Advocates of privatizing education suggest that traditional public schools are not adequately preparing students for college, career readiness, and global citizenship (Lobosco, 2019; Schneider and Berkshire, 2020; Tienken and Mullen, 2016). Charter school supporters believe charter school students perform better than public school children on state standardized tests (Lubienski and Lubienski, 2014). Advocates for traditional public schools promote the idea that there are no significant differences between public and charter schools in academic achievement (Chen, 2020b; Fischler, 2021). This study compares public and charter elementary school students in terms of their reading and math assessment scores, both as measured by the Virginia Standard of Learning (SOL) for the 2018-2019 school year. Data were collected and analyzed on 642 students enrolled in three of Virginia's elementary charter schools and three traditional public schools in Loudoun County and Richmond City. SOL assessment data for the public and charter schools were compared for the overall student population per grade level to determine if there is a significant difference for the 2018-2019 school year. A two-way ANOVA was utilized in this study. Results indicated no significant differences in the reading mean SOL assessment scores between traditional public elementary and public charter school students: F (1, 636) = .119, p = .730. Additionally, results showed no significant interaction between school type and grade level between traditional public elementary and public charter schools: F (2, 636) = 1.076, p = .342. However, findings revealed a significant difference in the reading SOL assessment scores between grade levels of traditional public elementary schools and public charter schools: F (2, 636) = 4.473, p = .012. Furthermore, results from the math analysis indicated no statistical differences in math SOL scores between traditional public elementary schools and public charter schools: F (1, 636) = .000, p = .997. Also, findings indicated no significant difference in the math SOL scores between the grade levels of traditional public elementary and public charter schools: F (2, 636) = .520, p = .595. / Doctor of Education / Advocates of privatizing education suggest that traditional public "brick-and-mortar" schools are not adequately preparing students for college, career readiness, and global citizenship (Lobosco, 2019; Tienken and Mullen, 2016; Schneider and Berkshire, 2020). Charter school supporters believe charter school students perform better than public school children on state standardized tests (Lubienski and Lubienski, 2014). Advocates for traditional public schools promote the idea that there are no significant differences between public and charter schools in academic achievement (Chen, 2020b; Fischler, 2021). This study compares public and charter elementary school students in terms of their reading and math assessment scores, both as measured by the Virginia Standard of Learning (SOL) for the 2018-2019 school year. Data were collected and analyzed on 642 students enrolled in three of Virginia's elementary charter schools and three traditional public schools in Loudoun County and Richmond City. SOL assessment data for the public and charter schools were compared for the overall student population per grade level to determine if there is a significant difference for the 2018-2019 school year. This study did not reveal any significant differences in reading and math SOL scores between traditional elementary public schools and public elementary charter schools. However, findings in this study revealed significant differences in reading SOL scores on average among grade levels. Conversely, findings did not reveal any differences in math SOL assessment scores on average between grade levels of traditional public elementary school and public elementary charter school students.

abstract: This study tested the effects of two kinds of cognitive, domain-based preparation tasks on learning outcomes after engaging in a collaborative activity with a partner. The collaborative learning method of interest was termed "preparing-to-interact," and is supported in theory by the Preparation for Future Learning (PFL) paradigm and the Interactive-Constructive-Active-Passive (ICAP) framework. The current work combined these two cognitive-based approaches to design collaborative learning activities that can serve as alternatives to existing methods, which carry limitations and challenges. The "preparing-to-interact" method avoids the need for training students in specific collaboration skills or guiding/scripting their dialogic behaviors, while providing the opportunity for students to acquire the necessary prior knowledge for maximizing their discussions towards learning. The study used a 2x2 experimental design, investigating the factors of Preparation (No Prep and Prep) and Type of Activity (Active and Constructive) on deep and shallow learning. The sample was community college students in introductory psychology classes; the domain tested was "memory," in particular, concepts related to the process of remembering/forgetting information. Results showed that Preparation was a significant factor affecting deep learning, while shallow learning was not affected differently by the interventions. Essentially, equalizing time-on-task and content across all conditions, time spent individually preparing by working on the task alone and then discussing the content with a partner produced deeper learning than engaging in the task jointly for the duration of the learning period. Type of Task was not a significant factor in learning outcomes, however, exploratory analyses showed evidence of Constructive-type behaviors leading to deeper learning of the content. Additionally, a novel method of multilevel analysis (MLA) was used to examine the data to account for the dependency between partners within dyads. This work showed that "preparing-to-interact" is a way to maximize the benefits of collaborative learning. When students are first cognitively prepared, they seem to make the most efficient use of discussion towards learning, engage more deeply in the content during learning, leading to deeper knowledge of the content. Additionally, in using MLA to account for subject nonindependency, this work introduces new questions about the validity of statistical analyses for dyadic data. / Dissertation/Thesis / Ph.D. Educational Psychology 2013