Category: Educational Administration and Leadership

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Educational Administration and Leadership Kindergarten

Student absenteeism and teacher job satisfaction

Student absenteeism is known to impact individual student outcomes negatively, but research suggests that high rates of absenteeism also affect classroom dynamics and teachers’ job satisfaction. A recent article in Educational Researcher analyzed data from a nationally representative sample of kindergarten teachers to understand the correlation between classroom absenteeism and teacher job satisfaction. Using responses from 2,370 teachers surveyed in the Early Childhood Longitudinal Study-Kindergarten Class, the study investigated whether an increase in classroom absenteeism predicted lower levels of teacher satisfaction.

The study found that teachers reported lower job satisfaction when a higher percentage of their students were frequently absent. Key dimensions affected included general job enjoyment and teachers’ perceived effectiveness in their roles, as they often had to remediate absent students, slowing instructional pace and potentially disengaging other students. While absenteeism led to a noticeable decline in overall teacher satisfaction, there was no statistically significant impact on other related aspects, such as teaching efficacy, perceptions of school culture, or school support systems. These results were consistent across both novice and experienced teachers, suggesting that absenteeism challenges contribute to job dissatisfaction regardless of teaching experience.

The findings have broader implications for policy, particularly in today’s educational climate where absenteeism has reached record levels post-pandemic. The authors highlight that addressing absenteeism is essential not only for improving student outcomes but also for supporting teacher retention and satisfaction. Recommended interventions include professional development focused on family engagement, trauma-informed practices, and enhanced support for teachers facing high absenteeism rates in their classrooms.

 

Source: Gottfried, M. A., Ansari, A., & Woods, S. C. (2024). Do teachers with absent students feel less job satisfaction? Educational Researcher, 0013189X241292331. https://doi.org/10.3102/0013189X241292331… Read the rest

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Achievement Educational Administration and Leadership Primary School Education Programme Evaluation

Evidence supports Air Reading

Research consistently highlights the benefits of tutoring for improving student learning and closing achievement gaps. However, scaling up in-person tutoring can be challenging in certain settings. As a result, an increasing number of studies are exploring the efficacy of virtual tutoring as a potential solution. A recent study conducted in spring 2024 of the Air Reading program adds valuable insight to this discussion.

Air Reading is a virtual tutoring program providing skills-based instruction in reading, delivered via paid tutors using a virtual synchronous instruction platform. With a 1:3 tutor-to-student ratio, the program is intended to strike a balance between scalability and individualization.

A randomized controlled trial of Air Reading was conducted in a rural Texas district with 418 first-sixth grade students across six schools. Tutored students received four 40-minute sessions per week for one semester. At post-test, Air Reading students outperformed control students on the NWEA MAP reading assessment (ES = + 0.12), equivalent to an average of 1.6 additional months of learning. Treatment students attended an average of 39.8 sessions of tutoring, and those who completed 40 or more sessions demonstrated significantly higher gains than those with fewer sessions (ES = + 0.17).

 

Source (Open Access): Neitzel, A. J., & Storey, N. (2024). Air reading: A randomized evaluation of a virtual tutoring model. https://jscholarship.library.jhu.edu/handle/1774.2/70119… Read the rest

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Educational Administration and Leadership Kindergarten Primary School Education

Maryland’s ban on school suspensions in K-2: Improvement but more work left to be done

Many school districts now aim to eliminate or at least reduce the use of exclusionary discipline, but is a top-down statewide ban an effective way to accomplish this? A working paper from Jane Lincove and colleagues reviewed statewide data from Maryland for K-2 students from 2014-2019 in an attempt to answer this question after a suspension ban in 2017. The authors used multiple analyses of these data over time to determine whether the ban changed trajectories for students.

The authors found that the statewide ban decreased the usage of out-of-school suspensions by about 60% compared to what was expected based on prior trends, both overall and among key subgroups (including Black, male, economically disadvantaged, and special education students). Importantly, this reduction did not result in adverse effects, such as an increased reliance on in-school suspensions or a rise in violent events.

Despite these overall positive results, the article highlighted several areas where the policy was less successful. The reduction in suspensions was limited to the grades directly affected by the policy (K-2) and did not significantly impact suspension trends in other grades in the same schools (grades 3-5). Additionally, the suspension ban had no measurable impact on student attendance.

 

Source (Open Access): Lincove, Jane Arnold, Mata, Catherine, & Cortes, Kalena E. (n.d.). The effects of a statewide ban on school suspensions. (EdWorkingPaper: 24 -1004)  https://doi.org/10.26300/RZKW-Y763… Read the rest

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Educational Administration and Leadership K-12 Education

Tutoring report and guide for community-based organizations

A new report from Accelerate and ProvenTutoring tells the story of seven community-based organizations (CBOs) who partnered with schools to implement high-dosage, in-person tutoring programs during the school day across a range of contexts and using various approaches. It synthesizes the successes, challenges, and lessons learned during the planning, implementation, and evaluation process. The report provides guidance and raises key questions about supporting community-based organizations in scaling their tutoring models.

The report suggests that CBOs have a vital role to play in the scaling and sustaining of high-dosage, in-person, school day tutoring to address pandemic learning loss and longstanding inequities. Their local knowledge, relationships, expertise in delivering other community programs, and resources make them valuable school partners.  A few of the report’s main points are as follows:

  • Clarity on Tutoring Goals: CBOs and their school partners need to agree on what they are hoping to achieve and use those goals to guide planning and implementation.
  • Support in Tutor Recruitment and Training: CBOs can provide valuable support in recruiting, training, and supporting invested adults to serve as tutors.
  • Adopting Proven Models: CBOs and school partners should adopt a proven, high-dosage tutoring model because it offers the greatest promise of impact on learning outcomes. Building your own model requires an enormous amount of trial and error to make the program effective. It is generally beyond the expertise of CBOs to adapt school materials or develop its own content.
  • Continuous Improvement: Getting tutoring right is challenging. A commitment to continuous improvement, guided by evidence, is necessary to ensure that high-dosage tutoring achieves the desired outcomes.

A companion step-by-step guide is also available for organizations planning to implement tutoring.

 

Source (Open Access): Krajewski, J., Neitzel, A., Lake, C., Davis, S., & Madden, N. (2024). Leveraging community based organizations: High-dosage tutoring pilots in review. ProvenTutoring. ~(https://accelerate.us/wp-content/uploads/2024/09/CBO-Synthesis-Report-compressed.pdf… Read the rest

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Educational Administration and Leadership K-12 Education

Why to adjust effect sizes for baseline covariates?

Standardized mean difference is the effect size typically used to compare the difference between a treatment and control group on continuous outcomes. However, data provided in primary studies to calculate effect sizes vary. Sometimes, multiple options are available, and it’s not always clear which method is best to use.

In an article from 2021, Joseph Taylor and colleagues provided guidelines for reporting data in primary studies to calculate effect sizes, as well as recommendations on which data should be prioritized for meta-analyses.

The authors’ key recommendations for meta-analysts are:

  • Use effect sizes that adjust for baseline covariates, at the very least the pretest scores of the outcome measure, and possibly demographic variables as well. This produces an effect size estimate that is more interpretable and precise.
  • Avoid using unadjusted means when covariate-adjusted means are available, because effect sizes from unadjusted means introduce imprecision and artificially increase effect size heterogeneity in meta-analyses.
  • In cluster studies that assigned schools or classes, adjust effect sizes and variances for baseline covariates and for clustering.

Following these recommendations requires better reporting of necessary data in primary studies. This includes covariate-adjusted means, unadjusted standard deviations and standard error of the adjusted mean difference for individual level studies. For cluster studies, it also requires reporting the intraclass correlation (ICC) and the standard error of the adjusted mean difference from a model that accounts for clustering. The authors provided an online tool to perform all calculations.

 

Source: Taylor, J. A., Pigott, T., & Williams, R. (2022). Promoting knowledge accumulation about intervention effects: Exploring strategies for standardizing statistical approaches and effect size reporting. Educational Researcher, 51(1), 72–80. https://doi.org/10.3102/0013189X211051319… Read the rest

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Educational Administration and Leadership Language Development Primary School Education

Relationship between statistical learning and working memory in children with and without dyslexia

Statistical learning (SL) is the ability to recognize and extract patterns from environmental data, such as language structures and sound co-occurrences, accordingly, SL is crucial for language acquisition and reading skills. Zhou and colleagues studied the relationship between working memory (WM) and SL in children with developmental dyslexia (DD) and their typically developing (TD) peers. Data of this cross-sectional study were collected from 2014 to 2019, involving 651 Grade 1 to Grade 6 Chinese children from Hong Kong, among them 199 diagnosed with DD by a clinical or educational psychologist.

The study consisted of two experiments. First in the artificial orthography experiment, researchers used pseudocharacters with varying predictability levels (high, moderate, low) to assess the impact of working memory on distributional statistical learning. Participants studied 30 pseudocharacters in the learning phase. In the testing phase, they identified whether a pseudocharacter was previously shown in the learning phase.

The findings showed no significant overall difference in working memory’s association with SL between DD and TD children. Notably, the effect of WM on SL was weaker on recognizing moderate-predictable items compared to those of high-predictability or low-predictability. As age increased there was stronger positive effect of WM on recognition of familiar items (studied) in both groups. A negative association between WM and SL was found for unfamiliar items (non-studied), particularly among older children with DD.

Second, the visual triplet learning experiment involved a two-alternatives forced-choice task assessing conditional statistical learning through a sequence of visual triplets. After studying four triples of cartoons, children were required to identify the more familiar item between a familiar (studied) and an unfamiliar (not studied) triplet. Results indicated that children with DD showed a stronger effect of WM when recognizing sequences displayed as familiar-unfamiliar compared to unfamiliar-familiar items, while no such association was found in TD.

These findings highlight the complexity of the relationship between working memory and statistical learning, which varies according to the characteristics of the items and the specific type of statistical learning involved.

 

Source (Open Access): Zhou, M., Zhang, P., Mimeau, C., & Tong, S. X. (2024). Unraveling the complex interplay between statistical learning and working memory in Chinese children with and without dyslexia across different ages. Child Development, 95(5), e338–e351. https://doi.org/10.1111/cdev.14121… Read the rest