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IntroductionThe primary objective of this study was to identify variables that significantly influence the implementation of math Response to Intervention (RTI) at the school level, utilizing the ECLS-K: 2011 dataset. MethodsDue to missing values in the original dataset, a Random Forest algorithm was employed for data imputation, generating a total of 10 imputed datasets. Elastic net logistic regression, combined with nested cross-validation, was applied to each imputed dataset, potentially resulting in 10 models with different variables. Variables for the models derived from the imputed datasets were selected using four methods, leading to four candidate models for final selection. These models were assessed based on their performance of prediction accuracy, culminating in the selection of the final model that outperformed the others. Results and discussionMethod₅₀and Method_coefemerged as the most effective, achieving a balanced accuracy of 0.852. The ultimate model selected relevant variables that effectively predicted RTI. The predictive accuracy of the final model was also demonstrated by the receiver operating characteristic (ROC) plot and the corresponding area under the curve (AUC) value, indicating its ability to accurately forecast math RTI implementation in schools for the following year. 

Abstract When large-scale assessment programs are developed and administered in a particular language, students from other native language backgrounds may experience considerable barriers to appropriate measurement of the targeted knowledge and skills. Empirical work is needed to determine if one of the most commonly-applied accommodations to address language barriers, namely extended test time limits, corresponds to score comparability for students who use it. Prior work has examined score comparability for English learners (ELs) eligible to use extended time on tests in the United States, but not specifically for those who more specifically show evidence of using the accommodation. NAEP process data were used to explore score comparability for two groups of ELs eligible for extended time: those who used extended time and those who did not. Analysis of differential item functioning (DIF) was applied to examine potential item bias for these groups when compared to a reference group of native English speakers. Items showing significant and large DIF were identified in both comparisons, with slightly more DIF items identified for the comparison involving ELs who used extended time. Item location and word counts were examined for those items displaying DIF, with results showing some alignment with the notion that language-related barriers may be present for ELs even when extended time is used. Overall, results point to a need for ongoing consideration of the unique needs of ELs during large-scale testing, and the opportunities test process data offer for more comprehensive analyses of accommodation use and effectiveness. 

Abstract Schools are often encouraged to foster a positive climate to reduce adolescent violence, but evidence on the effectiveness of this approach varies significantly. This study investigates the roots of this variation by testing alternative hypotheses about how positive school-level climate and school-level student friendship network density interact to shape adolescent violence perpetration. Research on informal social control and network closure suggests that the violence-reducing association of positive school climate will be enhanced among schools where students are more densely tied through their friendships. Research on youth conflict and subversion of control suggests the opposite. These hypotheses are tested with data from Waves I-II of the National Longitudinal Study of Adolescent to Adult Health (n = 11,771; 49% Female; Age mean = 15.04, SD = 1.60). Consistent with the conflict/subversion hypothesis, analyses indicate that the inverse association between positive school climate and adolescent violence is only evident among schools with a very low density of friendship ties. Strikingly, however, there is evidence that a more positive school climate is associated with increases in violence among youth attending schools with a high density of friendship ties. These findings suggest that efforts to reduce violence by fostering cohesion among youth in their schools and other social contexts can be undermined by youth network processes. 

Abstract Traditional approaches to the modeling of multiple‐choice item response data (e.g., 3PL, 4PL models) emphasize slips and guesses as random events. In this paper, an item response model is presented that characterizes both disjunctively interacting guessing and conjunctively interacting slipping processes as proficiency‐related phenomena. We show how evidence for this perspective is seen in the systematic form of invariance violations for item slip and guess parameters under four‐parameter IRT models when compared across populations of different mean proficiency levels. Specifically, higher proficiency populations tend to show higher guess and lower slip probabilities than lower proficiency populations. The results undermine the use of traditional models for IRT applications that require invariance and would suggest greater attention to alternatives. 

Abstract Item difficulty and dimensionality often correlate, implying that unidimensional IRT approximations to multidimensional data (i.e., reference composites) can take a curvilinear form in the multidimensional space. Although this issue has been previously discussed in the context of vertical scaling applications, we illustrate how such a phenomenon can also easily occur within individual tests. Measures of reading proficiency, for example, often use different task types within a single assessment, a feature that may not only lead to multidimensionality, but also an association between item difficulty and dimensionality. Using a latent regression strategy, we demonstrate through simulations and empirical analysis how associations between dimensionality and difficulty yield a nonlinear reference composite where the weights of the underlying dimensionschangeacross the scale continuum according to the difficulties of the items associated with the dimensions. We further show how this form of curvilinearity produces systematic forms of misspecification in traditional unidimensional IRT models (e.g., 2PL) and can be better accommodated by models such as monotone‐polynomial or asymmetric IRT models. Simulations and a real‐data example from the Early Childhood Longitudinal Study—Kindergarten are provided for demonstration. Some implications for measurement modeling and for understanding the effects of 2PL misspecification on measurement metrics are discussed. 

Abstract In computer‐based tests allowing revision and reviews, examinees' sequence of visits and answer changes to questions can be recorded. The variable‐length revision log data introduce new complexities to the collected data but, at the same time, provide additional information on examinees' test‐taking behavior, which can inform test development and instructions. In the current study, we used recently proposed statistical learning methods for sequence data to provide an exploratory analysis of item‐level revision and review log data. Based on the revision log data collected from computer‐based classroom assessments, common prototypes of revisit and review behavior were identified. The relationship between revision behavior and various item, test, and individual covariates was further explored under a Bayesian multivariate generalized linear mixed model. 

Background/Context:Schools are increasingly using scripted curricula that limit teacher autonomy. These limitations are exacerbated when scripted curricula are enacted in fully standardized, asynchronous online course environments with no mechanisms for student–teacher communication. Purpose:This study extends understanding of how teacher discretion, identity, and the relationship between those two components shape students’ educational experiences online. Research Design:Within a sequential mixed method design, we identified spaces for teacher discretion using critical discourse analysis. By coding lesson transcripts, we developed a typology of common strategies: friendly, directive, personalized, and procedural. We used the resulting typology to run statistical models examining associations among teacher identity, discretionary acts, and student achievement. Lastly, we turned back to the qualitative data to confirm findings, test hypotheses, and provide nuance. Findings:Teachers presenting as Black were significantly more likely to use a procedural approach and significantly less likely to use friendly strategies. Students scored higher on their end-of-lesson quiz when their teacher used personalized strategies, such as sharing relevant personal experiences, and scored lower when teachers used friendly or directive strategies. Conclusions:Findings have implications for understanding and enacting equitable educational practices in asynchronous, scripted online environments. The isolation of discretionary acts feasible within the virtual learning environment studied contributes nuance to knowledge of the mechanisms through which teacher discretion might result in more favorable learning outcomes for students belonging to minoritized groups. 

Abstract Private nonprofit colleges are increasingly using tuition resets, or a decrease in sticker price by at least 5%, to attract new students and counter declining demand. While discounting tuition with institutional aid is a common practice to get accepted students to matriculate and to increase affordability, a tuition reset is a more transparent approach that moves colleges away from a high aid/high tuition model. The authors find minimal evidence that these policies increase student enrollment in the long run, but that there may be short-term impacts. As expected, institutional aid decreases and varies directly with the size of the sticker price reduction. The average net price students pay decreases, but this effect may be driven by changes in the estimated non-tuition elements of the total cost of attendance. Finally, net tuition revenue appears unrelated to tuition resets. These findings call into question the efficacy of this practice.