Bundled or unbundled? A multi-text corpus-assisted discourse analysis of the relationship between teaching and research in UK universities

Creating and disseminating knowledge through research and teaching has long been regarded as the hallmark of the modern university. However, new university business models have called into question the ‘bundling’ of teaching and research, and sustained research on the relationship between teaching and research has found little evidence of an insoluble connection between the two activities. In this article, we explore the relationship between teaching and research from the perspective of universities’ institutional discourse. We use corpus-assisted discourse analysis to examine the relationship between research and teaching as presented in two sets of institutional texts currently influential in UK Higher Education: Research Excellence Framework environment statements and Teaching Excellence Framework provider submissions (a total of 2143 documents and 12,492,071 words). Our findings show that, while universities emphasise the value of research to their teaching, they do not always emphasise (or sometimes even decry) the influence of teaching on their research. We empirically evidence that, according to what universities themselves write in institutional texts, teaching and research are not always in a mutually beneficial entanglement, but often rather a one-way relationship in which research expertise and institutional prestige are used to bolster claims of teaching excellence. This has implications for the communication of both the vision and the purpose of a university in regulatory exercises and wider policy, but also speaks to the broader idea and practice of being a university in the twenty-first century.     

‘Teaching’ the path towards university: understanding student access through storied-futures and meritocratic grand narratives

The notion that the stories of our lives shape dispositions towards imagined futures is another lens through which university underrepresentation should be viewed. A storied lens attends to how futures, like university attendance, are storied during childhood to the extent that some youth imagine, and therefore plan, these futures as natural progression. Such was the case for study participants, indicating that childhood stories contain answers for mitigating social reproduction connected to parental education and cultural forces within the home. Examining social mobility through the underexplored storied-futures grand narrative presents unique solutions that lay hidden within the dominant meritocratic grand narrative.     

Breaking Down Barriers for Student Parents and Caregivers with Family-Friendly Library Spaces

Abstract

In 2016, J. Murrey Atkins Library at the University of North Carolina at Charlotte opened a reservable study room where student parents and caregivers can study with their children on campus. In 2018, the library opened a second family-friendly study room to meet the needs of our growing campus community. To inform the room design, the library conducted a mixed methods research study that included a user survey, an examination of room reservation and usage data, and one-on-one user interviews. This paper focuses on the user-centered design process used to inform the development of the second, family-friendly, library study room.     

汇川H2U系列PLC之间RS-485通信的实现

主要研究了汇川公司H2U可编程控制器(PLC)的通信技术,实现了两个H2U系列PLC之间基于RS-485的通信,并详细介绍了PLC之间通信的硬件连接方式、通信串口参数配置、触摸屏画面的设计以及程序实现。所讨论的方法已在采用H2U PLC及辅助设备组建的"运动控制系统"课程的教学实验平台上进行了验证,可以拓展应用于多台H2U PLC之间以及其他设备与H2U PLC之间的RS-485通信实现,对工程应用具有一定的借鉴意义。     

Discrete Choice Modeling in Education: An Innovative Method to Assess Teaching Practices

Self‐reported measures are an easy, time‐efficient, and low‐cost way to collect research data compared to other assessment methods. They are, however, characterized by several limitations regarding the quality and the clarity of the data they produce, especially when they are implemented in education. The main purpose of the current study was to use a method called discrete choice modeling (DCM) in education, in order to develop a self‐reported instrument that will reduce the bias for socially desirable responses and to assess teachers’ practices in physical activity. DCM method has the ability to overcome the respondents’ tendency to answer in a socially desirable way. A nationally representative sample of 531 Greek early educators participated in this study and were administered a self‐assessment questionnaire based on DCM. Results showed that the DCM based newly developed instrument manages to assess effectively educators’ practices and provided evidence of the applicability of the method in education. Further implications and future recommendations regarding the effective application of DCM in education are discussed.     

Parents’ son preference,childhood adverse experience and mental health in old age: Evidence from China

BackgroundSon preference is an enduring phenomenon in China and may often be related to childhood adverse experiences. According to a life-course perspective, adverse experiences during a childhood period may have a long-term effect on mental health in later age. However, little is known about this relationship between parents’ son preference, childhood adverse experiences and adulthood mental health in China.ObjectiveThe study aims to evaluate the association of parents’ son preference and individual mental health in old age in China. The mediating role of childhood adverse experiences was also estimated.Participants and settingThe China Health and Retirement Longitudinal Study (CHARLS) 2015 combined with CHARLS life history survey was analyzed (N = 11,666).MethodsMental health was measured by a shortened modification of the Center for Epidemiologic Studies Depression scale including seven items, and higher scores indicated worse mental health status. A four-step mediating model was applied.ResultsRespondents growing in families with son preference had on average 0.75 (P < 0.001) points higher on the mental health scale than their counterparts, and the effects were consistent for both males and females. Childhood adverse experiences measured by physical maltreatment, emotional adverse experiences and witnesses of inter-parent violence mediated the relationship between parents’ son preference and individual adulthood mental health by 47.87%. For females, physical maltreatment and emotional adverse experiences explained the most parts of health effects of parents’ son preference, whereas witnesses of inter-parent violence was the most influential mediator for males.ConclusionParents’ son preference led to adverse childhood experiences, which influenced mental health in adulthood.     

A longitudinal investigation of protective factors for bereaved maltreated youth

BackgroundMaltreated youth are at an elevated risk for the development of problem behaviors. Coping with the death of a family member or close friend during adolescence, referred to as bereavement, is a stressful event that could potentiate risk linked to maltreatment. However, developmental research suggests that youth adjustment is a product of multiple risk and protective factors. Although maltreated youth who experience loss may be particularly vulnerable to behavior problems, personal and contextual factors may attenuate or exacerbate youths’ risk for internalizing and externalizing psychopathology.ObjectiveThe overarching goal of this study is to examine individual, family, and community-level protective factors for maltreated youth who experience bereavement. Specifically, we aim to examine the effect of age 12 bereavement on age 16 internalizing and externalizing psychopathology, and to investigate the moderating role of multi-level protective factors at ages 14 and 16.MethodsThe study consisted of a sample of 800 youth (52.4% female, 45.1% African-American) drawn from the Longitudinal Studies of Child Abuse and Neglect (LONGSCAN), collected from 1998 to 2011.ResultsMaltreated youth who experienced significant loss were at increased risk for externalizing symptoms, compared to non-bereaved maltreated youth (β = 0.085, p < .05). Individual future orientation (β = 0.103, p < .05) family future orientation (β = −0.120, p < .05), parental monitoring (β = −0.123, p< .01), and neighborhood collective efficacy (β = −0.126, p < .01) each significantly moderated the association between bereavement and externalizing symptoms.ConclusionsThese results have implications for future interventions aimed towards reducing problem behaviors in adolescents with a history of child maltreatment and who experience bereavement.     

Digital Module 16: Longitudinal Data Analysis

In this digital ITEMS module, Dr. Jeffrey Harring and Ms. Tessa Johnson introduce the linear mixed effects (LME) model as a flexible general framework for simultaneously modeling continuous repeated measures data with a scientifically defensible function that adequately summarizes both individual change as well as the average response. The module begins with a nontechnical overview of longitudinal data analyses drawing distinctions with cross-sectional analyses in terms of research questions to be addressed. Nuances of longitudinal designs, timing of measurements, and the real possibility of missing data are then discussed. The three interconnected components of the LME model—(1) a model for individual and mean response profiles, (2) a model to characterize the covariation among the time-specific residuals, and (3) a set of models that summarize the extent that individual coefficients vary—are discussed in the context of the set of activities comprising an analysis. Finally, they demonstrate how to estimate the linear mixed effects model within an open-source environment (R). The digital module contains sample R code, diagnostic quiz questions, hands-on activities in R, curated resources, and a glossary.     

Digital Module 05: Diagnostic Measurement—The G‐DINA Framework https://ncme.elevate.commpartners.com

In this ITEMS module, we introduce the generalized deterministic inputs, noisy “and” gate (G‐DINA) model, which is a general framework for specifying, estimating, and evaluating a wide variety of cognitive diagnosis models. The module contains a nontechnical introduction to diagnostic measurement, an introductory overview of the G‐DINA model, as well as common special cases, and a review of model‐data fit evaluation practices within this framework. We use the flexible GDINA R package, which is available for free within the R environment and provides a user‐friendly graphical interface in addition to the code‐driven layer. The digital module also contains videos of worked examples, solutions to data activity questions, curated resources, a glossary, and quizzes with diagnostic feedback.