Using Curriculum‐Based Measurement to Improve Student Achievement: Review of Research
By Pamela M. Stecker, Lynn S. Fuchs, Douglas Fuchs. 2005
537 citations recorded by the source corpus.
Subfields: Developmental and Educational Psychology, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/787d603985e8a50b1fb7c49da4708cfd4d427946
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Developmental and Educational Psychology
- Douglas Fuchs
- Lynn S. Fuchs
- A. Foegen
- Donald L. Compton
- L. Moats
- S. Vaughn
- Elizabeth A. Swanson
- Erica S. Lembke
In Statistics and Probability
- Douglas Fuchs
- Lynn S. Fuchs
- Elizabeth A. Swanson
- Donald L. Compton
- Erica S. Lembke
- A. Foegen
- C. Espin
- S. Vaughn
Citations in the corpus
- Creating a Progress–Monitoring System in Reading for Middle–School Students: Tracking Progress toward Meeting High–Stakes Standards (2010, background): “…one which will need to be examined directly at both the middle-and high school level because one cannot assume that the positive results for use of the measures at the elementary-school level (see Stecker, Fuchs, & Fuchs, 2005, for a review) will necessarily replicate at the secondary-school level.”
- Learning progress assessment and goal setting: Effects on reading achievement, reading motivation and reading self-concept (2014, background): “Studies on the effectiveness of LPA using CBM have demonstrated that providing teachers with diagnostic information about their students’ progress leads to increased student achievement (Stecker et al., 2005).”
- Literature Synthesis on Curriculum-Based Measurement in Reading (2007, background): “Given the time-consuming nature of the type of approach suggested by Ardoin et al. (2005), and the positive treatment validity results reported in Stecker et al. (2005), use of passages selected from controlled sources, such as basalreading series, is probably sufficient for such classroom use.”
- Rethinking Response to Intervention at Middle and High School (2010, background): “As the Vaughn et al. (2010) study reminds us, whereas research demonstrates that validated small-group tutoring delivered in the early grades can alter the course of academic development for many children, the more serious academic deficits associated with middle and high school make large numbers o”
- Response to Intervention Screening and Progress–Monitoring Practices in 41 Local Schools (2009, methodology): “By collecting and analyzing learning and performance data, teachers and school teams are better able to make decisions about appropriate subsequent instruction, particularly for those students not succeeding (Mellard & Johnson, 2007; Stecker, Fuchs, & Fuchs, 2005).”
- Using Progress-Monitoring Data to Improve Instructional Decision Making (2008, unknown): “Moreover, research demonstrates that when teachers use CBM information to monitor student progress and make instructional changes in response to student data, students achieve significantly more than do students whose teachers use their own assessment practices (for a review, see Stecker, Fuchs, & ”
- Identifying Early Numeracy Indicators for Kindergarten and First–Grade Students (2009, methodology): “CBM is an evidence-based method for screening and progress monitoring that utilizes brief measures of academic performance that have demonstrated technical adequacy to improve student achievement (Fuchs & Fuchs, 1986; Stecker, Fuchs, & Fuchs, 2005).”
- Progress Monitoring Measures in Mathematics (2007, unknown): “These counterintuitive patterns in the Stage 3 research have been discussed by Stecker et al. (2005); further research on the dynamics of expert consultation and research training are warranted.”
- Special Education Research Advances Knowledge in Education (2015, background): “It also requires teacher training in not only assessment administration but also charting and interpreting scores so that teachers use the data to both determine when a goal is met and also consider the data slope in a predictive fashion to estimate whether students are on target toward meeting long”