Adolescent Language: Models, Assessment, and Links to Reading

2019 ◽  
Author(s):  
Amanda Goodwin ◽  
Yaacov Petscher ◽  
Jamie Tock
Keyword(s):  
Reading Comprehension ◽  
Bifactor Model ◽  
Language Models ◽  
Multiple Group ◽  
Global Factor ◽  
Eighth Grade Students ◽  
Key Aspects ◽  
Future Work ◽  
The Relationship ◽  
Best Fit

Various models have highlighted the complexity of language. Building on foundational ideas regarding three key aspects of language, our study contributes to the literature by 1) exploring broader conceptions of morphology, vocabulary, and syntax, 2) operationalizing this theoretical model into a gamified, standardized, computer-adaptive assessment of language for fifth to eighth grade students entitled Monster, PI, and 3) uncovering further evidence regarding the relationship between language and standardized reading comprehension via this assessment. Multiple-group item response theory (IRT) across grades show that morphology was best fit by a bifactor model of task specific factors along with a global factor related to each skill. Vocabulary was best fit by a bifactor model that identifies performance overall and on specific words. Syntax, though, was best fit by a unidimensional model. Next, Monster, PI produced reliable scores suggesting language can be assessed efficiently and precisely for students via this model. Lastly, performance on Monster, PI explained more than 50% of variance in standardized reading, suggesting operationalizing language via Monster, PI can provide meaningful understandings of the relationship between language and reading comprehension. Specifically, considering just a subset of a construct, like identification of units of meaning, explained significantly less variance in reading comprehension. This highlights the importance of considering these broader constructs. Implications indicate that future work should consider a model of language where component areas are considered broadly and contributions to reading comprehension are explored via general performance on components as well as skill level performance.

Monster, P.I.: Validation Evidence for an Assessment of Adolescent Language That Assesses Vocabulary Knowledge, Morphological Knowledge, and Syntactical Awareness

2020 ◽  
pp. 153450842096638
Author(s):  
Amanda P. Goodwin ◽  
Yaacov Petscher ◽  
Jamie Tock ◽  
Sara McFadden ◽  
Dan Reynolds ◽  
...  
Keyword(s):  
Reading Comprehension ◽  
Eighth Graders ◽  
Vocabulary Knowledge ◽  
Hierarchical Regression ◽  
Language Performance ◽  
Morphological Knowledge ◽  
Multiple Group ◽  
Reading Vocabulary ◽  
Middle Schoolers ◽  
Eighth Grade Students

Assessment of language skills for upper elementary and middle schoolers is important due to the strong link between language and reading comprehension. Yet, currently few practical, reliable, valid, and instructionally informative assessments of language exist. This study provides validation evidence for Monster, P.I., which is a gamified, standardized, computer-adaptive assessment (CAT) of language for fifth to eighth grade students. Creating Monster, P.I. involved an assessment of the dimensionality of morphology and vocabulary and an assessment of syntax. Results using multiple-group item response theory (IRT) with 3,214 fifth through eighth graders indicated morphology and vocabulary were best assessed via bifactor models and syntax unidimensionally. Therefore, Monster, P.I. provides scores on three component areas of language (multidimensional morphology and vocabulary and unidimensional syntax) with the goal of informing instruction. Validity results also suggest that Monster, P.I. scores show moderate correlations with each other and with standardized reading vocabulary and reading comprehension assessments. Furthermore, hierarchical regression results suggest an important link between Monster, P.I. and standardized reading comprehension, explaining between 56% and 75% of the variance. Such results indicate that Monster, P.I. can provide meaningful understandings of language performance which can guide instruction that can impact reading comprehension performance.

scholarly journals The Task Matters: A Scoping Review on Reading Comprehension Abilities in ADHD

2021 ◽  
pp. 108705472110680
Author(s):  
Kaitlyn M.A. Parks ◽  
Christine N. Moreau ◽  
Kara E. Hannah ◽  
Leah Brainin ◽  
Marc F. Joanisse
Keyword(s):  
Reading Comprehension ◽  
Scoping Review ◽  
Current Knowledge ◽  
Task Demands ◽  
Typically Developing ◽  
Comprehension Ability ◽  
Comprehensive Search ◽  
Future Work ◽  
The Relationship ◽  
Reading Comprehension Ability

Objective: A broad range of tasks have been used to classify individuals with ADHD with reading comprehension difficulties. However, the inconsistency in the literature warrants a scoping review of current knowledge about the relationship between ADHD diagnosis and reading comprehension ability. Method: A comprehensive search strategy was performed to identify relevant articles on the topic. Thirty-four articles met inclusion criteria for the current review. Results: The evidence as a whole suggests reading comprehension is impaired in ADHD. The most prominent effect was found in studies where participants retell or pick out central ideas in stories. On these tasks, participants with ADHD performed consistently worse than typically developing controls. However, some studies found that performance in ADHD improved when reading comprehension task demands were low. Conclusion: Results suggest that performance in ADHD depends on the way reading comprehension is measured and further guide future work clarifying why there are such discrepant findings across studies.

Identifying Physico-Chemical Laws from the Robotically Collected Data

2019 ◽  
Author(s):  
Liwei Cao ◽  
Danilo Russo ◽  
Vassilios S. Vassiliadis ◽  
Alexei Lapkin
Keyword(s):  
Experimental Data ◽  
Numerical Models ◽  
Predictor Variable ◽  
Physical Models ◽  
Training Data ◽  
Mixed Integer ◽  
Physico Chemical ◽  
Data Points ◽  
Future Work ◽  
The Relationship

<p>A mixed-integer nonlinear programming (MINLP) formulation for symbolic regression was proposed to identify physical models from noisy experimental data. The formulation was tested using numerical models and was found to be more efficient than the previous literature example with respect to the number of predictor variables and training data points. The globally optimal search was extended to identify physical models and to cope with noise in the experimental data predictor variable. The methodology was coupled with the collection of experimental data in an automated fashion, and was proven to be successful in identifying the correct physical models describing the relationship between the shear stress and shear rate for both Newtonian and non-Newtonian fluids, and simple kinetic laws of reactions. Future work will focus on addressing the limitations of the formulation presented in this work, by extending it to be able to address larger complex physical models.</p><p><br></p>

Development and evaluation of trans-Amadi groundwater parameters: The integration of finite element techniques

2019 ◽  
Author(s):  
Chem Int
Keyword(s):  
Finite Element ◽  
Polynomial Regression ◽  
Nitrate Concentration ◽  
Strong Relationship ◽  
Total Iron ◽  
Coefficient Of Determination ◽  
Port Harcourt ◽  
Polynomial Expression ◽  
The Relationship ◽  
Best Fit

Mathematical model was developed and evaluated to monitor and predict the groundwater characteristics of Trans-amadi region in Port Harcourt City. In this research three major components were considered such as chloride, total iron and nitrate concentration as well as the polynomial expression on the behavious on the concentration of each component was determined in terms of the equation of the best fit as well as the square root of the curve. The relationship between nitrate and distance traveled by Nitrate concentration by the model is given as Pc = 0.003x2 - 0.451x + 14.91with coefficient of determination, R² = 0.947, Chloride given as Pc = 0.000x2 - 0.071x + 2.343, R² = 0.951while that of Total Iron is given as Pc = 2E-05x2 - 0.003x + 0.110, R² = 0.930. All these show a strong relationship as established by Polynomial Regression Model. The finite element techniques are found useful in monitoring, predicting and simulating groundwater characteristics of Trans-amadi as well as the prediction on the variation on the parameters of groundwater with variation in time.

THE EFFECTIVENESS OF USING COOPERATIVE SCRIPT METHOD TO IMPROVE STUDENTS’ READING COMPREHENSION ON RECOUNT TEXT OF 8th GRADE STUDENTS OF SMP N KEWAPANTE, MAUMERE IN ACADEMIC YEAR 2017/ 2018

2018 ◽  
Vol 2 (2) ◽  
pp. 210-220
Author(s):  
Wendelinus Oscar Janggo ◽  
Yuliana Wisnawati Nona Nungsi
Keyword(s):  
Reading Comprehension ◽  
Data Analysis ◽  
Experimental Research ◽  
Qualitative Data ◽  
Qualitative Data Analysis ◽  
Quantitative Data Analysis ◽  
8Th Grade ◽  
Eighth Grade Students ◽  
Quasi Experimental ◽  
Academic Year

This research is entitled “The Effectiveness of Using Cooperative Script Method to Improve Students’ Reading Comprehension on Recount Text of 8th Grade Students of SMP N Kewapante, Maumere in Academic Year 2017/ 2018”. The objective of this research is to investigate and to find out whether the use of cooperative script method effective to improve students’ reading comprehension on recount text. The method of this research is experimental research especially quasi experimental research. In analyzing the data, the researcher combined both quantitative and qualitative data analysis. In qualitative data analysis, the researcher used interview technique in order to get information about students’ perceptions in reading, while in quantitative data analysis, the researcher used SPSS version 16. The result of the research showed that the implementation of Cooperative Script Method in experimental class was more effective to help the students in reading comprehension on recount text compared to the use of the conventional method in control class of the eighth grade students of SMP N Kewapante, Maumere. It is also found that cooperative script method positively contributed to improve students’ reading comprehension. Therefore ,the researcher  suggests the teachers to use cooperative script method in order to improve students reading comprehension Additionally, cooperative script method can also motivate students to be more active, relax and enthusiastic to comprehend reading texts.

Soil and Stream Water Chemistry During Spring Snowmelt

1992 ◽  
Vol 23 (1) ◽  
pp. 13-26 ◽  
Author(s):  
W. H. Hendershot ◽  
L. Mendes ◽  
H. Lalande ◽  
F. Courchesne ◽  
S. Savoie
Keyword(s):  
Stream Water ◽  
Base Cations ◽  
Stream Chemistry ◽  
Stream Water Chemistry ◽  
The Matrix ◽  
Adsorption Desorption ◽  
The Relationship ◽  
Best Fit ◽  
Spring Snowmelt ◽  
Over Time

In order to determine how water flowpath controls stream chemistry, we studied both soil and stream water during spring snowmelt, 1985. Soil solution concentrations of base cations were relatively constant over time indicating that cation exchange was controlling cation concentrations. Similarly SO4 adsorption-desorption or precipitation-dissolution reactions with the matrix were controlling its concentrations. On the other hand, NO3 appeared to be controlled by uptake by plants or microorganisms or by denitrification since their concentrations in the soil fell abruptly as snowmelt proceeded. Dissolved Al and pH varied vertically in the soil profile and their pattern in the stream indicated clearly the importance of water flowpath on stream chemistry. Although Al increased as pH decreased, the relationship does not appear to be controlled by gibbsite. The best fit of calculated dissolved inorganic Al was obtained using AlOHSO4 with a solubility less than that of pure crystalline jurbanite.

Potential Role of Inflammation in Associations between Particulate Matter and Heart Failure

2018 ◽  
Vol 24 (3) ◽  
pp. 341-358 ◽  
Author(s):  
Xiaotong Ji ◽  
Yingying Zhang ◽  
Guangke Li ◽  
Nan Sang
Keyword(s):  
Heart Failure ◽  
Particulate Matter ◽  
Inflammatory Response ◽  
Heart Diseases ◽  
Experimental Studies ◽  
Epidemiological Studies ◽  
Inflammatory Mechanism ◽  
High Concentrations ◽  
Future Work ◽  
The Relationship

Recently, numerous studies have found that particulate matter (PM) exposure is correlated with increased hospitalization and mortality from heart failure (HF). In addition to problems with circulation, HF patients often display high expression of cytokines in the failing heart. Thus, as a recurring heart problem, HF is thought to be a disorder characterized in part by the inflammatory response. In this review, we intend to discuss the relationship between PM exposure and HF that is based on inflammatory mechanism and to provide a comprehensive, updated evaluation of the related studies. Epidemiological studies on PM-induced heart diseases are focused on high concentrations of PM, high pollutant load exposure in winter, or susceptible groups with heart diseases, etc. Furthermore, it appears that the relationship between fine or ultrafine PM and HF is stronger than that between HF and coarse PM. However, fewer studies paid attention to PM components. As for experimental studies, it is worth noting that coarse PM may indirectly promote the inflammatory response in the heart through systematic circulation of cytokines produced primarily in the lungs, while ultrafine PM and its components can enter circulation and further induce inflammation directly in the heart. In terms of PM exposure and enhanced inflammation during the pathogenesis of HF, this article reviews the following mechanisms: hemodynamics, oxidative stress, Toll-like receptors (TLRs) and epigenetic regulation. However, many problems are still unsolved, and future work will be needed to clarify the complex biologic mechanisms and to identify the specific components of PM responsible for adverse effects on heart health.

Sign in / Sign up

Export Citation Format

Share Document