Improving IRT parameter estimates with small sample sizes: Evaluating the efficacy of a new data augmentation technique

The 3PL model is a flexible and widely used tool in assessment. However, it suffers from limitations due to its need for large sample sizes. This study introduces and evaluates the efficacy of a new sample size augmentation technique called Duplicate, Erase, and Replace (DupER) Augmentation through a simulation study. Data are augmented using several variations of DupER Augmentation (based on different imputation methodologies, deletion rates, and duplication rates), analyzed in BILOG-MG 3, and results are compared to those obtained from analyzing the raw data. Additional manipulated variables include test length and sample size. Estimates are compared using seven different evaluative criteria. Results are mixed and inconclusive. DupER augmented data tend to result in larger root mean squared errors (RMSEs) and lower correlations between estimates and parameters for both item and ability parameters. However, some DupER variations produce estimates that are much less biased than those obtained from the raw data alone. For one DupER variation, it was found that DupER produced better results for low-ability simulees and worse results for those with high abilities. Findings, limitations, and recommendations for future studies are discussed. Specific recommendations for future studies include the application of Duper Augmentation (1) to empirical data, (2) with additional IRT models, and (3) the analysis of the efficacy of the procedure for different item and ability parameter distributions.

Anti-Americanism in Europe: Theoretical Mechanisms and Empirical Evidence

One of the most popular explanations for post-9/11 anti-Americanism argues that resentment against America and Americans is mainly a function of the US government’s unpopular actions. The present article challenges this interpretation: first, it argues that neither the vitality of the resentment in times when the United States had no influence in the respective parts of the world nor its recent radical manifestations are accounted for in a political reductionist framework. In fact, specific traditions of anti-Americanism have an influence on the negative attitudes observed today, as a comparison between Britain, France, Germany, and Poland reveals. Second, this article suggests an alternative theoretical approach. Anti-Americanism can be explained by two basic mechanisms: it functions as a strategy to project denied and disliked self-concepts onto an external object, and it offers an interpretation frame for complex social processes that allows to reduce cognitive dissonance. Multivariate analyses based on empirical data collected in the Pew surveys of 2002 and 2007 show the fruitfulness of our theoretical approach.

Response-based segmentation using Finite Mixture Partial Least Squares: theoretical foundations and an application to American Customer Satisfaction Index Data

When applying multivariate analysis techniques in information systems and social science disciplines, such as management information systems (MIS) and marketing, the assumption that the empirical data originate from a single homogeneous population is often unrealistic. When applying a causal modeling approach, such as partial least squares (PLS) path modeling, segmentation is a key issue in coping with the problem of heterogeneity in estimated cause-and-effect relationships. This chapter presents a new PLS path modeling approach which classifies units on the basis of the heterogeneity of the estimates in the inner model. If unobserved heterogeneity significantly affects the estimated path model relationships on the aggregate data level, the methodology will allow homogenous groups of observations to be created that exhibit distinctive path model estimates. The approach will, thus, provide differentiated analytical outcomes that permit more precise interpretations of each segment formed. An application on a large data set in an example of the American customer satisfaction index (ACSI) substantiates the methodology’s effectiveness in evaluating PLS path modeling results.

A comparison of microphone and speech recognition engine efficacy for mobile data entry

The research presented in this paper is part of an ongoing investigation into how best to incorporate speech-based input within mobile data collection applications. In our previous work [1], we evaluated the ability of a single speech recognition engine to support accurate, mobile, speech-based data input. Here, we build on our previous research to compare the achievable speaker-independent accuracy rates of a variety of speech recognition engines; we also consider the relative effectiveness of different speech recognition engine and microphone pairings in terms of their ability to support accurate text entry under realistic mobile conditions of use. Our intent is to provide some initial empirical data derived from mobile, user-based evaluations to support technological decisions faced by developers of mobile applications that would benefit from, or require, speech-based data entry facilities.

A comparison of microphone and speech recognition engine efficacy for mobile data entry

The research presented in this paper is part of an ongoing investigation into how best to incorporate speech-based input within mobile data collection applications. In our previous work [1], we evaluated the ability of a single speech recognition engine to support accurate, mobile, speech-based data input. Here, we build on our previous research to compare the achievable speaker-independent accuracy rates of a variety of speech recognition engines; we also consider the relative effectiveness of different speech recognition engine and microphone pairings in terms of their ability to support accurate text entry under realistic mobile conditions of use. Our intent is to provide some initial empirical data derived from mobile, user-based evaluations to support technological decisions faced by developers of mobile applications that would benefit from, or require, speech-based data entry facilities.

Biogeochemical data from terrestrial and aquatic ecosystems in a periglacial catchment, West Greenland

Global warming is expected to be most pronounced in the Arctic where permafrost thaw and release of old carbon may provide an important feedback mechanism to the climate system. To better understand and predict climate effects and feedbacks on the cycling of elements within and between ecosystems in northern latitude landscapes, a thorough understanding of the processes related to transport and cycling of elements is required. A fundamental requirement to reach a better process understanding is to have access to high-quality empirical data on chemical concentrations and biotic properties for a wide range of ecosystem domains and functional units (abiotic and biotic pools). The aim of this study is therefore to make one of the most extensive field data sets from a periglacial catchment readily available that can be used both to describe present-day periglacial processes and to improve predictions of the future. Here we present the sampling and analytical methods, field and laboratory equipment and the resulting biogeochemical data from a state-of-the-art whole-ecosystem investigation of the terrestrial and aquatic parts of a lake catchment in the Kangerlussuaq region, West Greenland. This data set allows for the calculation of whole-ecosystem mass balance budgets for a long list of elements, including carbon, nutrients and major and trace metals.

Climbing Up the Leaderboard: An Empirical Study of Applying Gamification Techniques to a Computer Programming Class

Conventional taught learning practices often experience difficulties in keeping students motivated and engaged. Video games, however, are very successful at sustaining high levels of motivation and engagement through a set of tasks for hours without apparent loss of focus. In addition, gamers solve complex problems within a gaming environment without feeling fatigue or frustration, as they would typically do with a comparable learning task. Based on this notion, the academic community is keen on exploring methods that can deliver deep learner engagement and has shown increased interest in adopting gamification – the integration of gaming elements, mechanics, and frameworks into non-game situations and scenarios – as a means to increase student engagement and improve information retention. Its effectiveness when applied to education has been debatable though, as attempts have generally been restricted to one-dimensional approaches such as transposing a trivial reward system onto existing teaching materials and/or assessments. Nevertheless, a gamified, multi-dimensional, problem-based learning approach can yield improved results even when applied to a very complex and traditionally dry task like the teaching of computer programming, as shown in this paper. The presented quasi-experimental study used a combination of instructor feedback, real time sequence of scored quizzes, and live coding to deliver a fully interactive learning experience. More specifically, the “Kahoot!” Classroom Response System (CRS), the classroom version of the TV game show “Who Wants To Be A Millionaire?”, and Codecademy’s interactive platform formed the basis for a learning model which was applied to an entry-level Python programming course. Students were thus allowed to experience multiple interlocking methods similar to those commonly found in a top quality game experience. To assess gamification’s impact on learning, empirical data from the gamified group were compared to those from a control group who was taught through a traditional learning approach, similar to the one which had been used during previous cohorts. Despite this being a relatively small-scale study, the results and findings for a number of key metrics, including attendance, downloading of course material, and final grades, were encouraging and proved that the gamified approach was motivating and enriching for both students and instructors.

Optimal choice of electoral preference data

Electoral researchers are so much accustomed to analyzing the choice of the single most preferred party as the left-hand side variable of their models of electoral behavior that they often ignore revealed preference data. Drawing on random utility theory, their models predict electoral behavior at the extensive margin of choice. Since the seminal work of Luce and others on individual choice behavior, however, many social science disciplines (consumer research, labor market research, travel demand, etc.) have extended their inventory of observed preference data with, for instance, multiple paired comparisons, complete or incomplete rankings, and multiple ratings. Eliciting (voter) preferences using these procedures and applying appropriate choice models is known to considerably increase the efficiency of estimates of causal factors in models of (electoral) behavior. In this paper, we demonstrate the efficiency gain when adding additional preference information to first preferences, up to full ranking data. We do so for multi-party systems of different sizes. We use simulation studies as well as empirical data from the 1972 German election study. Comparing the practical considerations for using ranking and single preference data results in suggestions for choice of measurement instruments in different multi-candidate and multi-party settings.

Research Monograph: The role of community and lifestyle in the making of a knowledge city

Our brief is to investigate the role of community and lifestyle in the making of a globally successful knowledge city region. Our approach is essentially pragmatic. We start by broadly examining knowledge-based urban development from a number of different perspectives. The first view is historical. In this context knowledge work and knowledge workers are seen as vital parts of a new emergent mode of production reliant on the continual production of abstract knowledge. We briefly develop this perspective to encompass the work of Richard Florida who has, notedly, claimed: “Wherever talent goes, innovation, creativity, and economic growth are sure to follow.” Our next perspective examines concepts of knowledge and modes of its production to discover knowledge is not an unchanging object but a human activity that changes in form and content through history. The suggestion emerges that not only is the production of contemporary ‘knowledge’ organised in a specific (and new) manner but also the output of this networked production is a particular type of knowledge (i.e. techné). The third perspective locates knowledge production and its workers in the contemporary urban context. As such, it co-ordinates the knowledge city in the increasingly global structure of cities and develops a typology of different groups of knowledge workers in their preferred urban environment(s). We see emerging here a distinctive geography of knowledge production. It is an urban phenomenon. There is, in short, something about the nature of cities that knowledge workers find particularly attractive. In the next, essentially anthropological, perspective we start to explore the needs and desires of the individual knowledge worker. Beyond the needs basic to any modern human household an attempt is made to deduce, from a base understanding of knowledge work as mental labour, the compensatory cultural needs of the knowledge worker when not at work - and the expression of these needs in the urban fabric. Our final perspective consists of two case studies. In a review of the experiences of Austin, Texas and Singapore’s one-north precinct we collect empirical data on, respectively, a knowledge city that has sustained itself for over 50 years and an urban precinct newly launched into the global market for knowledge work and knowledge workers. Interwoven The Role of Community and Lifestyle in the Making of a Knowledge City Urban Research Program 8 through all perspectives, in the form of apposite citation, is that of ‘expert opinion’ gathered in a rudimentary poll of academic and industry sources. This opinion appears in text boxes while details of the survey can be found in Appendix A. In the conclusion of the report we interpret the wide range of evidence gathered above in a policy frame. It is our hope this report will leave the reader with a clearer picture of the decisive organisational, infrastructural, aesthetic and social dimensions of a knowledge precinct.

Can governments use their construction contracts to improve training outcomes?

This paper explores the likely efficacy of government agencies using their contracting relationships with private firms to affect training outcomes in the construction industry. Specifically, it reports on the results of a study of two training policies of theWestern Australian government. Empirical data is drawn from the government’s Tender Registration System between 1997 and 2006. The main finding of the quantitative analysis is that in the absence of strong industry commitment to policy objectives, the contracting approach is likely to result in high levels of avoidance activity and generate very few benefits. The results of a qualitative investigation also support these findings.

Compliance in peritoneal dialysis : a qualitative study of renal nurses

End-stage renal failure is a life-threatening condition, often treated with home-based peritoneal dialysis (PD). PD is a demanding regimen, and the patients who practise it must make numerous lifestyle changes and learn complicated biomedical techniques. In our experience, the renal nurses who provide mostPDeducation frequently express concerns that patient compliance with their teaching is poor. These concerns are mirrored in the renal literature. It has been argued that the perceived failure of health professionals to improve compliance rates with PD regimens is because ‘compliance’ itself has never been adequately conceptualized or defined; thus, it is difficult to operationalize and quantify. This paper examines how a group of Australian renal nurses construct patient compliance with PD therapy. These empirical data illuminate how PD compliance operates in one practice setting; how it is characterized by multiple and often competing energies; and how ultimately it might be pointless to try to tame ‘compliance’ through rigid definitions and measurement, or to rigidly enforce it in PD patients. The energies involved are too fractious and might be better spent, as many of the more experienced nurses in this study argue, in augmenting the energies that do work well together to improve patient outcomes.

Changing assessment practices : the case for online moderation

Online moderation meetings have the potential to support the collaborative professional development of teachers, and the formation of a common understanding of what denotes quality in student work in a standards based assessment system. In doing so systemic calls for consistency across education systems are also being met. In this paper a case for employing online moderation meetings is developed through recourse to the demands of learning in the twenty-first century and the place of assessment within those discourses. It is argued that empirical data is needed on the efficacy of online moderation meetings to guide future practice as the use of information and communication technologies increases in education systems. Online moderation is one way of gathering teachers across vast distances to share their understandings and develop common meanings of assessment. While it is suggested that online moderation is one possible procedure to meet systemic requirements and support teachers’ professional collaboration, the implementation of such a system also introduces new challenges for schools and teachers. Meeting online to discuss professional understandings is a new way of operating for teachers and involves technology that has not yet been fully utilised within education departments. Issues such as the types of interactions that are afforded within such an environment, as well as technical operating problems that occur when using technology impact on the employment of online meetings. Online moderation meetings while potentially solving the issue of developing common understandings across an entire department also pose new issues to be resolved. There is a need for research into the efficacy of online moderation meetings so that future policy decisions may be based on sound empirical data. It is imperative that as new ways of knowing and acting are incorporated into school curriculum and pedagogy, assessment practices are also aligned. Online moderation meetings can support such practices by enabling teachers to communicate with a wider and more diverse group of teachers to establish common understandings.

How useful is expert opinion for predicting the distribution of a species within and beyond the region of expertise? A case study using brush-tailed rock-wallabiesPetrogale penicillata

1. Species' distribution modelling relies on adequate data sets to build reliable statistical models with high predictive ability. However, the money spent collecting empirical data might be better spent on management. A less expensive source of species' distribution information is expert opinion. This study evaluates expert knowledge and its source. In particular, we determine whether models built on expert knowledge apply over multiple regions or only within the region where the knowledge was derived. 2. The case study focuses on the distribution of the brush-tailed rock-wallaby Petrogale penicillata in eastern Australia. We brought together from two biogeographically different regions substantial and well-designed field data and knowledge from nine experts. We used a novel elicitation tool within a geographical information system to systematically collect expert opinions. The tool utilized an indirect approach to elicitation, asking experts simpler questions about observable rather than abstract quantities, with measures in place to identify uncertainty and offer feedback. Bayesian analysis was used to combine field data and expert knowledge in each region to determine: (i) how expert opinion affected models based on field data and (ii) how similar expert-informed models were within regions and across regions. 3. The elicitation tool effectively captured the experts' opinions and their uncertainties. Experts were comfortable with the map-based elicitation approach used, especially with graphical feedback. Experts tended to predict lower values of species occurrence compared with field data. 4. Across experts, consensus on effect sizes occurred for several habitat variables. Expert opinion generally influenced predictions from field data. However, south-east Queensland and north-east New South Wales experts had different opinions on the influence of elevation and geology, with these differences attributable to geological differences between these regions. 5. Synthesis and applications. When formulated as priors in Bayesian analysis, expert opinion is useful for modifying or strengthening patterns exhibited by empirical data sets that are limited in size or scope. Nevertheless, the ability of an expert to extrapolate beyond their region of knowledge may be poor. Hence there is significant merit in obtaining information from local experts when compiling species' distribution models across several regions.

Elicitator : an expert elicitation tool for regression in ecology

Expert elicitation is the process of retrieving and quantifying expert knowledge in a particular domain. Such information is of particular value when the empirical data is expensive, limited, or unreliable. This paper describes a new software tool, called Elicitator, which assists in quantifying expert knowledge in a form suitable for use as a prior model in Bayesian regression. Potential environmental domains for applying this elicitation tool include habitat modeling, assessing detectability or eradication, ecological condition assessments, risk analysis, and quantifying inputs to complex models of ecological processes. The tool has been developed to be user-friendly, extensible, and facilitate consistent and repeatable elicitation of expert knowledge across these various domains. We demonstrate its application to elicitation for logistic regression in a geographically based ecological context. The underlying statistical methodology is also novel, utilizing an indirect elicitation approach to target expert knowledge on a case-by-case basis. For several elicitation sites (or cases), experts are asked simply to quantify their estimated ecological response (e.g. probability of presence), and its range of plausible values, after inspecting (habitat) covariates via GIS.

A model of teacher professional development based on the principles of lesson study

The researcher’s professional role as an Education Officer was the impetus for this study. Designing and implementing professional development activities is a significant component of the researcher’s position description and as a result of reflection and feedback from participants and colleagues, the creation of a more effective model of professional development became the focus for this study. Few studies have examined all three links between the purposes of professional development that is, increasing teacher knowledge, improving teacher practice, and improving student outcomes. This study is significant in that it investigates the nature of the growth of teachers who participated in a model of professional development which was based upon the principles of Lesson Study. The research provides qualitative and empirical data to establish some links between teacher knowledge, teacher practice, and student learning outcomes. Teacher knowledge in this study refers to mathematics content knowledge as well as pedagogical-content knowledge. The outcomes for students include achievement outcomes, attitudinal outcomes, and behavioural outcomes. As the study was conducted at one school-site, existence proof research was the focus of the methodology and data collection. Developing over the 2007 school year, with five teacher-participants and approximately 160 students from Year Levels 6 to 9, the Lesson Study-principled model of professional development provided the teacher-participants with on-site, on-going, and reflective learning based on their classroom environment. The focus area for the professional development was strategising the engagement with and solution of worded mathematics problems. A design experiment was used to develop the professional development as an intervention of prevailing teacher practice for which data were collected prior to and after the period of intervention. A model of teacher change was developed as an underpinning framework for the development of the study, and was useful in making decisions about data collection and analyses. Data sources consisted of questionnaires, pre-tests and post-tests, interviews, and researcher observations and field notes. The data clearly showed that: content knowledge and pedagogical-content knowledge were increased among the teacher-participants; teacher practice changed in a positive manner; and that a majority of students demonstrated improved learning outcomes. The positive changes to teacher practice are described in this study as the demonstrated use of mixed pedagogical practices rather than a polarisation to either traditional pedagogical practices or contemporary pedagogical practices. The improvement in student learning outcomes was most significant as improved achievement outcomes as indicated by the comparison of pre-test and post-test scores. The effectiveness of the Lesson Study-principled model of professional development used in this study was evaluated using Guskey’s (2005) Five Levels of Professional Development Evaluation.