These videos illustrate how parents and grandparents can implement the NCII reading and mathematics sample lessons to provide additional practice.
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The Academic Screening Tools Chart is comprised of evidence-based screening tools that can be used to identify students at risk for poor academic outcomes, including students who require intensive intervention. The chart displays ratings on technical rigor in the areas of classification accuracy, reliability, and validity, and provides information on the representativeness of the sample, whether a bias analysis was conducted, and key usability features. The chart is intended to assist educators and families in becoming informed consumers who can select academic screening tools that address their specific needs. The presence of a particular program on the chart does not constitute endorsement and should not be viewed as a recommendation from either the TRC on Academic Screening or NCII.
This lesson, featuring Karen McWilliams, a 504 Coordinator and Dyslexia Teacher in Rochelle ISD in Texas, supports educators in using technology to teach foundational reading skills to students in elementary grades. During this virtual literacy lesson, students engage in a variety of facilitated activities to support phonemic awareness, phoneme–grapheme correspondence, irregular and high-frequency words, writing, and connected text. Educators may present this lesson to students one-on-one or in a small group. The templates were adapted from content developed by the University of Florida Literacy Institute to support educators implementing virtual instruction. The collection includes a tip sheet, a video examples, and slides illustrating the lesson.
This is part 1 of the larger module, “Informal Academic Diagnostic Assessment: Using Data to Guide Intensive Instruction.” This part is intended to provide an overview of common general outcome measures (GOM) used for progress monitoring in reading and mathematics, with guidance on selecting an appropriate measure.
This lesson illustrates the use of Elkonin boxes in a virtual setting and includes three variations.
This example illustrates the virtual implementation of EL Education’s Decoding and Spelling assessments.
This resource developed by Sarah Thorud, Elementary Reading Specialist from Clatskanie School District in Oregon focuses on implementing screening and progress monitoring virtually. It includes guiding questions and considerations for implementation, video examples, and a sample sign-up sheet for screening and progress monitoring students virtually.
Norms for oral reading fluency (ORF) can be used to help educators make decisions about which students might need intervention in reading and to help monitor students’ progress once instruction has begun. This paper describes the origins of the widely used curriculum-based measure of ORF and how the creation and use of ORF norms has evolved over time. Using data from three widely-used commercially available ORF assessments (DIBELS, DIBELS Next, and easyCBM), a new set of compiled ORF norms for grade 1-6 are presented here along with an analysis of how they differ from the norms created in 2006.
The Academic Progress Monitoring Tools Chart is comprised of evidence-based progress monitoring tools that can be used to assess students’ academic performance, to quantify a student rate of improvement or responsiveness to instruction, and to evaluate the effectiveness of instruction. The chart displays ratings on technical rigor of performance level standards (reliability and validity) and growth standards (sensitivity, alternate forms, and decision rules) and provides information on the whether a bias analysis was conducted, and key usability features. The chart is intended to assist educators and families in becoming informed consumers who can select academic progress monitoring tools that address their specific needs. The presence of a particular tool on the chart does not constitute endorsement and should not be viewed as a recommendation from either the TRC on Academic Progress Monitoring or NCII.
This training module demonstrates how academic progress monitoring fits into the Data-Based Individualization (DBI) process by (a) providing approaches and tools for academic progress monitoring and (b) showing how to use progress monitoring data to set ambitious goals, make instructional decisions, and plan programs for individual students with intensive needs.