Automated Essay Scoring: A Literature Review

In recent decades, large-scale English language proficiency testing and testing research have seen an increased interest in constructed-response essay-writing items (Aschbacher, 1991; Powers, Burstein, Chodorow, Fowles, & Kukich, 2001; Weigle, 2002). The TOEFL iBT, for example, includes two constructed-response writing tasks, one of which is an integrative task requiring the test-taker to write in response to information delivered both aurally and in written form (Educational Testing Service, n.d.). Similarly, the IELTS academic test requires test-takers to write in response to a question that relates to a chart or graph that the test-taker must read and interpret (International English Language Testing System, n.d.). Theoretical justification for the use of such integrative, constructed-response tasks (i.e., tasks which require the test-taker to draw upon information received through several modalities in support of a communicative function) date back to at least the early 1960’s. Carroll (1961, 1972) argued that tests which measure linguistic knowledge alone fail to predict the knowledge and abilities that score users are most likely to be interested in, i.e., prediction of actual use of language knowledge for communicative purposes in specific contexts

Rangeland reference areas : summary of cooperative project between the Western Australian Department of Agriculture and the Environmental Protection Authority

The development of agriculture in south-western Australia has been characterised by the replacement of deep-rooted, perennial species of native vegetation with shallow-rooted, annual species. Except for the high rainfall areas, the native vegetation was able to intercept and transpire nearly all of the rainfall resulting in low stream flows and recharge to a groundwater system which was typically deep and restricted to the major valleys. The lack of surface or groundwater movement out of inland catchments used large quantities of cyclic salts to become stored in the regolith. Although annual crops and pastures can be high water users, they are poorly adapted to transpire rainfall outside of the growing season

Diagnostic Second Language Assessment in the Classroom

The term diagnosis is familiar, and refers to the identification of disease or disorder in an individual. In the broadest sense, then, diagnostic second language (L2) assessment refers to any L2 assessment practice, whether in the form of a formal written test or informal teacher questioning, that yields diagnostic feedback—information on learner strengths and weaknesses. In low-stakes classroom contexts, where psychometric rigor is sacrificed for the attention and rich intuitions of teachers, informal diagnostic assessment occurs on a regular basis in the form of student questioning, explanation, and the provision of written feedback on quizzes, tests, and written work. Indeed, Huff and Goodman (2007) showed that K-12 science and language arts teachers highly value diagnostic feedback and prefer assessments which yield detailed information that can be used to identify the instructional needs of individual learners. Despite this apparent interest on the part of teachers in the diagnostic function of assessment, Alderson (2005, 2007) points out that diagnostic testing has been largely neglected in the L2 literature. Fundamental questions regarding the proper domain and application of diagnostic testing are unresolved: Must a diagnostic L2 test measure proficiency and be based on a theoretical model of L2 ability, or can diagnostic assessment be equally applied to achievement in a curriculum? Where does the boundary between formative assessment and diagnostic assessment lie? What kinds of feedback, and at what level of detail, are most beneficial to L2 learners

Technological Growth and L2 Construct Definition: Will Applied Linguistics Keep Pace with Language Users?

Chapelle (2003) coined the phrase “tunnel of efficiency” to describe what she considers a truncation of vision on the part of applied linguists who have studied technological innovations in L2 assessment. This nearsightedness, she argues, has led to an overemphasis of research that serves immediate practical considerations, i.e., faster, more efficient delivery and scoring of traditional tests. Underemphasized is the question of how the rapidly advancing availability and widespread use of new technology can or should change L2 constructs. To maintain the relevance of our field and coherently evaluate the validity of L2 assessment use arguments, we must pay attention to these questions

The Use of Mixed Models for the Analysis of Mediated Data with Time-Dependent Predictors

Linear mixed models (LMMs) are frequently used to analyze longitudinal data. Although these models can be used to evaluate mediation, they do not directly model causal pathways. Structural equation models (SEMs) are an alternative technique that allows explicit modeling of mediation. The goal of this paper is to evaluate the performance of LMMs relative to SEMs in the analysis of mediated longitudinal data with time-dependent predictors and mediators. We simulated mediated longitudinal data from an SEM and specified delayed effects of the predictor. A variety of model specifications were assessed, and the LMMs and SEMs were evaluated with respect to bias, coverage probability, power, and Type I error. Models evaluated in the simulation were also applied to data from an observational cohort of HIV-infected individuals. We found that when carefully constructed, the LMM adequately models mediated exposure effects that change over time in the presence of mediation, even when the data arise from an SEM

Estimating Heterogeneous Intra-class Correlation Coefficients in Dyadic Ecological Momentary Assessment

A method is described for estimating and testing predictors for influence on the variance of momentary behaviors in dyadic ecological momentary assessment data. Results show that the method allows intraclass correlations of momentary observations from two members of the same couple to vary by observation-level, individual-level and couple-level predictors

Non-linear mixed models in the analysis of mediated longitudinal data with binary outcomes

<p>Abstract</p> <p>Background</p> <p>Structural equation models (SEMs) provide a general framework for analyzing mediated longitudinal data. However when interest is in the total effect (i.e. direct plus indirect) of a predictor on the binary outcome, alternative statistical techniques such as non-linear mixed models (NLMM) may be preferable, particularly if specific causal pathways are not hypothesized or specialized SEM software is not readily available. The purpose of this paper is to evaluate the performance of the NLMM in a setting where the SEM is presumed optimal.</p> <p>Methods</p> <p>We performed a simulation study to assess the performance of NLMMs relative to SEMs with respect to bias, coverage probability, and power in the analysis of mediated binary longitudinal outcomes. Both logistic and probit models were evaluated. Models were also applied to data from a longitudinal study assessing the impact of alcohol consumption on HIV disease progression.</p> <p>Results</p> <p>For the logistic model, the NLMM adequately estimated the total effect of a repeated predictor on the repeated binary outcome and were similar to the SEM across a variety of scenarios evaluating sample size, effect size, and distributions of direct vs. indirect effects. For the probit model, the NLMM adequately estimated the total effect of the repeated predictor, however, the probit SEM overestimated effects.</p> <p>Conclusions</p> <p>Both logistic and probit NLMMs performed well relative to corresponding SEMs with respect to bias, coverage probability and power. In addition, in the probit setting, the NLMM may produce better estimates of the total effect than the probit SEM, which appeared to overestimate effects.</p

Genome Analysis: Birds of a Feather

This Birds-of-a-Feather session presents the national infrastructure serving genome science, including NCGAS, iPlant, XSEDE, and networks, detailing goals, resources, and projects.This research is supported by NSF Award 1062432 – ABI Development: National Center for Genome Analysis Support (NCGAS).  This research was also supported by a generous grant from the Lilly Endowment, Inc. to the Indiana University Pervasive Technology Institute

Profiling of berries by comprehensive two-dimensional gas chromatography/time-of-flight mass spectrometry (GCxGC/TOF-MS)

poster C149, Proceedings Annual Biomedical Research Conference for Minority Students (ABRCMS 2011), November 9 - 12, 2011, America’s Center, St. Louis, MO, US