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The goal of this study was to define the construct and establish the validity of disciplinary literacy, which has recently gained attention from the implementation of the Common Core State Standards (National Governors Association Center for Best Practices & Council of Chief State School Officers in Common Core State Standards for English language arts & literacy in history/social studies, science, and technical subjects [PDF]. Authors, Washington, DC, 2010). After defining disciplinary literacy in the four core disciplines of English language arts, science, history and social studies, and mathematics, scales were developed and administered to a snowball sample of professionals nationwide, with 857 respondents. The data showed evidence of disciplinary literacy as a multidimensional construct with three related factors: source literacy, analytic literacy, and expressive literacy. Based on EFA and CFA results, we can conclude that there are at least three types of literacy in operation among the four core disciplines. The three factors of literacy varied significantly by the four core disciplines of English/language arts (ELA), science, history and social studies, and mathematics, supporting the notion that each discipline uses literacy uniquely. This is the first study of its kind to attempt to define, quantify, and validate the construct of disciplinary literacy.

The present study examined middle school teachers' perceptions of literacy demands in their disciplines and specific literacy strategies they used to teach their disciplines. The eight participants in this multiple case study included 2 middle school teachers from each of 4 disciplines (i.e., English/language arts, science, social studies, and mathematics) who had completed 6 weeks of online professional development on disciplinary literacy. Data sources comprised 2 classroom observations and 2 semi-structured interviews following observations for each of the 8 teachers, as well as classroom and school artifacts. Qualitative analyses included within-case and cross-case themes. Findings indicated participants used a range of content area literacy and discipline-specific literacy instruction. Based on cross-case analysis, 4 themes emerged from the 4 discipline-based cases: (a) interdisciplinary literacy, (b) power in disciplinary language, (c) pedagogical tensions related to end of grade exams, and (d) individualized access. Two pedagogical tensions emerged from the data: the tension between content area literacy and disciplinary literacy and the tension between disciplinary-based instruction and interdisciplinarity, which permeates the middle school curriculum. Future research should explore how middle school teachers navigate the pedagogical tensions of disciplinary literacy within interdisciplinarity in light of Common Core State Standards and other current policy initiatives.

Disciplinary literacy is gaining momentum as an approach to adolescent literacy. Believing that a key aspect of disciplinary literacy is knowledge construction, the authors introduce a model for relating disciplinary literacy with project-based inquiry. Rather than merely exploring topics during inquiry, students use practices of a discipline to understand claims and evidences and to create new knowledge. The aim is that students will engage in authentic, intellectually challenging work so their products will have value within and outside of school. The model proposes to help teachers create an instructional path for deeper learning within the disciplines.

We propose to investigate the use of subregion Hotelling observers (SRHOs) in conjunction with perceptrons for the computerized classification of suspicious regions in chest radiographs for being nodules requiring follow up. Previously, 239 regions of interest (ROIs), each containing a suspicious lesion with proven classification, were collected. We chose to investigate the use of SRHOs as part of a multilayer classifier to determine the presence of a nodule. Each SRHO incorporates information about signal, background, and noise correlation for classification. For this study, 225 separate Hotelling observers were set up in a grid across each ROI. Each separate observer discriminates an 8 by 8 pixel area. A round robin sampling scheme was used to generate the 225 features, where each feature is the output of the individual observers. These features were then rank ordered by the magnitude of the weights of a perceptron. Once rank ordered, subsets of increasing number of features were selected to be used in another perceptron. This perceptron was trained to minimize mean squared error and the output was a continuous variable representing the likelihood of the region being a nodule. Performance was evaluated by receiver operating characteristic (ROC) analysis and reported as the area under the curve (Az). The classifier was optimized by adding additional features until the Az declined. The optimized subset of observers then were combined using a third perceptron. A subset of 80 features was selected which gave an Az of 0.972. Additionally, at 98.6% sensitivity, the classifier had a specificity of 71.3% and increased the positive predictive value from 60.7% to 84.1 %. Preliminary results suggest that using SRHOs in combination with perceptrons can provide a successful classification scheme for pulmonary nodules. This approach could be incorporated into a larger computer aided detection system for decreasing false positives.

Layer decomposition is a promising method for obtaining accurate densitometric profiles of diseased coronary artery segments. This method decomposes coronary angiographic image sequences into moving densitometric layers undergoing translation, rotation, and scaling. In order to evaluate the accuracy of this technique, we have developed a technique for embedding realistic simulated moving stenotic arteries in real clinical coronary angiograms. We evaluate the accuracy of layer decomposition in two ways. First, we compute tracking errors as the distance between the true and estimated motion of a reference point in the arterial lesion. We find that noise-weighted phase correlation and layered background subtraction are superior to cross correlation and fixed mask subtraction, respectively. Second, we compute the correlation coefficient between the true vessel profile and the raw and processed images in the region of the stenosis. We find that layer decomposition significantly improves the correlation coefficient.

We consider detection of a nodule signal profile in noisy images meant to roughly simulate the statistical properties of tomographic image reconstructions in nuclear medicine. The images have two sources of variability arising from quantum noise from the imaging process and anatomical variability in the ensemble of objects being imaged. Both of these sources of variability are simulated by a stationary Gaussian random process. Sample images from this process are generated by filtering white-noise images. Human-observer performance in several signal-known-exactly detection tasks is evaluated through psychophysical studies by using the two-alternative forced-choice method. The tasks considered investigate parameters of the images that influence both the signal profile and pixel-to-pixel correlations in the images. The effect of low-pass filtering is investigated as an approximation to regularization implemented by image-reconstruction algorithms. The relative magnitudes of the quantum and the anatomical variability are investigated as an approximation to the effects of exposure time. Finally, we study the effect of the anatomical correlations in the form of an anatomical slope as an approximation to the effects of different tissue types. Human-observer performance is compared with the performance of a number of model observers computed directly from the ensemble statistics of the images used in the experiments for the purpose of finding predictive models. The model observers investigated include a number of nonprewhitening observers, the Hotelling observer (which is equivalent to the ideal observer for these studies), and six implementations of channelized-Hotelling observers. The human observers demonstrate large effects across the experimental parameters investigated. In the regularization study, performance exhibits a mild peak at intermediate levels of regularization before degrading at higher levels. The exposure-time study shows that human observers are able to detect ever more subtle lesions at increased exposure times. The anatomical slope study shows that human-observer performance degrades as anatomical variability extends into higher spatial frequencies. Of the observers tested, the channelized-Hotelling observers best capture the features of the human data.

In a recent paper [J. Opt. Soc. Am. A 17, 206 (2000)], a modified detectability index, d'r, was proposed to accommodate correlations between internal responses in multiple-alternative forced-choice (MAFC) experiments. The derivation given in that work pertained only to two-alternative forced choice, although it was shown empirically that the result held for general MAFC tasks when the correlation between responses is constant. Here we present a rigorous derivation that shows that the d'r result generalizes to MAFC tasks in this case.