions in a rigorous way.     

Unpacking foreshadowing in mathematics teachers’ planned practices

This paper provides an empirical exploration of mathematics teachers’ planned practices. Specifically, it explores the practice of foreshadowing, which was one of Wasserman’s (2015) four mathematical teaching practices. The study analyzed n?=?16 lessons that were planned by pairs of highly qualified and experienced secondary mathematics teachers, as well as the dialogue that transpired, to identify the considerations the teachers made during this planning process. The paper provides empirical evidence that teachers engage in foreshadowing as they plan lessons, and it exemplifies four ways teachers engaged in this practice: foreshadowing concepts, foreshadowing techniques, foregrounding concepts, and foregrounding techniques. Implications for mathematics teacher education are discussed.

     

Global pedigree and national imperative: Hong Kong universities’ response to China’s grand strategies

Higher Education - Literature offers a theoretical framework exemplifying the inherent tensions between “becoming Chinese” and “remaining global” in the evolution of the...     

The Multidimensionality of Measurement Bias in High-Stakes Testing: Using Machine Learning to Evaluate Complex Sources of Differential Item Functioning

Test developers and psychometricians have historically examined measurement bias and differential item functioning (DIF) across a single categorical variable (e.g., gender), independently of other variables (e.g., race, age, etc.). This is problematic when more complex forms of measurement bias may adversely affect test responses and, ultimately, bias test scores. Complex forms of measurement bias include conditional effects, interactions, and mediation of background information on test responses. I propose a multidimensional, person-specific perspective of measurement bias to explain how complex sources of bias can manifest in the assessment of human knowledge, skills, and abilities. I also describe a data-driven approach for identifying key sources of bias among many possibilities—namely, a machine learning method commonly known as regularization.     

Relationship of executive functioning and memory to autism symptomology and adaptive functioning: Implications for reducing future underemployment

Understanding the relationship between executive functioning and its connection to working memory and adaptive functioning can inform planning and employment efforts. This study explored the relationship between memory and adaptive functioning with a sample of Autistic youths/young adults. Participant mean age was 21.3 (SD = 3.0). Of the 22 participants, 17 were male, and 19 white, non-Hispanic/Latina/o/x. All but one lived with their parent(s). Participants were administered a full battery assessing cognitive ability (WAIS-IV), memory and executive functioning (WMS-IV and DKEFS), autism symptomatology (ADOS-II), and adaptive functioning (SIB-R). A multivariate lasso regression model was used. Memory, especially as measured on the WMS-IV, was found to be significantly related to adaptive functioning and autism symptomatology. There appears to be continuing evidence that memory is highly related to adaptive functioning and autism symptomatology. Interventions involving auditory and immediate memory could be helpful in promoting more mutually effective social interactions necessary for positive employment outcomes.     

How students reason about matter flows and accumulations in complex biological phenomena: An emerging learning progression for mass balance

In recent years, there has been a strong push to transform STEM education at K-12 and collegiate levels to help students learn to think like scientists. One aspect of this transformation involves redesigning instruction and curricula around fundamental scientific ideas that serve as conceptual scaffolds students can use to build cohesive knowledge structures. In this study, we investigated how students use mass balance reasoning as a conceptual scaffold to gain a deeper understanding of how matter moves through biological systems. Our aim was to lay the groundwork for a mass balance learning progression in physiology. We drew on a general models framework from biology and a covariational reasoning framework from math education to interpret students' mass balance ideas. We used a constant comparative method to identify students' reasoning patterns from 73 interviews conducted with undergraduate biology students. We helped validate the reasoning patterns identified with >8000 written responses collected from students at multiple institutions. From our analyses, we identified two related progress variables that describe key elements of students' performances: the first describes how students identify and use matter flows in biology phenomena; the second characterizes how students use net rate-of-change to predict how matter accumulates in, or disperses from, a compartment. We also present a case study of how we used our emerging mass balance learning progression to inform instructional practices to support students' mass balance reasoning. Our progress variables describe one way students engage in three dimensional learning by showing how student performances associated with the practice of mathematical thinking reveal their understanding of the core concept of matter flows as governed by the crosscutting concept of matter conservation. Though our work is situated in physiology, it extends previous work in climate change education and is applicable to other scientific fields, such as physics, engineering, and geochemistry.     

Networked feedback control for nonlinear systems with random varying delays

This paper discusses the controller synthesis problem of a nonlinear networked controlled system subject to delays in the measurement and actuation channels. The communication through the network also suffers non-stationary packet dropouts. The bounded nonlinearities in the plant state satisfy Lipschitz conditions. A Lyapunov function is developed for the closed-loop system considering dynamic output feedback and the resulting stabilization conditions are drawn in the form of linear matrix inequalities to ensure that the system is exponentially stable in the mean-square sense. The developed conditions are represented in the form of a convex optimization problem and the results are tested by simulation on a quadruple-tank process.