36 research outputs found
How Teachers Use Data: Description and Differences Across PreK Through Third Grade
The use of data to inform instruction has been linked to improved student outcomes, early identification of intervention needs, and teacher decision-making and efficacy. Additionally, data are used as a means of accountability within educational settings. However, little is known about data use practices among early grades teachers. The purpose of the current study is to describe the data use of PreK to third grade teachers and to investigate differences in data use and support across grade levels. Participants were 307 early childhood teachers in PreK and early elementary school. Analysis of survey data revealed, overall, most teachers across grade levels collected observational data and direct assessments and data were predominantly used to inform instruction and determine if students are ready to learn new skills. In general, teachers indicated that support for data use is available. Results also indicate significant variation in data types, use, and support across PreK to third grade
Validation of the short version of the dimensional inventory for child development assessment
Objectives: There is a critical need to monitor the development of children around the world, and in Brazil, this need is substantial since there is a paucity of assessment tools. This study aimed to describe the design and provide evidence of reliability and validity for the short version of the Dimensional Inventory for Child Development Assessment (IDADI-short). Methods: A sample of 1,865 biological mothers of children aged 4---72 months (M = 34.8, SD = 20.20) completed the IDADI to assess Cognitive, socio-emotional, Expressive, and Receptive Language and Communication, Fine and Gross Motor, and Adaptive Behavior development. The psychometric properties of a total of 118 subscales of IDADI were obtained and the IDADI-short age-specific scores were correlated with the original inventory, and criteria variables such as neurodevelopment diagnosis, socioeconomic status, and sex. Results: Item Response Theory analysis, Cronbach’s Alpha, and McDonald’s Omega indicated excellent internal consistency and optimal participant discrimination after minor alterations. IDADI-short scores were strongly associated with the original inventory, with high sensibility and specificity precision for developmental delays. Significant associations with relevant criteria variables were also observed. Conclusion: Findings support the use of IDADI-short as a parental measure of young children’s development
White privilege and teacher perceptions of teacher-child relationship quality
In this study, we investigated differences in teachers’ perceptions of the teacher-child relationship from kindergarten through second grade as a function of child race and gender from the perspective of critical race theory and the cultural synchrony hypothesis. Given the extensive evidence of White privilege and anti-Black racism in the US education system, we expected that teachers, particularly White teachers, would perceive their relationships with White children more positively than with Black children. Controlling for family SES and child gender, results supported this hypothesis. Black boys had the highest risk of being perceived by teachers as having poor relationships with teachers in kindergarten (highest conflict and lowest closeness) and White girls had the lowest risk. In addition, teachers perceived relationships with Black boys as increasing in conflict across first and second grades at higher rates than with White and female children. These findings remained after examining teacher-child racial match as a moderator. Our results indicate that racism and sexism work together to explain the perceptions teachers have of children in the early elementary grades. Implications for training teachers and school psychologists on anti-racism and cultural competency are discussed
Validation of the short version of the dimensional inventory for child development assessment
Objectives: There is a critical need to monitor the development of children around the world, and in Brazil, this need is substantial since there is a paucity of assessment tools. This study aimed to describe the design and provide evidence of reliability and validity for the short version of the Dimensional Inventory for Child Development Assessment (IDADI-short).
Methods: A sample of 1,865 biological mothers of children aged 4---72 months (M = 34.8, SD = 20.20) completed the IDADI to assess Cognitive, socio-emotional, Expressive, and Receptive Language and Communication, Fine and Gross Motor, and Adaptive Behavior development. The psychometric properties of a total of 118 subscales of IDADI were obtained and the IDADI-short age-specific scores were correlated with the original inventory, and criteria variables such as neurodevelopment diagnosis, socioeconomic status, and sex.
Results: Item Response Theory analysis, Cronbach’s Alpha, and McDonald’s Omega indicated excellent internal consistency and optimal participant discrimination after minor alterations. IDADI-short scores were strongly associated with the original inventory, with high sensibility and specificity precision for developmental delays. Significant associations with relevant criteria variables were also observed.
Conclusion: Findings support the use of IDADI-short as a parental measure of young children’s development
Congruence within the Parent-Teacher Relationship: Associations with Children’s Functioning
Meaningful interactions between families and schools benefit multiple facets of children’s functioning including their academic, social, and behavioral adjustment (Christenson & Sheridan, 2001).
Positive relationships between parents and teachers predict children’s enhanced social-emotional functioning and academic adjustment across time (Izzo, Weissberg, Kasprow, & Fendrich, 1999).
Studies of parent-teacher relationships often focus on the association of child outcomes with separate parent or teacher reports of their relationship quality. Little attention has focused on the congruence of perceptions within parent-teacher dyads.
It may be the case that when parents and teachers view their relationship in a similar positive light, better connections or partnerships across the home and school environments result, thereby enhancing children’s functioning.
Conversely, when parents and teachers hold discrepant views about their relationship, or both view it negatively, they may be less likely to communicate and share goals for children; this disconnect may impede children’s functioning.
This study examined the degree to which congruity and incongruity in parent and teacher views of their relationship are related to children’s academic, social, and behavioral functioning.
Congruity was examined using a categorical approach:
o Positive congruence: parents and teachers share positive views about their relationship
o Non-positive congruence: parents and teachers share non-positive views about their relationship
o Incongruence: parents and teachers hold differing views about the quality of their relationship
Research Question and Hypothesis
Is congruence/incongruence between parents and teachers in their views of their relationship related to children’s academic, social, and behavioral functioning?
It was hypothesized that congruent, positive views of the parent-teacher relationship would be associated with children’s enhanced academic, social, and behavioral functioning to a greater extent than non-positive congruent or incongruent views
Opportunities for learning and social interaction in infant sitting: Effects of sitting support, sitting skill, and gross motor delay
The development of independent sitting changes everyday opportunities for learning and has cascading effects on cognitive and language development. Prior to independent sitting, infants experience the sitting position with physical support from caregivers. Why does supported sitting not provide the same input for learning that is experienced in independent sitting? This question is especially relevant for infants with gross motor delay, who require support in sitting for many months after typically developing infants sit independently. We observed infants with typical development (n = 34, ages 4–7 months) and infants with gross motor delay (n = 128, ages 7–16 months) in early stages of sitting development, and their caregivers, in a dyadic play observation. We predicted that infants who required caregiver support for sitting would spend more time facing away from the caregiver and less time contacting objects than infants who could sit independently. We also predicted that caregivers of supported sitters would spend less time contacting objects because their hands would be full supporting their infants. Our first two hypotheses were confirmed; however, caregivers spent surprisingly little time using both hands to provide support, and caregivers of supported sitters spent more time contacting objects than caregivers of independent sitters. Similar patterns were seen in the group of typically developing infants and the infants with motor delay. Our findings suggest that independent sitting and supported sitting provide qualitatively distinct experiences with different implications for social interaction and learning opportunities
Targeted Physical Therapy Combined with Spasticity Management Changes Motor Development Trajectory for a 2- Year-Old with Cerebral Palsy
Therapies for children with cerebral palsy (CP) often fail to address essential components of early rehabilitation: intensity, child initiation, and an embodied approach. Sitting Together And Reaching To Play (START-Play) addresses these issues while incorporating intensive family involvement to maximize therapeutic dosage. While START-Play was developed and tested on children aged 7–16 months with motor delays, the theoretical construct can be applied to intervention in children of broader ages and skills levels. This study quantifies the impact of a broader STARTPlay intervention combined with Botulinum toxin-A (BoNT-A) and phenol on the developmental trajectory of a 24 month-old child with bilateral spastic CP. In this AB +1 study, A consisted of multiple baseline assessments with the Gross Motor Function Measure-66 and the Assessment of Problem Solving in Play. The research participant demonstrated a stable baseline during A and changes in response to the combination of BoNT-A/phenol and 12 START-Play sessions during B, surpassing the minimal clinically important difference on the Gross Motor Function Measure-66. The followup data point (+1) was completed after a second round of BoNT-A/phenol injections. While the findings suggest the participant improved his gross motor skills with BoNT-A/phenol and STARTPlay, further research is needed to generalize these findings
31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two
Background
The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd.
Methods
We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background.
Results
First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001).
Conclusions
In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival
A Comparison of Population-Averaged and Cluster-Specific Approaches in the Context of Unequal Probabilities of Selection
Sampling designs of large-scale, federally funded studies are typically complex, involving multiple design features (e.g., clustering, unequal probabilities of selection). Researchers must account for these features in order to obtain unbiased point estimators and make valid inferences about population parameters. Single-level (i.e., population-averaged) and multilevel (i.e., cluster-specific) methods provide two alternatives for modeling clustered data. Single-level methods rely on the use of adjusted variance estimators to account for dependency due to clustering, whereas multilevel methods incorporate the dependency into the specification of the model.
Although the literature comparing single-level and multilevel approaches is vast, comparisons have been limited to the context in which all sampling units are selected with equal probabilities (thus circumventing the need for sampling weights). Weighted multilevel modeling is more complex than weighted single-level modeling, and fully flexible methods for estimating weighted multilevel models have only recently been developed. Both approaches are used in practice, but researchers are left with minimal guidance as to which approach is most appropriate.
The goal of this study was to determine under what conditions single-level and multilevel estimators outperform one another (with respect to bias, mean square error, coverage, and root mean square error) in the context of a two-stage sampling design with unequal probabilities of selection. Monte Carlo simulation methods were used to evaluate the impact of several factors, including population model, informativeness of the design, distribution of the outcome variable, intraclass correlation coefficient, cluster size, and estimation method. Results indicated that the unweighted estimators performed similarly across conditions, whereas the weighted single-level estimators tended to outperform the weighted multilevel estimators, particularly under non-ideal sample conditions. Multilevel weight approximation methods did not perform well when the design was informative.
Single-level and multilevel approaches both have advantages and disadvantages, so it is recommended that researchers validate their findings by running the analyses multiple times using different methods. Convergence across methods lends support to the findings, whereas divergence provides a starting point for identifying potentially unreliable results. Ultimately, the appropriateness of a statistical method depends on the researcher’s aims, so even a seemingly well-performing approach may not be suitable.
Adviser: James A. Bovair
Evaluating Measurement Invariance with Censored Ordinal Data: A Monte Carlo Comparison of Alternative Model Estimators and Scales of Measurement
Evaluations of measurement invariance provide essential construct validity evidence. However, the quality of such evidence is partly dependent upon the validity of the resulting statistical conclusions. The presence of Type I or Type II errors can render measurement invariance conclusions meaningless.
The purpose of this study was to determine the effects of categorization and censoring on the behavior of the chi-square/likelihood ratio test statistic and two alternative fit indices (CFI and RMSEA) under the context of evaluating measurement invariance. Monte Carlo simulation was used to examine Type I error and power rates for the (a) overall test statistic/fit indices, and (b) change in test statistic/fit indices. Data were generated according to a multiple-group single-factor CFA model across 40 conditions that varied by sample size, strength of item factor loadings, and categorization thresholds. Seven different combinations of model estimators (ML, Yuan-Bentler scaled ML, and WLSMV) and specified measurement scales (continuous, censored, and categorical) were used to analyze each of the simulation conditions. As hypothesized, non-normality increased Type I error rates for the continuous scale of measurement and did not affect error rates for the categorical scale of measurement. Maximum likelihood estimation combined with a categorical scale of measurement resulted in more correct statistical conclusions than the other analysis combinations. For the continuous and censored scales of measurement, the Yuan-Bentler scaled ML resulted in more correct conclusions than normal-theory ML. The censored measurement scale did not offer any advantages over the continuous measurement scale. Comparing across fit statistics and indices, the chi-square-based test statistics were preferred over the alternative fit indices, and ΔRMSEA was preferred over ΔCFI.
Results from this study should be used to inform the modeling decisions of applied researchers. However, no single analysis combination can be recommended for all situations. Therefore, it is essential that researchers consider the context and purpose of their analyses