Search

The apps for drawing are present in our children's life. Nevertheless, little is known about the impact of mobile technology on the freehand drawing educational activity. There are few works which are contextualised within short periods of time, with teachers who are not theirs and, in some cases, outside the children's classroom. In this paper, we are focussed on the use of technology on freehand drawing activity. Thus, we have compared the graphics produced by 4- and 5-year-old children with paper&crayon in comparison with those with tablet-finger. Children made the drawings during a planned free-drawing activity, in their ordinary classrooms, with their teachers and during five sessions. Assessment of drawings has evidenced tablet feasibility for making graphics. Nevertheless, with the passing of time, quality of graphics (tablet-finger vs paper&crayons), are nearly matched, demonstrating the low impact level technology has on this activity. In addition, if drawings are analysed specifically according to ages, results have shown that both groups have to develop adaptation strategies of visual perceptual skills and fine motor skills for the touch screen in order to obtain the same quality in the drawings made on both support types. [ABSTRACT FROM AUTHOR]

Although various academic disciplines use data papers to support effective research practices, data papers are still uncommon in the educational sciences. Main goals of data papers are enhancing transparency regarding research processes and supporting data sharing among researchers and thus, open science. As many educational research projects include personal data often of minors, publishing raw data can be challenging due to privacy regulations and laws (GDPR). The present article aims at exploring how a data paper can contribute to open science and enhancing transparency regarding research and publication processes for educational research projects, often containing personal data that cannot be made openly available in its raw form. To this end, we describe a dataset of a research project on teachers' noticing as basis for their classroom management. As this project includes rich process-tracing recording methods, the dataset is diverse and serves as basis for multiple analyses and publications while containing personal data of teachers and minors. By elaborating on the characteristics of the dataset, its gathering, analysis approaches and sharing preprocessed and anonymized data files, this data paper explores how to contribute to transparency and open science in educational sciences while acting within the boundaries set by privacy regulations and laws. [ABSTRACT FROM AUTHOR]

Appropriate paper-based technology (APT) is used to provide postural support for children with cerebral palsy (CP) in low-resourced settings. This pilot study aimed to evaluate the impact of APT on the children's and families' lives. A convenience sample of children with CP and their families participated. Inclusion was based on the Gross Motor Function Classification System levels IV and V. APT seating or standing frames were provided for six months. A mixed methods impact of APT devices on the children and families included the Family Impact Assistive Technology Scale for Adaptive Seating (FIATS-AS); the Child Engagement in Daily Life (CEDL) questionnaire; and a qualitative assessment from diary/log and semi-structured interviews. Ten children (median 3 years, range 9 months to 7 years). Baseline to follow-up median (IQR) FIATS-AS were: 22.7 (9.3) and 30.3 (10.2), respectively (p=.002). Similarly mean (SD) CEDL scores for "frequency" changed from 30.5 (13.2) to 42.08 (5.96) (p=.021) and children's enjoyment scores from 2.23 (0.93) to 2.91 (0.79) (p=.019). CEDL questionnaire for self-care was not discriminatory; seven families scored zero at both baseline and 6 months. Qualitative interviews revealed three key findings; that APT improved functional ability, involvement/interaction in daily-life situations, and a reduced family burden of care. APT devices used in Kenyan children with non-ambulant CP had a meaningful positive effect on both the children's and their families' lives. Assistive devices are often unobtainable for children with cerebral palsy (CP) in low-income countries. APT is a low cost and sustainable solution to make seating and standing devices for disabled children in Kenya. The regular use of a postural support device enhanced the children's motor skills, ability to function and participate in everyday activities, reduced the burden of care for the families and promoted the children's social interaction. The postural support devices were highly valued and utilised by the children and families in this study. [ABSTRACT FROM AUTHOR]

This study examined the use of lexical bundles in the results and discussion sections of public health research articles (RAs) by comparing the native English writers with Iranian non-native English writers. To this end, four-, five-, and six-word lexical bundles were contrastively investigated in two different sub-corpora i.e. a native English corpus (NEC) and a non-native English corpus (NNEC). The corpus contained 496 985 words, and each sub-corpora included 100 RAs. The RAs were then examined structurally and functionally. The data were analysed both quantitatively, using frequency count and chi-square analyses, and qualitatively through content analysis. Based on the results, from among the lexical bundles, 29 four-word, 17 five-word, and one six-word bundles were identified in the NEC, while 52 four-word, 27 five-word, and five six-word bundles were found in the NNEC. The findings highlight that Iranian non-native English authors employed more four-word, five-word and six-word lexical bundles than native English authors. The descriptive and overall findings also suggested some differences in the two groups' functional and structural patterns of lexical bundles, whereas statistically insignificant differences were identified in the structural patterns of bundles in the groups. These findings lay considerable emphasis on the central part that lexical bundles play in English for academic purposes (EAP) and English for specific purposes (ESP) courses. [ABSTRACT FROM AUTHOR]

Users' experiences in mental health assessment are multifaceted, including their emotional experiences. Yet, studies of mobile apps for psychiatric assessment have centered on diagnostic accuracy and perceived usability, with little consideration of the impact of user emotional experiences. In this study, we focused on users' perceived usability and emotions and compared the user experience of a paper-and-pencil and an app-based collection of mental health screening questionnaires: EarlyDetect. The System Usability Scale (SUS) and modality-directed emotion questionnaires were administered using paper-and-pencil or iPad. Modality was assigned pseudo-randomly on patients' first visit at a referral-based mental health clinic. We found that patients assigned to the iPad app reported a significantly higher SUS score than patients assigned to paper-and-pencil, qualified by a modality-by-gender interaction where modality effects were significant for men but not for women. Moreover, enjoyment was positively linked to perceived usability, whereas boredom, frustration, and anxiety were negatively linked to usability. Our findings illustrate the added value of studying user experience applied to psychiatric assessments, where both emotions and gender-specific user experience should be taken into consideration. We further discuss the implications for psychiatric assessments via app versus traditional data collection. [ABSTRACT FROM AUTHOR]

This paper sought to examine psychological grit, defined as passion and perseverance for long-term goals, and its efficacy in determining postgraduate retention among historically disadvantaged students enrolled at the University of South Africa (UNISA). The Grit-S scale was used to gauge the level of grit among the participants (n = 594) followed by one-year lagged secondary data, which sought to ascertain retention among the sample. Previous performance at an undergraduate level (i.e. passed or passed with distinction) and demographic attributes (i.e. gender, age, ethnicity and home language) were also included in the scale and used as controls. Results from the binary logistic regression revealed that psychological grit is not a significant predictor of retention from one year to the next (β =.02, OR = 1.02, p =.91), nor does it add incremental value when controlling for previous undergraduate performance and demographic attributes (β =.08, OR = 1.09, p =.58). The paper concludes with a discussion on these pertinent results. [ABSTRACT FROM AUTHOR]

Having the ability to reproduce empirical results is foundational to the scientific process. Increasingly, there is an emphasis within the research community to create workflows which are not only reproducible but also replicable in that analytical approaches can be applied to new data. However, a disproportionate number of technical solutions designed to foster reproducibility and replicability have focused on data analysis, particularly within geography. This paper argues for greater attention on a phase of the research process which precedes analysis and is often taken for granted – that of data acquisition. Through code examples using the R Project for Statistical Computing, this paper demonstrates a path toward replicable spatial data acquisition for both secondary and primary data acquisition, with a focus on crowdsourced geographic information. The modular approach demonstrated is flexible in that it allows for straightforward replication but also enables extension to new spatial questions. Such work is valuable because it conserves labor, promotes research provenance, and allows for more robust analyses. [ABSTRACT FROM AUTHOR]

This paper explores the suggestion (Steen, 2023a, 2023b) that most metaphor may be structurally ambiguous between deliberate and non-deliberate meanings, which in turn affords multivalent metaphor use. The paper begins by examining a sample of 56 Metaphor-Related Words in 25 examples of language use from corpus research about metaphor in discourse about cancer and the end of life (Semino et al., 2018). These data are analyzed by means of a new method proposed by Deliberate Metaphor Theory (Steen, 2023a; cf.; Reijnierse et al. 2019). Results show that all metaphors in the sample that are both polysemous and conventional can be given two interpretations, one non-deliberate and one deliberate. This ambiguity is largely corroborated by additional analysis of these same data by Wmatrix. Subsequent inclusion of all other cases from the same chapter in Semino et al. (2018) offers additional support. This finding offers a critical perspective on the idea that metaphor is a strong psychological device for figurative framing in discourse, for the structural ambiguity of most metaphor allows for multivalent metaphor use, where, in fact, most metaphor may typically be comprehended non-metaphorically (Steen, 2008, 2023a, 2023b). The ambiguity of metaphor hence also explains the paradox of metaphor. [ABSTRACT FROM AUTHOR]

AbstractA TeachMeet is an informal gathering arranged by teachers to share and discuss practice with peers in a social setting. This paper focuses on reporting one fundamental finding of an in-depth exploration of TeachMeet, relating to the characteristics of the events; other findings are reported independently. TeachMeet originated in 2006, adopting participant-driven unconference practices and exploiting emergent social media channels and becoming a global phenomenon. This paper reports findings from a sensemaking exploration of TeachMeet events (n. = 15) in which analysis of data from observations highlighted elements most commonly present, which characterise the events. Data collected were analysed using Descriptive Statistics and Interpretative Phenomenological Analysis. This analysis found TeachMeets to be voluntary, open, non-hierarchical events attended by teachers from all levels and sectors, during which the three characteristic elements at play were (i) the catalytic role of the facilitator, (ii) the impact of nanopresentations, and (iii) the Open Space dynamic. The element of connectivity via social media was influential during and between events. We conclude that these elements in combination characterise this novel phenomenon for informal open professional learning among peers, at gatherings convened by and for teachers to share their experiences in the convivial setting of a TeachMeet. [ABSTRACT FROM AUTHOR]

Public participation in local governance is crucial for effective climate action and for ensuring that policies are designed in a way that respects the rights of communities. Policy developments and choices are shaped by the groups that participate, by the ideas that they hold, and by the institutions that enable and constrain their participation. This paper seeks to understand local climate change governance in Ireland by identifying the environmental interests and the ideas of the groups that participate, and by examining how they engage with institutionalised local policymaking processes and with the organisations that represent the officially recognised views of the country's national environmental movement. An analysis of survey data collected from the groups that are members of one of Ireland's Public Participation Networks shows that a majority of groups are small, rural, voluntary, interested in a wide variety of environmental issues and have a pro-ecological worldview. Most groups follow a pro-institutional advocacy strategy at the local level, while only a minority interact with the national environmental movement, mostly limiting their engagement to the acquisition of information. This paper contributes to the literature that examines how interests, ideas, and institutions shape public participation in local climate politics. [ABSTRACT FROM AUTHOR]

Integrating the Internet of Things (IoT) in smart cities can solve rapid urbanization. It will provide better urban services, addressing urban problems that develop because of enhancing urbanization without establishing policies focusing on well-being. The present investigation explores the growing trend of the dynamic publications associated with the advanced technologies integrated into smart city publication productivity using bibliometric analysis. This approach enables the detection of the usage history, the usage scheme, and the research landscape topic in scientific papers on IoT in smart cities. This study included 976 articles from 2013 to 2023. The area of research in smart cities is categorized into six important clusters: (1) IoT application areas in smart cities, (2) IoT infrastructure for smart cities, (3) IoT security and privacy for smart cities, (4) IoT architecture for smart cities, (5) IoT technologies and communication protocol for smart cities, (6) IoT data analysis for smart cities. Moreover, this study reveals that the issues related to new technologies, security, and privacy of IoT to integrate into smart cities would be an interesting topic for future research. [ABSTRACT FROM AUTHOR]

The application of post-occupancy evaluation (POE) to address the quality of built spaces is widely recognized. This paper deals with the artifact 'Como Você Mora? – CVM' (How Do You Live?) – BIM', which incorporates questions from the POE CVM in BIM. The hypothesis raised was that POE data incorporated into BIM assists in understanding and analyzing the data designers obtained, for it provides clearer and more contextualized answers in the information model. The objective of the paper is to demonstrate the potential of incorporating a POE into the BIM information model, with the POE questionnaire CVM as a case study. To achieve the proposed goal, the work steps are based on Design Science Research, and are divided into (1) problem identification, (2) definition of expected results, (3) development, (4) demonstration, (5) evaluation, and (6) communication. In this paper, the first three steps of the method are presented. The contribution is made by the methodological advance in the area of POE over previous research, seeking artifacts that assist the realization of more efficient projects in terms of housing quality assessment. Results show the potential of incorporating CVM POE into BIM, to facilitate data analysis and looking for patterns of responses by project typology, through the color map in floor plans, as well as the possibility of concentrating all project information permanently linked to a single BIM model. This can in turn avoid the loss of information we obtained in the POE. [ABSTRACT FROM AUTHOR]

AbstractModern public transport systems are typically designed by following universal aspirations to predictability and standardisation. In the case of Santiago’s public transport, however, this design philosophy has often translated into concrete, practical struggles for users with more vulnerable corporealities. In analysing the case of a controversial turnstile installed in Santiago’s buses in 2016, this paper draws on video analysis to examine how passengers respond to, and locally deal with, its exclusionary design. Passengers’ interactions with this technology demonstrate how the turnstile is taken up as more than a mere sorting device, to become a matter of concern around mobility (in)justice. A detailed analysis of these interactions – through ethnomethodological analysis of video data – describes how passengers respond to the turnstile’s exclusionary design by deploying diverse embodied practices of care towards other users experiencing trouble with it. Such practices of care align with a grounded, embodied sense of mobility (in)justice as opposed to more abstract understandings of distributive justice. The paper concludes by discussing the potential forpublic transport systems to become more just and inclusive environments designed as infrastructures of care, whereby materialities may not only allow, but support, practices of care among users. [ABSTRACT FROM AUTHOR]

Underlying thematic analysis are a few fundamental human cognitive processes, such as categorizing, prototyping and metaphorical mapping. By unpacking these basic processes of human cognition, this paper hopes to provide a cognitive basis for thematic analysis as a foundational method in data analysis for qualitative research. In particular, it hopes to address the gap between qualitative methodologists' assumption of thematic analysis as a subjective, creative and flexible process and editors/reviewers' expectation that thematic analysis shall be objective, reliable and rigorous. By consciously and purposefully applying these cognitive processes, thematic analysis can be subjective and yet disciplined, creative and yet rigorous, flexible and yet reliable. The ultimate goal of this paper is to demystify, delineate and further demarcate the thematic analysis process for young and novice qualitative researchers. [ABSTRACT FROM AUTHOR]

The conjunctive model of skill map reflects a way to solve the items in a knowledge domain. Currently, a skill map has been transformed into a formal context to construct a knowledge structure. In fact, the conjunctive model of skill map can be regarded as a special case of skill function. In this paper, we consider a way to solve the items in a knowledge domain as a scale. As a result, a skill function can be decomposed into multiple formal contexts, which correspond to a multi-scale context. Based on this, a method for constructing a knowledge structure delineated via competency model by skill function is proposed. In addition, a method for finding minimal skill function is proposed to reduce the complexity. Last but not least, the experimental analysis of five data sets on the UCI Repository shows that the improved method of constructing knowledge structure is effective and feasible and that it is necessary to perform skill reduction on skill function. [ABSTRACT FROM AUTHOR]

In this paper, the authors describe an investigation of Kennesaw State University's inaugural MOOC, a professional development opportunity designed to enhance educator skills in designing blended and online learning environments for their K-12 learners. Additionally, the authors discuss design aspects of the MOOC in regard to learning impact and first steps taken to evaluate the learners' perceptions of the instructional strategies used during the MOOC. The methods included an analysis of quantitative survey data, as well as a qualitative analysis of both open-ended survey questions and discussion forum responses. The findings from the investigation are presented in terms of design factors contributing to the students' learning, as well as the strategies perceived as barriers to their learning. Results of the study indicate a successful MOOC design from the learners' perspective. [ABSTRACT FROM AUTHOR]

Ranked set sampling (RSS) is used as a powerful data collection technique for situations where measuring the study variable requires a costly and/or tedious process while the sampling units can be ranked easily (e.g. osteoporosis research). In this paper, we develop ridge and Liu-type shrinkage estimators under RSS data from multiple observers to handle the collinearity problem in estimating coefficients of linear regression, stochastic restricted regression and logistic regression. Through extensive numerical studies, we show that shrinkage methods with the multi-observer RSS result in more efficient coefficient estimates. The developed methods are finally applied to bone mineral data for analysis of bone disorder status of women aged 50 and older. [ABSTRACT FROM AUTHOR]

Utilising novel ways of knowing, aligned with an ecological approach, the Learning in Development Research Framework (LDRF) has been introduced as a different way to guide research and practice in sport. A central feature of this framework is an appreciation of researcher embeddedness; positioned as an inhabitant who follows along with the unfolding inquiry. This positioning is integral for enriching ones understanding of the relations between socio-cultural constraints and affordances for skill learning within a sports organisation. Moreover, the notion of embeddedness foregrounds the ongoing nature of inquiry when practiced as an art of inquiry. In an effort to extend these ideas, this paper highlights how a phronetic iterative approach to data analysis-synthesis could be undertaken, while ensuring that the researcher remains 'in touch' with a phenomenon, and thus faithful to key tenets of research practiced as an art of inquiry. To illustrate this, we present a 'walk-through' from a recent LDRF study. Rather than focusing on data collection or recorded observations made from afar, this walk-through shows how a researcher, practicing an art of inquiry, can grow knowledge of and with the phenomena, enriching the evolution of practice and performance from within an ecology of relations. [ABSTRACT FROM AUTHOR]

AbstractNonparametric regression suffers from curse of dimensionality, requiring a relatively large sample size for accurate estimation beyond the univariate case. In this paper, we consider a simple method of dimension reduction in nonparametric regression via series estimation, based on the concept of low-rankness which was previously studied in parametric multivariate reduced-rank regression and matrix regression. For d>2 , the low-rank assumption is realized via tensor regression. We establish a faster convergence rate of the estimator in the (approximate) low-rank case. Limitations of the model are also discussed. Through simulation studies and real data analysis, we compare the estimation accuracy of the proposed method with that of existing approaches. The results demonstrate that the proposed method yields estimates with lower RMSE compared to existing methods. [ABSTRACT FROM AUTHOR]

Understanding the mobility of entities in geospatial data is important to many fields, ranging from the social sciences to epidemiology, economics or air traffic control. Visualizing such entities can be challenging as it requires preserving both their explicit properties (spatial trajectories) and their implicit properties (abstract attributes of those trajectories). An existing technique called origin–destination maps preserves both explicit and implicit properties of datasets, using the spatial nesting technique. In this paper, we aim at generalizing this technique beyond an origins-and-destinations dataset (2-attribute datasets), to explore multi-dimensional datasets (N-attribute datasets) with the nesting approach. We present an abstraction framework – we call Gridify – and an interactive open-source tool implementing this framework using several levels of nested maps. We report on several case studies representative of the types of dimensions found in geospatial datasets (quantitative, temporal, discrete, boolean), showing the applicability of this approach to achieve visual exploratory analysis tasks in various application domains. [ABSTRACT FROM AUTHOR]

AbstractFor statistical analysis of network data, the β -model has emerged as a useful tool, thanks to its flexibility in incorporating nodewise heterogeneity and theoretical tractability. To generalize the β -model, this paper proposes the Sparse β -Regression Model (S β RM) that unites two research themes developed recently in modelling homophily and sparsity. In particular, we employ differential heterogeneity that assigns weights only to important nodes and propose penalized likelihood with an ℓ1 penalty for parameter estimation. While our estimation method is closely related to the LASSO method for logistic regression, we develop a new theory emphasizing the use of our model for dealing with a parameter regime that can handle sparse networks usually seen in practice. More interestingly, the resulting inference on the homophily parameter demands no debiasing normally employed in LASSO type estimation. We provide extensive simulation and data analysis to illustrate the use of the model. As a special case of our model, we extend the Erdős-Rényi model by including covariates and develop the associated statistical inference for sparse networks, which may be of independent interest. [ABSTRACT FROM AUTHOR]

The recent explosion in online dissemination of health-related information, and its availability to more and more people around the world, has led to a situation in which both healthcare providers and patients are accepting new roles. This paper examines the transformations toward new roles for healthcare professionals and patients, with a focus on Japan, based on the assumption that one of the driving forces accelerating these changes may be the digitalization of patient peer support. The methods used in this study were: 1) questionnaires and interviews with patients and healthcare providers asking about their participation in peer support and the effectiveness of its implementation; and 2) observations, questionnaires, and interviews with three patient groups about the experience of digitalizing peer support (via implementation of peer support in a virtual reality space). Analysis of the data showed that peer support by patient groups has both challenges and benefits, and that peer support in virtual spaces has certain positive effects. The empowerment of patients through digitalized peer support is transforming the relationship between healthcare providers and patients, changing it from a traditional asymmetrical relationship (in which the healthcare professionals are in a dominant position) to a cooperative relationship on a more equal footing. [ABSTRACT FROM AUTHOR]

Big data streams have garnered significant attention in multiple industries. However, the immense volume and the presence of outliers in high-velocity streaming data pose great challenges to its analysis. To address these concerns, this paper introduces a novel Online Updating Huber Robust Regression algorithm. By efficiently capturing the salient features of new data subsets, a computationally efficient online updating estimator is proposed without the need for storing historical data. Furthermore, by incorporating Huber regression into its framework, the estimator exhibits robustness to heavy-tailed, heterogeneous as well as outlier-contaminated data. Theoretically, the proposed online updating estimator is asymptotically equivalent to an Oracle estimator derived from the entire dataset. Extensive numerical simulations and a real-world data analysis have been conducted to demonstrate the effectiveness and practicality of the proposed method. [ABSTRACT FROM AUTHOR]

The analysis of interval-censored data with informative observation processes has recently attracted much attention and a few methods have been developed. However, all of the existing methods assume that covariate effects are constant and this may not be true sometimes in practice. To address this, in this paper, we propose a varying-coefficient additive hazards model and in the proposed method, frailty variables are used to describe the dependence between the failure time and the informative observation process. For inference, a Bernstein polynomials-based, two-step sieve maximum likelihood method is developed and the proposed method can be easily implemented. Furthermore, the resulting estimators of regression parameters are shown to be consistent and asymptotically normal. An extensive simulation study is conducted and suggests that the proposed approach works well for practical situations. The proposed method is applied to a cardiac allograft vasculopathy (CAV) study that motivated this investigation. [ABSTRACT FROM AUTHOR]

This paper examined phonological processing as reflected in Mandarin word and non-word repetition. Issues related to dementia effects, age effects, and linguistic variables are discussed. Forty-five speakers of Mandarin Chinese in Taiwan took part in this study. Fourteen seniors with Alzheimer's disease (AD), 14 healthy adults, and 17 healthy seniors individually completed a task of word repetition. Scores of accurate repetition were calculated, and error types as well as error frequency were analysed. Linguistic variables, including lexicality, frequency, non-word, and syllable length, were discussed. Major findings were indicative of a significant dementia effect, in which participants with AD were significantly impaired in repeating words with more syllables, specifically 5-syllable non-words of low frequency. Numerous significant age effects were noted. Theoretical implications and directions for future study are discussed. [ABSTRACT FROM AUTHOR]

Increasing numbers of researchers in the field of higher education research are searching for meaning rather than metrics: something in their data that call to them and that make their hearts soar. This paper leans into post-qualitative approaches and attempts to resist methodological arrest, drawing on the disciplinary language of literary fiction to explore how we can make meaning through creative acts of reading. We trace our literary roots across readings from a diverse range of texts and approaches to show how this method could help us reshape and reframe pedagogic challenges within higher education. [ABSTRACT FROM AUTHOR]

Programming is becoming increasingly common in mathematics degrees as it is a desirable skill for new graduates. However, research shows that its use is mostly restricted to computational or modelling tasks. This paper reports a study on students' perceptions of and difficulties with Lean, an interactive theorem prover introduced as part of a transition to proof first-year module. The data consist of first-year university mathematics students' questionnaire responses (n = 99) and sections of 37 semi-structured interviews with students from the same cohort. Findings highlight students' difficulties with syntactic and strategic knowledge, in line with similar research on programming, and how conceptual knowledge is discussed in terms of conceptual-mathematics and conceptual-programming. Moreover, some students share how the experience with Lean changed their perception of mathematics by contributing to the epistemological shift from school to university, which is necessary for students to be successful. However, many students failed to engage with Lean due to its difficult syntax and because they perceived programming to be disconnected from the activity of proving and not worth the time investment needed to become proficient with this tool. We conclude with some reflections on the implications of this study for university teaching and suggestions for future research. [ABSTRACT FROM AUTHOR]

Aim: To assess the knowledge, attitudes and practices of Registered Nurses working in residential aged care facilities pertaining to pain management for residents living with dementia. Background: Sub-optimal pain management continues for people living with dementia in residential aged care. Registered Nurses are the pivotal staff responsible for complex assessment and management of people residing in residential aged care facilities. Design and methods: :This integrative literature review was informed by Whittemore (2005). Searching and screening followed the PRISMA guidelines. Results: Thirteen papers were identified, the major themes identified were gaps in knowledge and skills, uncertainty of assessment, and delays in treatment. Conclusion: Registered Nurses require education on pain management for people living with dementia in residential aged care. Broader issues in residential aged care contribute to the problem and require examination. Research pertaining to Registered Nurses' roles pain management for residents living with dementia is required. [ABSTRACT FROM AUTHOR]

AbstractIn this paper, we investigate the functional partially linear single index models with contaminated functional and real covariates when the functional sample grid is dense. To eliminate the influence of measurement error on the estimations of the proposed models, a two-stage estimation procedure is introduced. In the first stage, we utilize a kernel presmoothing regression to denoise the corrupted functional curves. In the second stage, the fitted functional curves are applied to replace the original ones to obtain the predictor of unknown parameter in parametric component with the attenuation correction method and then we derive the predictor of unknown link function in nonparametric part with kernel method. Meanwhile, in order to improve computational efficiency, functional slice inverse regression method is employed to estimate the functional single index parameter. The asymptotic properties are also stated in this process at the situation of independent and identical distribution sample under some mild conditions. A simulation study and real data analysis are further explored to illustrate the good performance of our methodology. [ABSTRACT FROM AUTHOR]

In survival data analysis, comparison of two hazard rate curves is critically important for evaluating a treatment effect. In many applications, the two hazard curves could potentially cross each other, violating the proportional hazards assumption in the Cox's model. In such cases, the traditional tests like the log-rank test and the Peto-Peto test that were developed based on that assumption would be ineffective. There have been some discussions in the literature on comparison of two potentially crossing hazard curves, based on either parametric modeling or nonparametric testing approaches. However, the assumed models of the existing parametric methods are often difficult to justify in practice. On the other hand, the existing nonparametric tests are usually based on the maximization with respect to an unknown crossing point, leading to complex null distributions for the corresponding test statistics. We suggest a novel method in this paper for comparing two hazard curves based on a nonparametric testing procedure. Its test statistic avoids the maximization mentioned above and consequently has the desirable asymptotic normality property under some regularity conditions. We show that the new method is effective for comparing two potentially crossing hazard curves. [ABSTRACT FROM AUTHOR]

AbstractThe effectiveness of educational interventions has traditionally been evaluated using effect size measures which focus on a single feature of the distribution of the outcomes under intervention and control conditions: a (standardized) mean difference. Recently there has been increased interest in methods which assess the information contained in the full distributions of outcomes under intervention and control, providing measures of separation from these distributions which do not depend on arbitrary cutoffs, hence which are “threshold-free”. We investigate the statistical relationship between several concepts of this type, and discuss how they can be used to estimate alternative effect size metrics as well as their uncertainties in the context of multilevel models as commonly used for the analysis of educational data. A specific aim of this paper is to investigate how the recently proposed “gain index” relates to other measures of separation including the Area under the Curve (AUC) and the overlapping index. A simulation study, using data with an educationally motivated structure, is presented to compare the different methodologies. [ABSTRACT FROM AUTHOR]

AbstractThis paper aims to simulate conditional samples for generalized linear models and to show their use in goodness of fit. The particular case of the natural exponential family with quadratic variance function and categorical covariates is studied. The conditional samples are drawn from the conditional distribution having conditioned on a sufficient statistic. A procedure that uses the Rao-Blackwell estimate for the cumulative distribution function is employed. The performance of the proposed procedure is shown through a simulation study and the analysis of a data set. [ABSTRACT FROM AUTHOR]

The recruitment and use of children by armed groups continue to threaten the effective protection of children. Preventive approaches to child protection, call for robust early warning mechanisms that do not only focus on the recruitment and use of children, but capture the root causes and vulnerabilities of both boys and girls for recruitment. A comprehensive early warning mechanism for prevention requires a gender-sensitive approach. This paper seeks to examine the gender dynamics of the recruitment and use of children by armed groups, and how that can inform a gender sensitive data collection and analysis to improve early warning. [ABSTRACT FROM AUTHOR]

This study outlines an approach that captures the messy landscape of the learning opportunities on which teaching focused academics draw. The Activity Centred Analysis and Design framework was employed to analyse data from a focused ethnographic study of seven TFAs in a research-intensive university. The Activity Centred Analysis and Design framework revealed processes of reconfiguring structures that allow for teaching focused academics to focus on their goals (influencing their peers and being recognized as legitimate academics). This paper offers an avenue for understanding authentic practices of teaching focused academics with broader implications for research into the professional learning of academics. [ABSTRACT FROM AUTHOR]

The growth of the Chinese language in African countries and African students' consequent flocking into Chinese higher education are both emergent phenomena. This partly explains the lack of empirical research on this body of student migrants and their Chinese language learning. This paper applies Watkins' theorisation on pedagogic affect to explore pedagogic practices and students' learning experiences in a vocational college in Southeast China. Through a participant observation stance, journal entry and interview data reveal that the teacher's pedagogy generated and heightened affects, which skilfully aroused students' desire to learn but also the capacity to do so. By engaging with the 'affective turn' in second language acquisition studies, I argue that the affective link developed through pedagogic relationships and the bonds fostered in language learning have powerful potential to contribute to the delivery of language skills and resolve cultural adaptation issues in a positive atmosphere. [ABSTRACT FROM AUTHOR]

In many studies on disease progression, biomarkers are restricted by detection limits, hence informatively missing. Current approaches ignore the problem by just filling in the value of the detection limit for the missing observations for the estimation of the mean and covariance function, which yield inaccurate estimation. Inspired by our recent work [Liu and Houwing-Duistermaat (2022), 'Fast Estimators for the Mean Function for Functional Data with Detection Limits', Stat, e467.] in which novel estimators for mean function for data subject to detection limit are proposed, in this paper, we will propose a novel estimator for the covariance function for sparse and dense data subject to a detection limit. We will derive the asymptotic properties of the estimator. We will compare our method to the standard method, which ignores the detection limit, via simulations. We will illustrate the new approach by analysing biomarker data subject to a detection limit. In contrast to the standard method, our method appeared to provide more accurate estimates of the covariance. Moreover its computation time is small. [ABSTRACT FROM AUTHOR]

Working with approximations is a common practice in physics. This paper presents an exploratory study of student understanding of some of the elementary aspects of approximations encountered in college physics. For this purpose, a questionnaire (a set of 14 multiple-choice questions) was developed to probe how students dealt with these aspects in a variety of contexts. The questionnaire was finalized after a trial of its pilot version on 7 students on the basis of their written scripts and interviews. After content validation by three external experts, the test was administered to a sample of 141 senior undergraduate physics students from a diverse set of colleges and national institutes. Data analysis reveals several significant student pitfalls in the topic related principally to (i) the identification of a dimensionless ratio to characterize an approximation, (ii) the notion of the order of approximation and consistent handling of a problem up to the required order, and (iii) the notion of the order of infinitesimal in calculus-based derivations. The findings are of direct pedagogic relevance. [ABSTRACT FROM AUTHOR]

Fun and social affiliation are good predictors of long-term intention to use game-based interventions including those for motivating physical activity, yet current player matching algorithms are poor at facilitating social connectedness. In this paper, we report on the results of a study investigating how different player traits are associated with interest in social features of an exercise game for improving player experience through better player matching using common and complementary characteristics. Twelve conceptual scenarios were illustrated using storyboards and data was collected from 196 respondents who rated their attitudes and preferences towards gamification elements. Correlational results showed that all scenarios, except for cutting corners, were perceived as persuasive, enjoyable, engaging and are likely to increase future exercise intention for players who score high on Philanthropist- and Socialiser-oriented traits. Results also showed that many players favour the altruistic donation feature. Furthermore, qualitative results underscore that it is the player's partner that matters more than the players' personalities. We conclude with practical recommendations for designing more personalised exercise games that can include more socially engaging game mechanics in the future. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic created global disruption in health professions education and healthcare practice, necessitating an abrupt move to digital delivery. A longitudinal survey was conducted to track the evolution of global responses to the pandemic. During the initial stages, educational and health institutions were forced to adapt quickly without careful consideration of optimal pedagogy, practices, and effectiveness of implemented approaches. In this paper, we report the results of Phase 3 of the global survey that was distributed between November 2021 and February 2022 through InterprofessionalResearch.Global (IPR.Global). The Phase 3 qualitative survey received 27 responses, representing 25 institutions from 13 countries in 6 regions. Using inductive thematic analysis, the data analysis resulted in three emerging themes: Impact of the pandemic on the delivery of interprofessional education and collaborative practice (IPECP); Impact of the pandemic on the healthcare system (team, population/client health, clients); and Sustainability and innovation. This study highlights the evolving nature of health education and collaborative practices in response to the COVID-19 pandemic. IPECP educators need to be resilient and deal with the complexities of face-to-face and digital learning delivery. Preparing for emerging forms of teamwork is essential for new work contexts and optimal health services. [ABSTRACT FROM AUTHOR]

Increasing advancements in building digitization, smart sensing, and metering technologies have allowed large amounts of timeseries data to be collected for monitoring, analyzing, and controlling building systems. However, due to sensor or communication failures, the data collected are often incomplete and poor in quality. Data imputation approaches to replace the missing values, specifically based on either statistical or predictive models have been widely adopted for multivariate datasets in other domains. It is hence of interest to find an effective way to impute timeseries data collected from a building system. In this paper, we evaluate multiple data imputation approaches using data collected from a medium sized building situated in Stockholm, Sweden and a small commercial building from the ASHRAE RP-1312 research project. Sensors with widely varying characteristics from the case study buildings were selected to evaluate the imputation methods. The imputation accuracy and the impact of each chosen imputation method on information entropy, short-term building forecasting model performance, and fault detection strategy were evaluated. Results demonstrate that incorporating time-lagged cross correlations within a k -nearest neighbor ( k NN) model provide the most accurate imputations without affecting the quality of subsequent data analysis. [ABSTRACT FROM AUTHOR]

In this paper, we introduce a new distribution defined on $ \mathbb {Z} $ Z , called the $ {{ZPMOIEP}} $ ZPMOIEP distribution, which can be viewed as a natural extension of the zero-and-one-inflated Poisson ( $ {ZOIP} $ ZOIP ) distribution. It is designed to fit the count data with potentially excess zeros and/or ones, and/or minus ones. We explore its various properties and investigate the estimation of the unknown parameters. Moreover, simulation experiments are carried out to attest to the performance of the estimation. Through the use of a useful data set on football scores, the applicability of the proposed distribution is examined. [ABSTRACT FROM AUTHOR]

With dramatic global expansion of secondary schooling there has been significant research interest in how education is related to future aspirations, with important calls to acknowledge connections within processes of aspiring to young people's social, economic and cultural circumstances. This paper presents findings from thematic analysis of interview, participant observation and classroom observation data from an ethnographic study in two secondary schools in Tanzania. It argues that an important, and often overlooked, aspect of this complex process is the way in which aspirations for the future are connected not only to present realities, but also aspirations in the present. Focusing on students' aspirations relating to 'being a "good" student' and being able to 'soma kwa bidii' or 'study hard', this paper uses the conceptual language of the capability approach to assert the importance of considering aspirations for 'being' in education in conjunction with future aspirations for 'becoming'. [ABSTRACT FROM AUTHOR]

Despite the complexity of thermodynamic models in predicting wax precipitation, they have not shown satisfactory results in the literature. This paper proposes the least-squares support vector machine optimized by the genetic algorithm to forecast wax precipitation based on the mole fractions, specific gravity, and temperature of crude oil samples. The genetic algorithm was used to prevent sticking in local optima in optimizing the parameters of the predictive model. A dataset of 88 experimental wax precipitation samples was used to evaluate the performance of the proposed method. The results revealed that the suggested algorithm could predict wax precipitation with an accuracy of 0.939 and 0.997 before and after sensitivity analysis, respectively. Furthermore, sensitivity analysis improved the Coefficient of Determination, Mean Squared Error, and Root Mean Squared Error from 0.939, 0.768, and 0.877 to 0.997, 0.041, and 0.202, respectively. The results were compared with the results of previous data-driven and mathematical models that showed the outperformance of the proposed method. The contribution of this paper can be summarized as demonstrating the ability of intelligent models to predict wax precipitation without a need for complex thermodynamic models. Also, it was shown that a proper feature selection could improve the model's performance. [ABSTRACT FROM AUTHOR]

In this paper, we apply conformal prediction to time series data. Conformal prediction is a method that produces predictive regions given a confidence level. The regions outputs are always valid under the exchangeability assumption. However, this assumption does not hold for the time series data because there is a link among past, current, and future observations. Consequently, the challenge of applying conformal predictors to the problem of time series data lies in the fact that observations of a time series are dependent and therefore do not meet the exchangeability assumption. This paper aims to present a way of constructing reliable prediction intervals by using conformal predictors in the context of time series. We use the nearest neighbors method based on the fast parameters tuning technique in the weighted nearest neighbors (FPTO–WNN) approach as the underlying algorithm. Data analysis demonstrates the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

The paper deals with the estimation methodology for the α-stable periodic autoregressive (PAR) models. For the classical (Gaussian) PAR time series is cyclostationary systems the periodicity is manifested in the model characteristics. One of the most common characteristics used in this context is the autocovariance function. One of the methods of the PAR model estimation utilizes the Yule-Walker equations that contain the autocovariance function of the given process. However, for the infinite variance version of the PAR model (i.e., α-stable-distributed) it is expected that the autocovariance function is not properly defined. Thus, alternative measures need to be used. In this paper, we present the general idea of the modified Yule-Walker equations for the considered model. It is proposed to replace the classical dependency measure by the dependency measures properly defined for infinite variance models. We demonstrate two possible modifications based on the covariation and fractional lower order covariance. The first approach was recently proposed in the literature while the latter is a novel algorithm. We compare the effectiveness of both estimation methods for the considered model. Finally, the results are compared with the classical Yule-Walker approach. We demonstrate the limitations of the classical method for the considered model. The possible application for real data analysis is demonstrated. [ABSTRACT FROM AUTHOR]

Previous studies have identified a deficit with the higher education (HE) decision-making support offered by further education (FE) colleges, compared with other post-16 providers. However, there has been little research as to why this might be the case. This paper explores this issue by considering the HE choice-making experiences of Level 3 Business and Technology Education Council (BTEC) students and the staff supporting them in an FE college in England. Data are viewed through the theoretical lens of the Theory of Practice Architectures, a framework which illuminates the pre-existing conditions holding the practices of HE choice-making in place. The investigation reveals inconsistent College HE choice support, with a reliance on tutors and local universities that can both enable and constrain the programme. Factors underlying the construction of the programme include the structural parameters of both the BTEC qualification and the College, competing College priorities and the varying relationships the College has with different types of universities. The paper concludes by highlighting the complexity of the tensions and conflicts inherent in FE and making a number of practical recommendations as to the underlying conditions that would need to change in order for FE HE choice support to fulfil its potential. [ABSTRACT FROM AUTHOR]

Colleges are important providers of vocational education and training and in some countries they are the major provider. Although the international literature on colleges has grown considerably in the past two decades, it still consists primarily of qualitative descriptions of college sectors in different countries. Quantitative studies of differences in the activity mix of colleges in different countries could improve knowledge of international variation in the roles of colleges and provide a stronger foundation for study of the sources and consequences of variation in college roles. After reviewing different methodological frameworks for comparative analysis of college activity, the research reported here employs one of these frameworks to analyse differences in the activity mix of colleges in five countries. In addition to finding some noteworthy differences among the five countries, the paper also identified several problems of comparability of college data from different countries. The paper concludes that the development of internationally comparable data on colleges would require leadership by international organisations and agencies and is an undertaking well worth pursuing both for the benefits that it could bring to those whom colleges serve and for its contribution to the advancement of comparative study of vocational education and training. [ABSTRACT FROM AUTHOR]

In medical diagnostic research, it is customary to collect multiple continuous biomarker measures to improve the accuracy of diagnostic tests. A prevalent practice is to combine the measurements of these biomarkers into one single composite score. However, incorporating those biomarker measurements into a single score depends on the combination of methods and may lose vital information needed to make an effective and accurate decision. Furthermore, a diagnostic cut-off is required for such a combined score, and it is difficult to interpret in actual clinical practice. The paper extends the classical biomarkers' accuracy and predictive values from univariate to bivariate markers. Also, we will develop a novel pseudo-measures system to maximize the vital information from multiple biomarkers. We specified these pseudo-and-or classifiers for the true positive rate, true negative rate, false-positive rate, and false-negative rate. We used them to redefine classical measures such as the Youden index, diagnostics odds ratio, likelihood ratios, and predictive values. We provide optimal cut-off point selection based on the modified Youden index with numerical illustrations and real data analysis for this paper's newly developed pseudo measures. [ABSTRACT FROM AUTHOR]

Managing and analysing large qualitative datasets pose a particular challenge for researchers seeking a consistent and rigorous approach to qualitative data analysis. This paper describes and demonstrates the development and adoption of a matrix tool to guide the qualitative data analysis of a large sample (N = 122) of interview data. The paper articulates the theoretical and conceptual underpinnings of the matrix analysis tool and how it was developed and applied in a longitudinal mixed methods out-of-home-care research study. Specific illustrations and examples of data integration and data analysis are provided to demonstrate the benefits and potentials of constructing matrix tools to guide research teams when working with large qualitative data sets alone or in combination with quantitative data sets. [ABSTRACT FROM AUTHOR]