Matching Items (22)

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Assessing Working Memory in Children: The Comprehensive Assessment Battery for Children – Working Memory (CABC-WM)

Description

Working memory predicts a significant amount of variance for a variety of cognitive tasks, including speaking, reading, and writing. However, few tools are available to assess working memory in children.

Working memory predicts a significant amount of variance for a variety of cognitive tasks, including speaking, reading, and writing. However, few tools are available to assess working memory in children. We present an innovative, computer-based battery that comprehensively assesses different components of working memory in school-age children.

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Agent

Created

Date Created
  • 2017-06-12

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Relationships among goals and flirting: a recall study

Description

The relationships between goals and specific flirting behaviors were investigated in a college population. Research questions and hypotheses were guided by Dillard's (1990) Goals-Plans-Action (GPA) model of interpersonal influence, which

The relationships between goals and specific flirting behaviors were investigated in a college population. Research questions and hypotheses were guided by Dillard's (1990) Goals-Plans-Action (GPA) model of interpersonal influence, which states that goals lead to planning processes, which, in turn, produce behavior. Six hundred and eighty-five undergraduates at a large southwestern university participated in an online survey assessing their behaviors in their most recent flirting interactions, their goals for that interaction, as well as measures designed to assess planning, the importance of the goal, and the number of goals present for the interaction. Results indicate that goals relate to the use of some, but not all behaviors, and that a flirting script may exist. Furthermore, planning, importance, and number of goals were all found to relate to the reporting of specific flirting behaviors. Sex differences were found as well, such that men reported using more forward and direct behaviors, while women reported using more facial expressions, self-touch, and laughing; men also reported flirting for sexual reasons more than women, and women reported flirting for more fun reasons that men. Overall, this study confirms the utility of the GPA framework for understanding the relationship between goals and flirting behavior, and suggests several avenues for future research.

Contributors

Agent

Created

Date Created
  • 2014

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Maximizing the benefits of collaborative learning in the college classroom

Description

This study tested the effects of two kinds of cognitive, domain-based preparation tasks on learning outcomes after engaging in a collaborative activity with a partner. The collaborative learning method of

This study tested the effects of two kinds of cognitive, domain-based preparation tasks on learning outcomes after engaging in a collaborative activity with a partner. The collaborative learning method of interest was termed "preparing-to-interact," and is supported in theory by the Preparation for Future Learning (PFL) paradigm and the Interactive-Constructive-Active-Passive (ICAP) framework. The current work combined these two cognitive-based approaches to design collaborative learning activities that can serve as alternatives to existing methods, which carry limitations and challenges. The "preparing-to-interact" method avoids the need for training students in specific collaboration skills or guiding/scripting their dialogic behaviors, while providing the opportunity for students to acquire the necessary prior knowledge for maximizing their discussions towards learning. The study used a 2x2 experimental design, investigating the factors of Preparation (No Prep and Prep) and Type of Activity (Active and Constructive) on deep and shallow learning. The sample was community college students in introductory psychology classes; the domain tested was "memory," in particular, concepts related to the process of remembering/forgetting information. Results showed that Preparation was a significant factor affecting deep learning, while shallow learning was not affected differently by the interventions. Essentially, equalizing time-on-task and content across all conditions, time spent individually preparing by working on the task alone and then discussing the content with a partner produced deeper learning than engaging in the task jointly for the duration of the learning period. Type of Task was not a significant factor in learning outcomes, however, exploratory analyses showed evidence of Constructive-type behaviors leading to deeper learning of the content. Additionally, a novel method of multilevel analysis (MLA) was used to examine the data to account for the dependency between partners within dyads. This work showed that "preparing-to-interact" is a way to maximize the benefits of collaborative learning. When students are first cognitively prepared, they seem to make the most efficient use of discussion towards learning, engage more deeply in the content during learning, leading to deeper knowledge of the content. Additionally, in using MLA to account for subject nonindependency, this work introduces new questions about the validity of statistical analyses for dyadic data.

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Agent

Created

Date Created
  • 2013

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The Impact of Varying the Number of Measurement Invariance Constraints on the Assessment of Between-Group Differences of Latent Means

Description

Structural equation modeling is potentially useful for assessing mean differences between groups on latent variables (i.e., factors). However, to evaluate these differences accurately, the parameters of the indicators of these

Structural equation modeling is potentially useful for assessing mean differences between groups on latent variables (i.e., factors). However, to evaluate these differences accurately, the parameters of the indicators of these latent variables must be specified correctly. The focus of the current research is on the specification of between-group equality constraints on the loadings and intercepts of indicators. These equality constraints are referred to as invariance constraints. Previous simulation studies in this area focused on fitting a particular model to data that were generated to have various levels and patterns of non-invariance. Results from these studies were interpreted from a viewpoint of assumption violation rather than model misspecification. In contrast, the current study investigated analysis models with varying number of invariance constraints given data that were generated based on a model with indicators that were invariant, partially invariant, or non-invariant. More broadly, the current simulation study was conducted to examine the effect of correctly or incorrectly imposing invariance constraints as well as correctly or incorrectly not imposing invariance constraints on the assessment of factor mean differences. The results indicated that different types of analysis models yield different results in terms of Type I error rates, power, bias in estimation of factor mean difference, and model fit. Benefits and risks are associated with imposing or reducing invariance constraints on models. In addition, model fit or lack of fit can lead to wrong decisions concerning invariance constraints.

Contributors

Agent

Created

Date Created
  • 2014

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Executive function in preschoolers with primary language impairment

Description

Research suggests that some children with primary language impairment (PLI)

have difficulty with certain aspects of executive function; however, most studies examining executive function have been conducted using tasks that require

Research suggests that some children with primary language impairment (PLI)

have difficulty with certain aspects of executive function; however, most studies examining executive function have been conducted using tasks that require children to use language to complete the task. As a result, it is unclear whether poor performance on executive function tasks was due to language impairment, to executive function deficits, or both. The purpose of this study is to evaluate whether preschoolers with PLI have deficits in executive function by comprehensively examining inhibition, updating, and mental set shifting using tasks that do and do not required language to complete the tasks.

Twenty-two four and five-year-old preschoolers with PLI and 30 age-matched preschoolers with typical development (TD) completed two sets of computerized executive function tasks that measured inhibition, updating, and mental set shifting. The first set of tasks were language based and the second were visually-based. This permitted us to test the hypothesis that poor performance on executive function tasks results from poor executive function rather than language impairment. A series of one-way analyses of covariance (ANCOVAs) were completed to test whether there was a significant between-group difference on each task after controlling for attention scale scores. In each analysis the between-group factor was group and the covariate was attention scale scores.

Results showed that preschoolers with PLI showed difficulties on a broad range of linguistic and visual executive function tasks even with scores on an attention measure covaried. Executive function deficits were found for linguistic inhibition, linguistic and visual updating, and linguistic and visual mental set shifting. Overall, findings add to evidence showing that the executive functioning deficits of children with PLI is not limited to the language domain, but is more general in nature. Implications for early assessment and intervention will be discussed.

Contributors

Agent

Created

Date Created
  • 2015

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The impact of partial measurement invariance on between-group comparisons of latent means for a second-order factor

Description

A simulation study was conducted to explore the influence of partial loading invariance and partial intercept invariance on the latent mean comparison of the second-order factor within a higher-order confirmatory

A simulation study was conducted to explore the influence of partial loading invariance and partial intercept invariance on the latent mean comparison of the second-order factor within a higher-order confirmatory factor analysis (CFA) model. Noninvariant loadings or intercepts were generated to be at one of the two levels or both levels for a second-order CFA model. The numbers and directions of differences in noninvariant loadings or intercepts were also manipulated, along with total sample size and effect size of the second-order factor mean difference. Data were analyzed using correct and incorrect specifications of noninvariant loadings and intercepts. Results summarized across the 5,000 replications in each condition included Type I error rates and powers for the chi-square difference test and the Wald test of the second-order factor mean difference, estimation bias and efficiency for this latent mean difference, and means of the standardized root mean square residual (SRMR) and the root mean square error of approximation (RMSEA).

When the model was correctly specified, no obvious estimation bias was observed; when the model was misspecified by constraining noninvariant loadings or intercepts to be equal, the latent mean difference was overestimated if the direction of the difference in loadings or intercepts of was consistent with the direction of the latent mean difference, and vice versa. Increasing the number of noninvariant loadings or intercepts resulted in larger estimation bias if these noninvariant loadings or intercepts were constrained to be equal. Power to detect the latent mean difference was influenced by estimation bias and the estimated variance of the difference in the second-order factor mean, in addition to sample size and effect size. Constraining more parameters to be equal between groups—even when unequal in the population—led to a decrease in the variance of the estimated latent mean difference, which increased power somewhat. Finally, RMSEA was very sensitive for detecting misspecification due to improper equality constraints in all conditions in the current scenario, including the nonzero latent mean difference, but SRMR did not increase as expected when noninvariant parameters were constrained.

Contributors

Agent

Created

Date Created
  • 2016

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Nature or nurture?: a characterization of the knowledge and practices of in- and out-of-field beginning secondary physics teachers

Description

Previous studies have shown that adequate content knowledge is a necessary, but not sufficient, requirement for affective teaching. While legislation requests teachers to be "highly qualified" in a subject area,

Previous studies have shown that adequate content knowledge is a necessary, but not sufficient, requirement for affective teaching. While legislation requests teachers to be "highly qualified" in a subject area, such as physics, many teachers are frequently asked to teach in an area when they are not certified through a teaching license to do so. This study uses mixed methods to examine the knowledge of beginning physics teachers. Through semi-structured interviews, classroom observations, and concept maps, the pedagogical content knowledge, subject matter knowledge, and practices of three groups of beginning secondary physics teachers were explored. Data were analyzed qualitatively using cases and quantitatively using descriptive statistics and t-tests, the results of which were combined during the interpretation phase of the research process. The study indicated that, over the first two years of teaching, the in-field group of teachers showed stronger physics content knowledge, a consideration for student difficulties with physics topics, and a positive shift in pedagogical content knowledge impacted by working with students, as compared to the rest of the teachers in the study. This research has implications in the development of secondary physics teachers and in the field of physics education research. Specifically, this research has implications in the physics content support for beginning secondary science teachers, the novice/expert research in physics education research, and the pedagogical preparation of undergraduate students, graduate students, and faculty in physics.

Contributors

Agent

Created

Date Created
  • 2010

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Posterior predictive model checking in Bayesian networks

Description

This simulation study compared the utility of various discrepancy measures within a posterior predictive model checking (PPMC) framework for detecting different types of data-model misfit in multidimensional Bayesian network (BN)

This simulation study compared the utility of various discrepancy measures within a posterior predictive model checking (PPMC) framework for detecting different types of data-model misfit in multidimensional Bayesian network (BN) models. The investigated conditions were motivated by an applied research program utilizing an operational complex performance assessment within a digital-simulation educational context grounded in theories of cognition and learning. BN models were manipulated along two factors: latent variable dependency structure and number of latent classes. Distributions of posterior predicted p-values (PPP-values) served as the primary outcome measure and were summarized in graphical presentations, by median values across replications, and by proportions of replications in which the PPP-values were extreme. An effect size measure for PPMC was introduced as a supplemental numerical summary to the PPP-value. Consistent with previous PPMC research, all investigated fit functions tended to perform conservatively, but Standardized Generalized Dimensionality Discrepancy Measure (SGDDM), Yen's Q3, and Hierarchy Consistency Index (HCI) only mildly so. Adequate power to detect at least some types of misfit was demonstrated by SGDDM, Q3, HCI, Item Consistency Index (ICI), and to a lesser extent Deviance, while proportion correct (PC), a chi-square-type item-fit measure, Ranked Probability Score (RPS), and Good's Logarithmic Scale (GLS) were powerless across all investigated factors. Bivariate SGDDM and Q3 were found to provide powerful and detailed feedback for all investigated types of misfit.

Contributors

Agent

Created

Date Created
  • 2014

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Assessing Postsecondary Students' Orientation toward Lifelong Learning

Description

Institutions of higher education often tout that they are developing students to become lifelong learners. Evaluative efforts in this area have been presumably hindered by the lack of a uniform

Institutions of higher education often tout that they are developing students to become lifelong learners. Evaluative efforts in this area have been presumably hindered by the lack of a uniform conceptualization of lifelong learning. Lifelong learning has been defined from institutional, economic, socio-cultural, and pedagogical perspectives, among others. This study presents the existing operational definitions and theories of lifelong learning in the context of higher education and synthesizes them to propose a unified model of college students' orientation toward lifelong learning. The model theorizes that orientation toward lifelong learning is a latent construct which manifests as students' likelihood to engage in four types of learning activities: formal work-related activities, informal work-related activities, formal personal interest activities, and informal personal interest activities. The Postsecondary Orientation toward Lifelong Learning scale (POLL) was developed and the validity of the resulting score interpretations was examined. The instrument was used to compare potential differences in orientation toward lifelong learning between freshmen and seniors. Exploratory factor analyses of the responses of 138 undergraduate college students in the pilot study data provided tentative support for the factor structure within each type of learning activity. Guttman's <λ>λ2 estimates of the learning activity subscales ranged from .78 to .85. Follow-up confirmatory factor analysis using structural equation modeling did not corroborate support for the hypothesized four-factor model using the main student sample data of 405 undergraduate students. Several alternative reflective factor structures were explored. A two-factor model representing factors for Instructing/Presenting and Reading learning activities produced marginal model-data fit and warrants further investigation. The summed POLL total scores had a relatively strong positive correlation with global interest in learning (.58), moderate positive correlations with civic engagement and participation (.38) and life satisfaction (.29), and a small positive correlation with social desirability (.15). The results of the main study do not provide support for the malleability of postsecondary students' orientation toward lifelong learning, as measured by the summed POLL scores. The difference between freshmen and seniors' average total POLL scores was not statistically significant and was negligible in size.

Contributors

Agent

Created

Date Created
  • 2011

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Competency Assessment in Nursing Using Simulation: A Generalizability Study and Scenario Validation Process

Description

The measurement of competency in nursing is critical to ensure safe and effective care of patients. This study had two purposes. First, the psychometric characteristics of the Nursing Performance Profile

The measurement of competency in nursing is critical to ensure safe and effective care of patients. This study had two purposes. First, the psychometric characteristics of the Nursing Performance Profile (NPP), an instrument used to measure nursing competency, were evaluated using generalizability theory and a sample of 18 nurses in the Measuring Competency with Simulation (MCWS) Phase I dataset. The relative magnitudes of various error sources and their interactions were estimated in a generalizability study involving a fully crossed, three-facet random design with nurse participants as the object of measurement and scenarios, raters, and items as the three facets. A design corresponding to that of the MCWS Phase I data--involving three scenarios, three raters, and 41 items--showed nurse participants contributed the greatest proportion to total variance (50.00%), followed, in decreasing magnitude, by: rater (19.40%), the two-way participant x scenario interaction (12.93%), and the two-way participant x rater interaction (8.62%). The generalizability (G) coefficient was .65 and the dependability coefficient was .50. In decision study designs minimizing number of scenarios, the desired generalizability coefficients of .70 and .80 were reached at three scenarios with five raters, and five scenarios with nine raters, respectively. In designs minimizing number of raters, G coefficients of .72 and .80 were reached at three raters and five scenarios and four raters and nine scenarios, respectively. A dependability coefficient of .71 was attained with six scenarios and nine raters or seven raters and nine scenarios. Achieving high reliability with designs involving fewer raters may be possible with enhanced rater training to decrease variance components for rater main and interaction effects. The second part of this study involved the design and implementation of a validation process for evidence-based human patient simulation scenarios in assessment of nursing competency. A team of experts validated the new scenario using a modified Delphi technique, involving three rounds of iterative feedback and revisions. In tandem, the psychometric study of the NPP and the development of a validation process for human patient simulation scenarios both advance and encourage best practices for studying the validity of simulation-based assessments.

Contributors

Agent

Created

Date Created
  • 2014