An SEA Guide for Identifying Evidence-Based Interventions for School Improvement

The Every Student Succeeds Act (ESSA) is the most recent reauthorization of the Elementary and Secondary Education Act and replaces the No Child Left Behind Act (NCLB). The law focuses on using research evidence to improve teaching and learning and at the same time passes considerable authority from federal to state policymakers. This means that responsibility largely falls on states and localities to effectively make sense of and use research evidence in their decisions around school improvement, teacher preparation, principal recruitment, and family engagement. With support from the Annie E. Casey Foundation, Overdeck Family Foundation, and the William T. Grant Foundation, the Florida Center for Reading Research (FCRR) has developed Guides for Identifying Evidence-Based Interventions for School Improvement

Early Literacy Instruction and Intervention

The purpose of this paper is to describe the efficacy of early literacy interventions and to discuss possible roles for volunteer tutors in helping prevent reading difficulties within the Response to Intervention process. First, we describe a landmark study that evaluated the impact of primary classroom instruction on reducing the proportion of students at risk for reading failure, and a more recent series of studies exploring the effects of individualizing classroom reading instruction based on students’ initial skills. Second, we review studies of more intensive early intervention to demonstrate how these interventions substantially reduce the proportion of students at risk. Third, we examine effective tutoring models that utilize volunteers. Finally, we discuss the potential role of community tutors in supporting primary classroom instruction and secondary interventions

Teacher characteristics, classroom instruction, and student literacy and language outcomes in bilingual kindergartners

This study investigated the relation of teacher characteristics, including ratings of teacher quality, to classroom instructional variables and to bilingual students' literacy and oral language outcomes at the end of the kindergarten year. Teacher characteristics included observational measures of oral language proficiency, quality, and classroom activity structure, as well as surveys of knowledge of reading-related skills. Student outcomes in both languages included letter naming, word reading, and phonological awareness and oral language composites. The study involved 141 teachers from a multisite project who were observed up to 3 times at the beginning, middle, and end of the year during their reading/language arts block while teaching English language learners to read in their primary language (Spanish) and/or in English. Teacher quality, but not teacher knowledge, was related positively to student engagement and negatively to time spent in noninstructional activities. Initial student and classroom performance, language of instruction and of outcomes, and teacher oral language proficiency in both Spanish and English predicted outcomes, whereas teacher quality was less related, and teacher content knowledge was consistently not related to student outcomes

Barbara Foorman interview

Webcast file name: foorman_sept16_2010Date: September 16, 2010Voice of Literacy host, Dr. Betsy Baker, interviews Dr. Barbara Foorman, Director of the Florida Center for Reading Research at Florida State University and Francis Eppes Professor of Education

Summary of the Predictive Relationship between the FAIR and the FCAT in Grades 3-10: 2010-2011

<p>The FAIR was administered throughout the state of Florida to approximately 1.5 million students in grades 3-10 in the fall, winter, and spring portions of the 2010-2011 school year. The purpose of this report is two-fold: 1) to describe the general relationship between the FAIR and the FCAT and 2) to address the screening accuracy of the FAIR (e.g., how well does FAIR predict FCAT risk status?).</p

The Unique Role of the Broad Screen in Predicting FCAT Reading Comprehension

<p>One of the most frequently asked questions concerning the Grade 3-12 version of the Florida Assessments for Instruction in Reading (FAIR) is, “How well does the FAIR Broad Screen Reading Comprehension score predict FCAT?” This is an important question to address, as part of the professional development components of FAIR training highlights that students’ previous FCAT scores and the FAIR Broad Screen are both used in calculating the FCAT Success Probability (FSP) score. The FSP provides teachers, parents, and students with an indicator that communicates the percent change that a student has of passing the FCAT Reading Comprehension portion of the FCAT-SSS at level 3 or above.<br>In order to examine the relationship between the FAIR Broad Screen scores and its unique efficiency in predicting FCAT performance, we can use two separate analyses. First, we can study the relationship between the Broad Screen and FCAT to determine what general association one score has with the other (i.e., multiple regression). Secondly, we can examine how efficient the Broad Screen is along with a students’ prior year FCAT in predicting current FCAT as opposed to solely using prior year FCAT (i.e., logistic regression). A summary of the multiple regression findings are presented in Table 1. These results show that Prior FCAT accounts for a majority of the variance in predicting current FCAT (minimum=49.5% in Grade 4, maximum=64.7% in Grade 8). When the Broad Screen is added to the Prior FCAT, it can be seen that the Broad Screen accounts for significant unique</p> <p> </p

The association between the FCAT Success Probability (FSP) from the FAIR with FCAT low achieving and high achieving performances

<p>The Florida Assessments for Instruction in Reading (FAIR) reading comprehension screen was<br>administered to approximately 1.1 million students in grades 3‐10 during the 2011‐2012 school year. As<br>the FAIR continues to be utilized by teachers around the state, questions often arise about how the FSP<br>score may be used to improved predictions of future performance on the Florida Comprehensive<br>Assessment Test (FCAT). Specifically, many teachers are eager to understand how changes in FSP scores<br>across the assessment periods (AP) may predict how a student will perform on the FCAT. The FAIR has<br>traditionally provided several score types for FAIR users to understand how students are performing,<br>including: 1) the FSP, 2) a normative standard score with a grade‐based mean of 100, 3) a percentile<br>rank, and 4) a normative ability score (i.e., the reading comprehension ability score; RCAS). The standard<br>score, percentile rank, and RCAS are normed, meaning their scores are compared to a reference group<br>of students. Of the four score types, the RCAS is the most appropriate to use for examining growth, as it<br>is specifically sensitive to changes across the year within a grade, as well as for tracking progress across<br>the grades over time.</p> <p> </p