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- Genre: Doctoral Dissertation
Description
This study examines the effects of providing persuasive writing and reading comprehension strategy training on source-based essay writing. Strategy training was administered through the use of the Writing Pal and the Interactive Strategy Trainer for Active Reading and Thinking (iSTART). The impact of both individual (writing or reading) and blended strategy training on source-based writing was investigated. A total of 261 participants completed the study; after removing incomplete and second language participants the source-based writing and system performance was assessed for 175 participants (n no instruction = 48, n iSTART =41, n Writing Pal =41, n blended =45).
Results indicated that participants who received blended strategy training produced higher quality source-based essays than participants who received only reading comprehension, writing strategy training, or no training. Furthermore, participants who received only reading comprehension or writing strategy training did not produce higher quality source-based essays than participants in the no-training control group. Time on task was investigated as a potential explanation for the results. Neither total time on task nor practice time were predictive of group differences on source-based essay scores. Analyses further suggested that the impact of strategy training does not differ as a function of prior abilities; however, training does seem to impact the relation between prior abilities and source-based essay scores. Specifically, prior writing ability was unrelated to performance for those who received writing training (i.e., Writing Pal and blended conditions), and prior reading ability was unrelated to performance for those received the full dosage of iSTART training. Overall, the findings suggest that when taught in conjunction with one another, reading comprehension and writing strategy training transfers to source-based writing, providing a positive impact on score. Potential changes to the Writing Pal and iSTART to more closely align training with source-based writing are discussed as methods of further increasing the impact of training on source-based writing.
Results indicated that participants who received blended strategy training produced higher quality source-based essays than participants who received only reading comprehension, writing strategy training, or no training. Furthermore, participants who received only reading comprehension or writing strategy training did not produce higher quality source-based essays than participants in the no-training control group. Time on task was investigated as a potential explanation for the results. Neither total time on task nor practice time were predictive of group differences on source-based essay scores. Analyses further suggested that the impact of strategy training does not differ as a function of prior abilities; however, training does seem to impact the relation between prior abilities and source-based essay scores. Specifically, prior writing ability was unrelated to performance for those who received writing training (i.e., Writing Pal and blended conditions), and prior reading ability was unrelated to performance for those received the full dosage of iSTART training. Overall, the findings suggest that when taught in conjunction with one another, reading comprehension and writing strategy training transfers to source-based writing, providing a positive impact on score. Potential changes to the Writing Pal and iSTART to more closely align training with source-based writing are discussed as methods of further increasing the impact of training on source-based writing.
ContributorsWeston Jennifer L (Author) / McNamara, Danielle S. (Thesis advisor) / Connor, Carol M (Committee member) / Glenberg, Arthur M. (Committee member) / Graham, Steve (Committee member) / Arizona State University (Publisher)
Created2015
Description
The purposes of this study were (1) to examine the direct and indirect effect of school-level testing policies on reading achievement though changes in amount and types of reading instruction, (2) to investigate the reading trajectories moderated by school-level testing policies longitudinally, and (3) to examine the relationship between testing policies and the achievement gap by exploring whether certain student characteristics moderate the relationship between testing policy and reading achievement, using Early Childhood Longitudinal Study Kindergarten (ECLS-K) Cohort of 2010-2011 data. Findings from a multilevel full structural mediation model suggest that school-level frequency of state/local standardized tests had an indirect effect on student reading achievement through changes in both amount and the types of instruction at the school-level (cross-sectional fall kindergarten sample =12,241 children nested in 1,067 kindergarten classes). The findings from a three-level growth models indicated only children of Asian background and children from high socio-economic backgrounds who had frequent standardized tests in kindergarten accelerated in their monthly reading growth, whereas other children (e.g., low SES, non-Asian children) did not show any changes in the rate of the reading growth (longitudinal sample from fall of kindergarten to spring of first grade = 7,392 children nested in 744 kindergartens). The findings from the current study suggest that testing policy is not an effective means to reduce the achievement gap of children from disadvantaged family backgrounds, underperforming children or that children from low socieo-economic backgrounds. These children did not seem to benefit from frequent standardized tests longitudinally. Implications for supporting school assessment practices and instruction are discussed.
ContributorsIm, Haesung (Author) / Nakagawa, Kathryn (Thesis advisor) / Thompson, Marilyn (Committee member) / Swadener, Elizabeth (Committee member) / Iida, Masumi (Committee member) / Arizona State University (Publisher)
Created2015
Description
Although models for describing longitudinal data have become increasingly sophisticated, the criticism of even foundational growth curve models remains challenging. The challenge arises from the need to disentangle data-model misfit at multiple and interrelated levels of analysis. Using posterior predictive model checking (PPMC)—a popular Bayesian framework for model criticism—the performance of several discrepancy functions was investigated in a Monte Carlo simulation study. The discrepancy functions of interest included two types of conditional concordance correlation (CCC) functions, two types of R2 functions, two types of standardized generalized dimensionality discrepancy (SGDDM) functions, the likelihood ratio (LR), and the likelihood ratio difference test (LRT). Key outcomes included effect sizes of the design factors on the realized values of discrepancy functions, distributions of posterior predictive p-values (PPP-values), and the proportion of extreme PPP-values.
In terms of the realized values, the behavior of the CCC and R2 functions were generally consistent with prior research. However, as diagnostics, these functions were extremely conservative even when some aspect of the data was unaccounted for. In contrast, the conditional SGDDM (SGDDMC), LR, and LRT were generally sensitive to the underspecifications investigated in this work on all outcomes considered. Although the proportions of extreme PPP-values for these functions tended to increase in null situations for non-normal data, this behavior may have reflected the true misfit that resulted from the specification of normal prior distributions. Importantly, the LR and the SGDDMC to a greater extent exhibited some potential for untangling the sources of data-model misfit. Owing to connections of growth curve models to the more fundamental frameworks of multilevel modeling, structural equation models with a mean structure, and Bayesian hierarchical models, the results of the current work may have broader implications that warrant further research.
In terms of the realized values, the behavior of the CCC and R2 functions were generally consistent with prior research. However, as diagnostics, these functions were extremely conservative even when some aspect of the data was unaccounted for. In contrast, the conditional SGDDM (SGDDMC), LR, and LRT were generally sensitive to the underspecifications investigated in this work on all outcomes considered. Although the proportions of extreme PPP-values for these functions tended to increase in null situations for non-normal data, this behavior may have reflected the true misfit that resulted from the specification of normal prior distributions. Importantly, the LR and the SGDDMC to a greater extent exhibited some potential for untangling the sources of data-model misfit. Owing to connections of growth curve models to the more fundamental frameworks of multilevel modeling, structural equation models with a mean structure, and Bayesian hierarchical models, the results of the current work may have broader implications that warrant further research.
ContributorsFay, Derek (Author) / Levy, Roy (Thesis advisor) / Thompson, Marilyn (Committee member) / Enders, Craig (Committee member) / Arizona State University (Publisher)
Created2015
Description
In two separate publications, the average patterns of, and individual differences in, preschoolers' selective attention processes were investigated using a multilevel modeling framework. In Publication 1, using two independent samples (Ns= 42, 75), preschoolers' selective attention towards different types of emotions (both positive and negative) was examined using two eye-tracking tasks. The results showed that, on average, children selectively attended to valenced emotional information more than neutral emotional information. In addition, a majority of children were able to detect the different emotional stimulus among three neutral stimuli during the visual search task. Children were more likely to detect angry than sad emotional expressions among neutral faces; however, no difference was found between detection of angry and happy faces among neutral faces. In Publication 2, the associations of children's anger and sadness proneness to their attention biases towards anger and sad emotional information, respectively, and the relations of these biases to various aspects children's social functioning and adjustment were examined among preschool-aged children (N = 75). Children's predisposition to anger and sadness were shown to be related to attentional biases towards those specific emotions, particularly if children lacked the ability to regulate their attention. Similarly, components of attention regulation played an important role in moderating the associations of biases towards angry information to aggressive behaviors, social competence, and anxiety symptoms. Biases towards sadness were unrelated to maladjustment or social functioning. Findings were discussed in terms of the importance of attention biases and attention regulation as well as the implications of the findings for attention training programs.
ContributorsSeyed Nozadi, Sara (Author) / Spinrad, Tracy L. (Thesis advisor) / Eisenberg, Nancy (Committee member) / Johnson, Scott (Committee member) / Thompson, Marilyn (Committee member) / Arizona State University (Publisher)
Created2014
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) 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.
ContributorsCrawford, Aaron (Author) / Levy, Roy (Thesis advisor) / Green, Samuel (Committee member) / Thompson, Marilyn (Committee member) / Arizona State University (Publisher)
Created2014
Description
Broaden and build theory (BBT; Fredrickson, 1998; 2001) postulates that positive emotions expand the scope of one's attention and thought-action repertoires (Fredrickson & Branigan, 2005). Within the boundaries of BBT, the undoing hypothesis (Fredrickson, 1998, Fredrickson & Levenson, 1998) argues that positive emotions themselves do not bring forth specific action tendencies or urges; therefore, they do not consequently require an increase in cardiovascular activity to carry out the urge. On the other hand, positive emotions have evolved to subdue the cardiovascular response previously initiated by negative emotions. This dissertation proposes that the real power of positive emotions might be to undo not the effects of negative emotions themselves, however, but simply reduce the arousal itself. This dissertation used minor physiological arousal (e.g., a step-stool task) to simulate the cardiovascular effects of the stress manipulations used in previous tests of the undoing hypothesis by Fredrickson and colleagues. This dissertation asks if positive emotions undo the cardiovascular reactivity of an emotionally neutral stimulus. Positive emotions were induced through one film clip (i.e., a happy film clip) and was compared to a neutral film clip (no emotion elicited). An experimental design measured the effects of arousal induction and film clip on participants' cardiovascular activity. Results indicated that positive emotions had the same effect as no emotions on participants' cardiovascular activity. Implications for theory and research are provided, as well as an assessment of the study's strengths and limitations. Finally, several directions for future research are offered.
ContributorsDeiss, Douglas M (Author) / Floyd, Kory (Thesis advisor) / Mongeau, Paul (Committee member) / Thompson, Marilyn (Committee member) / Arizona State University (Publisher)
Created2012
Description
This study investigated the internal factor structure of the English language development Assessment (ELDA) using confirmatory factor analysis. ELDA is an English language proficiency test developed by a consortium of multiple states and is used to identify and reclassify English language learners in kindergarten to grade 12. Scores on item parcels based on the standards tested from the four domains of reading, writing, listening, and speaking were used for the analyses. Five different factor models were tested: a single factor model, a correlated two-factor model, a correlated four-factor model, a second-order factor model and a bifactor model. The results indicate that the four-factor model, second-order model, and bifactor model fit the data well. The four-factor model hypothesized constructs for reading, writing, listening and speaking. The second-order model hypothesized a second-order English language proficiency factor as well as the four lower-order factors of reading, writing, listening and speaking. The bifactor model hypothesized a general English language proficiency factor as well as the four domain specific factors of reading, writing, listening, and speaking. The Chi-square difference tests indicated that the bifactor model best explains the factor structure of the ELDA. The results from this study are consistent with the findings in the literature about the multifactorial nature of language but differ from the conclusion about the factor structures reported in previous studies. The overall proficiency levels on the ELDA gives more weight to the reading and writing sections of the test than the speaking and listening sections. This study has implications on the rules used for determining proficiency levels and recommends the use of conjunctive scoring where all constructs are weighted equally contrary to current practice.
ContributorsKuriakose, Anju Susan (Author) / Macswan, Jeff (Thesis advisor) / Haladyna, Thomas (Thesis advisor) / Thompson, Marilyn (Committee member) / Arizona State University (Publisher)
Created2011
Description
National assessment data indicate that the large majority of students in America perform below expected proficiency levels in the area of writing. Given the importance of writing skills, this is a significant problem. Curriculum-based measurement, when used for progress monitoring and intervention planning, has been shown to lead to improved academic achievement. However, researchers have not yet been able to establish the validity of curriculum-based measures of writing (CBM-W). This study examined the structural validity of CBM-W using exploratory factor analysis. The participants for this study were 253 third, 154 seventh, and 154 tenth grade students. Each participant completed a 3-minute writing sample in response to a narrative prompt. The writing samples were scored for fifteen different CBM-W indices. Separate analyses were conducted for each grade level to examine differences in the CBM-W construct across grade levels. Due to extreme multicollinearity, principal components analysis rather than common factor analysis was used to examine the structure of writing as measured by CBM-W indices. The overall structure of CBM-W indices was found to remain stable across grade levels. In all cases a three-component solution was supported, with the components being labeled production, accuracy, and sentence complexity. Limitations of the study and implications for progress monitoring with CBM-W are discussed, including the recommendation for a combination of variables that may provide more reliable and valid measurement of the writing construct.
ContributorsBrown, Alec Judd (Author) / Watkins, Marley (Thesis advisor) / Caterino, Linda (Thesis advisor) / Thompson, Marilyn (Committee member) / Arizona State University (Publisher)
Created2012
Description
The primary objective of this study was to develop the Perceived Control of the Attribution Process Scale (PCAPS), a measure of metacognitive beliefs of causality, or a perceived control of the attribution process. The PCAPS included two subscales: perceived control of attributions (PCA), and awareness of the motivational consequences of attributions (AMC). Study 1 (a pilot study) generated scale items, explored suitable measurement formats, and provided initial evidence for the validity of an event-specific version of the scale. Study 2 achieved several outcomes; Study 2a provided strong evidence for the validity and reliability of the PCA and AMC subscales, and showed that they represent separate constructs. Study 2b demonstrated the predictive validity of the scale and provided support for the perceived control of the attribution process model. This study revealed that those who adopt these beliefs are significantly more likely to experience autonomy and well-being. Study 2c revealed that these constructs are influenced by context, yet they lead to adaptive outcomes regardless of this contextual-specificity. These findings suggest that there are individual differences in metacognitive beliefs of causality and that these differences have measurable motivational implications.
ContributorsFishman, Evan Jacob (Author) / Nakagawa, Kathryn (Committee member) / Husman, Jenefer (Committee member) / Graham, Steve (Committee member) / Moore, Elsie (Committee member) / Arizona State University (Publisher)
Created2014
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 (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.
ContributorsO'Brien, Janet Elaine (Author) / Thompson, Marilyn (Thesis advisor) / Hagler, Debra (Thesis advisor) / Green, Samuel (Committee member) / Arizona State University (Publisher)
Created2014