12 research outputs found

    Examining Patterns in Second Graders’ Use of Virtual Manipulative Mathematics Apps through Heatmap Analysis

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    This study examined 32 second-grade children’s interactions with six virtual manipulative mathematics apps on the iPad using a novel analysis approach called heatmap analysis. Mathematical topics of the six apps focused on understanding skip counting and place value concepts. Children interacted individually with the apps under the guidance of an interviewer during 30-40 minute clinical interviews. The heatmap analysis revealed patterns in children’s performance on the tasks and suggested individual cases for further analysis. For example, clusters of children showed high or low performance during the skip counting sequence. In the high-performing cluster, one child still struggled to monitor the skip counting process. In the low-performing cluster, one child showed growth on learning tasks but struggled on the assessments, which contained a different representation of the mathematical content and involved greater target numbers than in the learning app. There were fewer variations in place value task performance, but application of interaction techniques influenced children’s growth on one learning app. Although some children showed varying performance when encountering challenging mathematics content in the higher levels of one app, other children inefficiently interacted with the app and did not reach the more challenging content

    Computational Statistics (Journal)

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    Reliability of hand diagrams for the epidemiologic case definition of carpal tunnel syndrome

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    INTRODUCTION: The purpose of this study was to evaluate the inter-rater reliability of hand diagrams, which are commonly used in research case definitions of carpal tunnel syndrome (CTS). To evaluate the potential of non-random misclassification of cases, we also studied predictors of rater disagreement as a function of personal and work factors, and of hand symptoms not classic for CTS. METHODS: Participants in a longitudinal study investigating the development of CTS completed repeated self-administered questionnaires. Three experienced clinicians, blind to subjects’ work or personal history, independently rated all hand diagrams on an ordinal scale from 0 to 3. Disagreements between ratings were resolved by consensus. Reliability was measured by the weighted kappa statistic. Logistic regression models evaluated predictors of disagreement. RESULTS: Three hundred and thirty-three subjects completed 494 hand diagrams. Eighty-five percent were completed by self-administered questionnaire and 15% by telephone interview. Weighted kappa values representing agreement among the three raters, were 0.83 (95% CI: 0.78, 0.87) for right hand diagrams and 0.88 (95% CI: 0.83, 0.91) for left hand diagrams. Ratings from hand diagrams obtained by telephone interview produced better agreement. Agreement among raters was not affected by subjects’ personal or work factors. Disagreement among raters was associated with the presence of hand/wrist symptoms other than classic CTS symptoms. CONCLUSIONS: Overall, high levels of agreement were attained by independent raters of hand diagrams. Personal factors did not affect agreement among raters, but presence of non-CTS symptoms seemed to affect results and should be considered in studies focused on diverse populations with heterogeneity of upper extremity symptoms

    Assessing agreement of self-reported and observed physical exposures of the upper extremity

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    Assessment of workplace physical exposures by self-reported questionnaires has logistical advantages in population studies but is subject to exposure misclassification. This study measured agreement between eight self-reported and observer-rated physical exposures to the hands and wrists, and evaluated predictors of inter-method agreement. Workers (n=341) from three occupational categories (clerical/technical, construction, and service) completed self-administered questionnaires and worksite assessments. Analyses compared self-reported and observed ratings using a weighted kappa coefficient. Personal and psychosocial factors, presence of upper extremity symptoms and job type were evaluated as predictors of agreement. Weighted kappa values were substantial for lifting (0.67) and holding vibrating tools (0.61), moderate for forceful grip (0.58) and fair to poor for all other exposures. Upper extremity symptoms did not predict greater disagreement between self-reported and observed exposures. Occupational category was the only significant predictor of inter-method agreement. Self-reported exposures may provide a useful estimate of some work exposures for population studies

    How Design Features in Digital Math Games Support Learning and Mathematics Connections

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    Current research shows that digital games can significantly enhance children’s learning. The purpose of this study was to examine how design features in 12 digital math games influenced children’s learning. The participants in this study were 193 children in Grades 2 through 6 (ages 8-12). During clinical interviews, children in the study completed pre-tests, interacted with digital math games, responded to questions about the digital math games, and completed post-tests. We recorded the interactions using two video perspectives that recorded children’s gameplay and responses to interviewers. We employed mixed methods to analyze the data and identify salient patterns in children’s experiences with the digital math games. The analysis revealed significant gains for 9 of the 12 digital games and most children were aware of the design features in the games. There were eight prominent categories of design features in the video data that supported learning and mathematics connections. Six categories focused on how the design features supported learning in the digital games. These categories included: accuracy feedback, unlimited/multiple attempts, information tutorials and hints, focused constraint, progressive levels, and game efficiency. Two categories were more specific to embodied cognition and action with the mathematics, and focused on how design features promoted mathematics connections. These categories included: linked representations and linked physical actions. The digital games in this study that did not include linked representations and opportunities for linked physical actions as design features did not produce significant gains. These results suggest the key role of mathematics-specific design features in the design of digital math games

    Dynamic graphics in a GIS: a link between ARC/ INFO(Tm) and XGobi

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    This paper describes a link between a Geograph ical Information System GIS ARC INFOTM and an in teractive dynamic graphics program XGobi GISs provide a user with a standard and convenient software for spatial geographical data In particular the GIS ARC INFO is a combination of two systems ARC maintains the spatial in formation of map features and provides tools for spatial anal yses while INFO maintains the thematic or attribute infor mation associated with the map features XGobi is an inter active dynamic graphics program for data visualization in the X Window SystemTM It is designed for the exploration of multivariate data primarily by manipulating and displaying scatterplots in arbitrary dimensions The motivation for the work is to link the dynamic inter active strengths of XGobi for visualizing highdimensional data with the exhaustive map handling tools of ARC INFO speci cally to explore spatial data This paper presents in formation about the technical realization of the link between ARC INFO and XGobi as well as an introductory example of its us

    Eye-Tracking in Practice: A first Analysis of a Study on Human Postures

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    In this article, we present our first results of a study that tries to determine where people are looking when ranking the stability of an actor holding certain postures. A mobile eye-tracker is used to record the original video data of people looking at human postures. Image processing methods are employed to extract statistical information from the video data. The statistical analyses are based on visualization and machine learning approaches

    On theuse of the Advanced Very High Resolution Radiometer for development of prognostic land surfacephenology models

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    Regulation of interannual phenological variability is an important component of climate and ecological models. Prior phenological efforts using the advanced very high resolution radiometer (AVHRR) as a proxy of vegetation dynamics have often simulated spring events only or failed to simulate interannual variability. Our aim is to address these shortcomings and to use the AVHRR to develop prognostic models for interannual land surface phenology and, critically, to test whether or not the developed models are superior to use of climatological phenology values from the AVHRR. Using datasets for the conterminous United States, we first filtered data to select regions and plant functional types for which the best-possible remotely sensed signal could be obtained. We then used a generalized linear model approach to model the relationship between an integrative productivity index and estimates of the start of season (SOS) and end of season (EOS) derived from the AVHRR, yielding models capable of prognostically predicting SOS/EOS events independently of satellite data. Mean absolute errors between the model-predicted and AVHRR-observed SOS/EOS ranged from 5.1 to 20.3 days. SOS errors were uniformly lower than EOS errors. SOS models for the deciduous broadleaf forest and grassland plant functional types produced lower errors than use of the climatological SOS values while all other models produced errors higher than those obtained from the climatological dates. Based on this criterion for success, we suggest that the AVHRR may not be appropriate for further development of prognostic land surface phenology models. However, an intercomparison of phenological dates from an independent spring index model, our model predictions, and the AVHRR observations indicated that interannual predictions from our models may be superior to the satellite data upon which they are based, implying that a further comparison between models based on the AVHRR and newer, superior sensors, should be conducted
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