Arkansas High School Freshmen Course Failures 2009-11 -- 2018-19

This study assesses the course failures among Arkansas high school freshmen by different student demographic and programmatic characteristics. We analyze 10 independent cohorts of Arkansas freshmen for descriptive analyses, and then we limit our analytic sample to the two most recent years of data. Algebra I is the most commonly failed course among Arkansas freshmen. Using logit analyses, we find economically disadvantaged students are nine percentage points more likely to fail a course their freshman year than their more advantaged peers after controlling for prior academic achievement and district characteristics and fixed effects. This study is the first research study conducted on Arkansas course for failure high school freshmen. We discuss our findings in the context of course failures among different demographic and programmatic characteristics and conclude with policy suggestions for district leaders to implement and help lead more students to success

Freshman Course Credit and Unexcused Absences: An Arkansas Policy Analysis

This policy analysis examines the implementation of A.C.A. 6-18-222, a statewide policy in Arkansas that addresses unexcused absences and course credit consequences for students. Using anonymized student-level data from the 2020-21 and 2021-22 school years (N=65,651), the study explores variations in policy implementation across districts and investigates the relationship between absences and course failures for freshmen. Our results highlight the wide variability in the number of allowed unexcused absences and the language of course credit consequence among districts. Additionally, our multivariate logistic regressions reveal FRL-eligible students more likely to fail a course after reaching their district’s unexcused absence threshold. Lastly, we find once students reach their district’s unexcused absence threshold, they more likely to fail a core course compared to a non-core course. Our findings provide insights into the variations of local policy implementation for student academic outcomes

Freshman Course Credit and Unexcused Absences: An Arkansas Policy Analysis

This policy analysis examines the implementation of A.C.A. 6-18-222, a statewide policy in Arkansas that addresses unexcused absences and course credit consequences for students. Using anonymized student-level data from the 2020-21 and 2021-22 school years (N=65,651), the study explores variations in policy implementation across districts and investigates the relationship between absences and course failures for freshmen. Our results highlight the wide variability in the number of allowed unexcused absences and the language of course credit consequence among districts. Additionally, our multivariate logistic regressions reveal FRL-eligible students more likely to fail a course after reaching their district’s unexcused absence threshold. Lastly, we find once students reach their district’s unexcused absence threshold, they more likely to fail a core course compared to a non-core course. Our findings provide insights into the variations of local policy implementation for student academic outcomes

Arkansas’s 9th Grade Course Failures and Building Configurations

In this brief, we examine the relationship between course failures among Arkansas’s 9th grade students and the grade levels served in their school. We find that in schools that terminate at 9th grade, 9th graders are less likely to fail one or more course during the year compared to failure rates in schools that terminate at 12th grade. We suggest an increase in awareness and examination of how we assess 9th graders in Arkansas

Examining Arkansas\u27 Freshman GPAs and Long-Term Outcomes

This study examines the Grade Point Averages (GPAs) of high school freshman in Arkansas and their relationship with later outcomes. Using de-identified student-level data from 2009-10 to 2018-19 from the Arkansas Department of Education, this research investigates trends in freshman GPAs, how these trends vary for different demographic and socioeconomic groups, and the relationship of freshman GPAs to high school graduation and college enrollment. We follow seven cohorts of Arkansas first-time freshmen who were enrolled in twelfth grade four years later. Using regression analyses controlling only for student demographic characteristics, we find a one-point gain in freshman GPAs to be associated with a six percentage point increase in the likelihood of graduating high school. Although statistically significant, over 95% of Arkansas students currently graduate high school. Our more practical, significant finding is that a one-point gain in freshman GPA is associated with a 26-percentage point increase in the likelihood of college enrollment. This study follows Chicago\u27s Consortium on School Research\u27s findings and finds freshman GPAs strongly influence future academic successes. We discuss our findings on the importance of freshman GPAs, and we suggest policies to help all subgroups of freshmen succeed

Examining Arkansas\u27 Ninth-Grade GPAs and Long-Term Outcomes

In this brief, we examine Arkansas’ students’ ninth-grade GPAs and their relationship to high school graduation and college enrollment. We follow seven cohorts of Arkansas first-time freshmen who were still enrolled in twelfth grade four years later. We find ninth-grade GPAs strongly influence future academic successes. We suggest policies to help all freshmen succeed

Arkansas High School Freshmen Course Failures

In this brief, we examine course failures among Arkansas high school freshmen by different student demographic and programmatic characteristics. We find economically disadvantaged students most likely to fail a course their freshman year. We suggest policies to benefit all student demographic and programmatic characteristic

Inviting Participation through IoT: Experiments and Performances in Public Spaces

This paper proposes a workshop on the Internet of Things (IoT) for participation in public life. We will bring together artists, designers, practitioners, and academics interested in site-specific projects involving lighting and other ambient technologies intended to serve community interests such as representation and safety. The authors share their current inquiry on stairwells as an example. Discussion of this project and others will help us locate, trace, and develop networked environments.

Planning a method for covariate adjustment in individually randomised trials: a practical guide

Background: It has long been advised to account for baseline covariates in the analysis of confirmatory randomised trials, with the main statistical justifications being that this increases power and, when a randomisation scheme balanced covariates, permits a valid estimate of experimental error. There are various methods available to account for covariates but it is not clear how to choose among them. // Methods: Taking the perspective of writing a statistical analysis plan, we consider how to choose between the three most promising broad approaches: direct adjustment, standardisation and inverse-probability-of-treatment weighting. // Results: The three approaches are similar in being asymptotically efficient, in losing efficiency with mis-specified covariate functions and in handling designed balance. If a marginal estimand is targeted (for example, a risk difference or survival difference), then direct adjustment should be avoided because it involves fitting non-standard models that are subject to convergence issues. Convergence is most likely with IPTW. Robust standard errors used by IPTW are anti-conservative at small sample sizes. All approaches can use similar methods to handle missing covariate data. With missing outcome data, each method has its own way to estimate a treatment effect in the all-randomised population. We illustrate some issues in a reanalysis of GetTested, a randomised trial designed to assess the effectiveness of an electonic sexually transmitted infection testing and results service. // Conclusions: No single approach is always best: the choice will depend on the trial context. We encourage trialists to consider all three methods more routinely