Psychoeducation Assessment

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timer Asked: Mar 29th, 2017

Question Description

Attached are two articles regarding Curriculum Based Measurement (CBM). Please review the articles and write a brief summary 2 pages using each article. The two articles are similar but will give you a better understand about CBM .

184 THE JOURNAL OF SPECIAL EDUCATION VOL. 37/NO. 3/2003/PP. 184–192 Developments in Curriculum-Based Measurement Stanley L. Deno, University of Minnesota Curriculum-based measurement (CBM) is an approach for assessing the growth of students in basic skills that originated uniquely in special education. A substantial research literature has developed to demonstrate that CBM can be used effectively to gather student performance data to support a wide range of educational decisions. Those decisions include screening to identify, evaluating prereferral interventions, determining eligibility for and placement in remedial and special education programs, formatively evaluating instruction, and evaluating reintegration and inclusion of students in mainstream programs. Beyond those fundamental uses of CBM, recent research has been conducted on using CBM to predict success in high-stakes assessment, to measure growth in content areas in secondary school programs, and to assess growth in early childhood programs. In this article, best practices in CBM are described and empirical support for those practices is identified. Illustrations of the successful uses of CBM to improve educational decision making are provided. The special characteristics of learners with disabilities have long driven the development of alternative specialized methods for assessing those needs. Perhaps the classic example of this phenomenon is the work of Alfred Binet, who as minister of public instruction in France, worked with Theodore Simon to explore the possibility of using different structured tasks to differentially diagnose and prescribe educational programs for students who might not profit from regular classroom instruction. Although Binet’s work subsequently was subverted by other efforts to scale intelligence, it is important to remember that Binet’s purpose was to identify more effective programs for educating students rather than excluding them. The innovation in assessment presented in this article, curriculum-based measurement (CBM; Deno, 1985), is also intended to improve educational programs. Background CBM was developed to test the effectiveness of a special education intervention model called data-based program modification (DBPM; Deno & Mirkin, 1977). That model was based on the idea that special education teachers could use repeated measurement data to formatively evaluate their instruction and improve their effectiveness. To empirically test teacher use of DBPM, a research and development program was conducted for 6 years through the federally funded University of Minnesota Institute for Research on Learning Disabilities (IRLD). One result of the IRLD formative evaluation research was the development of a generic set of progress monitoring procedures in reading, spelling, and written expression. Those procedures include specification of (a) the core outcome tasks on which performance should be measured; (b) the stimulus items, the measurement activities, and the scoring performance to produce technically adequate data; and (c) the decision rules used to improve educational programs. Ultimately, a set of criteria was specified that was used to establish the technical adequacy of the measures, the treatment validity or utility of the measures, and the logistical feasibility of the measures (Deno & Fuchs, 1987). Since then, CBM data have been used across a wide range of assessment activities, including screening, prereferral evaluation, placement in remedial and special education programs, formative evaluation, and evaluation of reintegration and inclusion. Recently, research has explored the use of CBM data to predict success on highstakes assessment and to measure growth in content areas in secondary school programs and in early childhood special education. The remainder of this article addresses the successful uses of CBM to accomplish these purposes. CBM Characteristics When the generic procedures for measurement are employed with stimulus materials drawn directly from the instructional materials used by teachers in their classrooms, the approach is referred to as curriculum-based. Because evidence has shown that the same procedures can be used successfully with stimulus materials drawn from other sources, the generic procedures have been referred to as general outcomes measures (GOMs; L. S. Fuchs & Deno, 1994) or dynamic indicators of basic skills (DIBS; Shinn, 1998). In contrast to the term curriculum-based assessment, which has been used to refer to a wide range of Address: Stanley L. Deno, University of Minnesota, Burton Hall, 178 Pillsbury Dr. S.E., Minneapolis, MN 55455; e-mail: denox001@umn.edu THE JOURNAL OF SPECIAL EDUCATION VOL. 37/NO. 3/2003 informal assessment procedures, curriculum-based measurement refers to a specific set of standard procedures that include the following characteristics. Technically Adequate The reliability and validity of CBM have been achieved through using standardized observational procedures for repeatedly sampling performance on core reading, writing, and arithmetic skills. Unlike most informal measures, the psychometric concepts of reliability and validity are primary characteristics of CBM (Good & Jefferson, 1998; Shinn, 1989). Standard Measurement Tasks (“What to Measure”) 185 Multiple Equivalent Samples One of the most distinctive and important features of CBM is that performance is repeatedly sampled across time. The repeated observations of performance are structured so that students respond to different but equivalent stimulus materials that are drawn from the same general source. For example, on the first occasion in measuring reading proficiency, students are asked to read aloud for 1 minute from a text passage that they have not previously read. On the next occasion, the students read again from the same book, but from a different, unfamiliar, and equally difficult text passage. In this way, task difficulty is held constant and inferences can be drawn regarding the generalizability of student proficiency at reading comparable, but unfamiliar, text. The standard tasks identified for use in CBM include reading aloud from text and selecting words deleted from text (maze) in reading, writing word sequences when given a story starter or picture in writing, writing letter sequences from dictation in spelling, and writing correct answers/digits in solving problems in arithmetic. Time Efficient Prescriptive Stimulus Materials Easy to Teach Because the materials used for assessment in CBM may be obtained from the instructional materials used by the local school, specifications are provided for materials selection (e.g., Shinn, 1989). Key factors in this selection process are the representativeness and equivalence of the stimulus materials. Both factors are addressed to increase the utility of the procedures for making instructional decisions. Another logistical consideration in using CBM is the ease with which professionals, paraprofessionals, and parents can learn to use the procedures in such a way that the data are reliable. Administration and Scoring (“How to Measure”) The original purpose of CBM was to enable teachers to formatively evaluate their instruction. What follows is a summary, beginning with the more common and older applications of CBM and progressing to recent applications. CBM procedures include specification of sample duration, administration, student directions, and scoring procedures. Combining the prescriptive selection of stimulus materials with standardization of the procedures is necessary to ensure sufficient reliability and utility of the data for individual and group comparisons across time. Standardization also enables summarization of group data for developing local norms and for general descriptions of program effects across students (Shinn, 1995). Performance Sampling In CBM, academic performance is sampled through the use of direct observation procedures. All CBM scores are obtained by counting the number of correct and incorrect responses made in a fixed time period. In reading, for example, the most commonly used measure requires a student to read aloud from a text for 1 minute and have an observer count the number of correctly and incorrectly pronounced words. CBM is designed for efficiency. Multiple performance sampling requires that measures be short. CBM performance samples are 1 to 3 minutes in duration, depending on the skill being measured and the number of samples necessary to maximize reliability. Common Uses Improving Individual Instructional Programs The formative evaluation model based on CBM is represented graphically in Figure 1. As can be seen in the figure, individual student performance during an initial baseline phase is plotted and a goal is established. A progress line connecting the initial level and the goal depicts the rate of improvement necessary for the student to achieve the goal. The vertical lines on the graph indicate the point at which a change is made in the student’s program. At each point, judgments are made regarding the effectiveness of the instruction being provided. This systematic approach to setting goals, monitoring growth, changing programs, and evaluating the effects of changes is the formative evaluation model. Research on the achievement effects of using this approach has revealed that the students of teachers who use systematic formative evaluation based FIGURE 1. CBM progress graph. 186 THE JOURNAL OF SPECIAL EDUCATION VOL. 37/NO. 3/2003 on CBM have greater achievement rates (L. S. Fuchs, Deno, & Mirkin, 1984). Predicting Performance on Important Criteria Teachers’ effective use of formative evaluation to increase achievement requires that CBM data be closely associated with a wide range of criteria important to making educational decisions (Good & Jefferson, 1998; Marston, 1989). All of the measures used in CBM possess relatively high-criterion validity coefficients (L. S. Fuchs, Fuchs, & Maxwell, 1988; Marston, 1989). For that reason, CBM data can be used not only to evaluate instruction but also to classify age and grade developmental status (Deno, 1985; Shinn, 2002), predict and improve on teacher judgments regarding student proficiency (Marston, Mirkin, & Deno, 1984), discriminate between students achieving typically and those in compensatory programs (Marston, & Magnusson, 1988), and predict who will succeed on high-stakes tests (Good, Simmons, & Kameenui, 2001). Recent research efforts have been successfully directed toward establishing reasonable growth standards for purposes of setting both individual and program standards (Deno, Fuchs, Marston, & Shin, 2001). Enhancing Teacher Instructional Planning Several related outcomes are also produced through a formative evaluation model based on CBM. In L. S. Fuchs, Deno, and Mirkin’s (1984) study, near the end of the school year, teachers of reading were asked whether they could identify their students’ reading goals. It is not surprising but important to note that those teachers using CBM in formative evaluation were more accurate in identifying their students’ goals. In a related study, when teachers used CBM within a formative evaluation model, it significantly affected both the frequency and quality of the instructional changes they made as they responded to unsatisfactory student progress (L. S. Fuchs, Fuchs, Hamlett, & Stecker, 1991; Fuchs, Fuchs, & Hamlett, 1993). Developing Norms CBM can be used to develop norms for decision making when the same CBMs are administered to normative peer samples. In Figure 1, individual performance can be compared to the average of peer performance, which is represented by the line well above the target student’s level during baseline and at the end of the year. This reference is important because it reveals the magnitude of the difference between the performances of individual students and those of their peers with the same stimulus materials. Teachers can create their own peer reference by sampling the performance of other students in the same classroom. Because CBM is standardized, it has also been 187 effectively used to create school and district norms. When local norms are created, peer references are more broadly representative of students in the same grade, in the same school, or across schools within a district (Marston & Magnusson, 1988; Shinn, 2002). Using CBM to create local norms has been especially useful in urban school districts where concerns exist regarding the degree to which the norms of commercially available standardized tests reflect the rapidly changing diversity of student populations. Increasing Ease of Communication Although the effectiveness of CBM in increasing both teacher and student awareness of goals has already been discussed, it is important to point out that the CBM graph, with its multiple references, creates opportunities for clearer communication. It has now become common practice for teachers to use the CBM data in parent conferences and at multidisciplinary team meetings to provide a framework for communicating individual student status. Professional educators and parents can easily use the CBM graph because little or no interpretation of the scores is necessary (Shinn, Habedank, & Good, 1993). This contrasts sharply with the complexities related to communicating the results of commercially available standardized test scores. A simple illustration of both the ease and effectiveness of communicating about CBM data can be found in the results of the teacher planning study mentioned earlier (i.e., Fuchs, Deno, & Mirkin, 1984). In that study, students as well as teachers were asked whether they knew their annual reading goals and were asked to specify those goals. Those students whose teachers were using CBM and formative evaluation not only expressed that they knew those goals but also were able to accurately specify their target reading scores. Screening to Identify Students Academically at Risk An increasingly common use of CBM is to screen students who are at risk for academic failure. As mentioned previously, because CBM procedures are standardized, they can be used to compare individual performance to that of the group. The use of local norms is common for this purpose, but norms are not required. In a study by Deno, Reschly-Anderson, Lembke, Zorka, and Callender (2002), all of the students in a large urban elementary school were given three standard CBM maze passages and their performance was aggregated within and across grades. The lowest 20% of the students on the CBM maze (multiple-choice cloze) measure in each grade were considered highly at risk and were required to undergo progress monitoring every other week with the more conventional CBM oral reading measure. Identification of high-risk students has now become commonplace among schools practicing CBM (Marston & Magnusson, 1988). 188 THE JOURNAL OF SPECIAL EDUCATION VOL. 37/NO. 3/2003 Evaluating Classroom Prereferral Interventions The cost and the consequences of special education are recurring issues in the literature of special education. Of particular concern is the possibility that some students are being referred for and placed in special education when they would succeed in general class programs with greater accommodation by classroom teachers. One approach to addressing this issue is to require classroom teachers to conduct prereferral interventions, to establish that such accommodations are insufficient. A problem with this approach has been that little useful data have been available to appraise the effects of those prereferral data. Because CBM data are sensitive to the effects of program changes over relatively short time periods, they can be used to aid in the evaluation of prereferral interventions. The use of CBM in evaluating prereferral interventions is the first component of the Problem Solving Model (Deno, 1989) that has been implemented at both the state and district levels (Shinn, 1995; Tilly & Grimes, 1998). The Problem Solving Model enables general and special educators to collaborate in the early stages of child study to determine with some validity that the problems of skill development faced by a student are more than “instructional failures.” Documentation stating that the problem is not readily solvable by the classroom teacher becomes the basis for special education eligibility assessment. Reducing Bias in Assessment The Problem Solving Model using CBM has attracted attention as a means for reducing bias in the assessment process. Because teachers typically are the source of referrals to special education, their validity as “tests” of student success in the classroom is an issue that has been examined using CBM (Shinn, Tindal, & Spira, 1987). Indeed, in one big city school system, the Office of Civil Rights joined forces with the district to examine whether the CBM data used as part of the Problem Solving Model could diminish the likelihood of minority students being inappropriately placed in special education (Minneapolis Public Schools, 2001). Data from that school district revealed that after implementation of the model, the proportion of non-White students referred for and placed in special education did not substantially change, but it became more likely that problems were addressed through general education classroom intervention than through special education placement. In addition, students who were placed in special education demonstrated lower achievement test scores than they had prior to the introduction of the Problem Solving Model. Offering Alternative Special Education Identification Procedures There has been widespread dissatisfaction with traditional approaches to identifying students for special education that rely on standardized tests of ability, achievement, or both (Reschly, 1988). Despite this dissatisfaction, few alternatives have been offered to replace these procedures. Over the past 20 years, the use of CBM within a systematic decision framework has been explored as a basis for developing alternative identification procedures (Marston & Magnusson, 1988; Marston, Mirkin, & Deno, 1984; Shinn, 1989). Recently, the use of CBM to test students’ responsiveness to treatment (L. S. Fuchs & Fuchs, 1998) has gained favor within policy-making groups. For example, the responsiveness to treatment approach has been recommended by the President’s Commission on Excellence in Special Education (2002) as an alternative to traditional standardized testing for identifying students with learning disabilities. That approach is an extension of prereferral evaluation and the Problem Solving Model to evaluate increased levels of intensity in instructional intervention, and it relies on CBM. For example, if a student fails to increase his or her rate of growth in response to several general education classroom interventions, that student might be considered as eligible for special education. This alternative approach to eligibility determination rooted in the Problem Solving Model has created an entirely different perspective of the concept of disability (Tilly, Reschly, & Grimes, 1999). Recommending and Evaluating Inclusion As increased emphasis has been placed on inclusion of students with disabilities in general education classrooms, and as laws and regulations have required schools to ensure access to the general education curriculum, the need to evaluate the effects of these changes on the academic development of students with disabilities has increased. CBM has proved to be a very useful tool for those accountable for the progress of students with disabilities as they seek to provide education for these students in the mainstream curriculum. The general strategy employed when using CBM to evaluate inclusion has been to collect data before and after integration into general education instruction and then to continue monitoring student progress to ensure that reintegration of students is occurring responsibly (D. Fuchs, Roberts, Fuchs, & Bowers, 1996; Powell-Smith & Stewart, 1998). The results of the research in this area provide clear evidence that both special educators and classroom teachers can use CBM to provide ongoing documentation of student progress and to signal the need for increased intensification of instruction when inclusive programs are unsuccessful. Predicting Performance on High-Stakes Assessment Perhaps no other aspects of contemporary education are receiving greater attention than accountability and high-stakes assessment. At federal and state levels, pressure is being applied to schools to “step up” to the challenge of reform movements rooted in testing. Schools are being placed on “pro- THE JOURNAL OF SPECIAL EDUCATION VOL. 37/NO. 3/2003 bation” and being threatened with the prospect of reconstitution (i.e., disbursement and replacement of the existing school staff). In this environment, the annual high-stakes summative evaluations have become a kind of Sword of Damocles hanging over the heads of teachers and administrators everywhere. Whatever one might think about this approach to improving education, one rational response has been to seek progressmonitoring data that enable school staff members to formatively evaluate programs and revise them when they appear to be unsuccessful in helping students pass the annual highstakes tests. The criterion validity of CBM data has become the basis for making judgments about whether students will achieve mandated levels of performance on benchmark tests. In a variety of studies, high correlations (.65–.85) have been obtained between CBM scores for reading and math and performance on high-stakes assessments (cf. Deno et al., 2002; Good, Simmons, & Kameenui, 2001; Muyskens & Marston, 2002). A related, noteworthy aspect of the research and development in this area has been the movement from computing simple correlations to identifying criterion levels of performance on the CBMs that teachers can use as targets for performance. Evidence has accumulated, for example, regarding the relationship between CBM reading scores and pass rates on state assessments. Students reading at least 40 words correctly in 1 minute by the end of first grade are on a trajectory to succeed in learning to read, and students reading more than 110 words correctly in 1 minute by the beginning of third grade are most likely to pass their state assessments in Oregon (Good et al., 2001). Eighth-grade students who can read at least 145 words from local newspaper passages correctly in 1 minute are almost certain to pass the Minnesota Basic Skills Test in reading (Muyskens & Marston, 2002). Preliminary research has been, and continues to be, conducted to identify criterion levels of performance on the CBM maze and math measures, as well. Measuring Growth in Secondary School Programs and Content Areas CBM was developed initially to help teachers at the elementary school level increase the achievement of students struggling to learn basic skills in reading, writing, and arithmetic. As development in those areas has proceeded, teachers in secondary school programs have become interested in the application of similar formative evaluation approaches with their students. For that reason, technical work has proceeded on establishing CBM progress monitoring methods for assessing student growth both in advanced academic skills and in content area learning (Espin, Scierka, Skare, & Halvorson, 1999; Espin & Tindal, 1998). The technical developments in using CBM methods to assess growth in reading and writing at the secondary level have generated outcomes that appear both promising and tentative. In general, attempts to establish the criterion validity of the same reading and writing measures 189 that have been used at the elementary level have revealed that those measures do correlate with important criteria (e.g., test scores, grade point average, teacher judgment), but the correlations are not as strong as for elementary students. One exception involves a recent study conducted by Muyskens and Marston (2002) in which correlations were high for students in eighth grade. That research was conducted with middle school students, rather than high school students, so it is possible that further studies will identify those upper levels of competence for which ordinary CBMs will be effective. Assessing English Language Learning Students A particular problem confronting schools in the United States is the dramatically increasing proportion of students whose first language is not English and who are still learning to speak English while they are learning to read and write in English. Commercially available standardized tests have not been useful because they have not included the full range of languages represented among English language learning (ELL) students within their norm samples. More significant, many achievement tests draw heavily on background knowledge of the American culture in structuring questions. Among other problems that exist because of the lack of technically adequate procedures is how to distinguish ELL students who are having difficulty learning because of their lack of proficiency in English from ELL students whose struggles also stem from special disabilities. Several studies have explored the use of CBM to overcome the problems of assessing ELL students and to monitor their growth in mainstream classrooms. Baker and colleagues (i.e., Baker & Good, 1995; Baker, Plasencia-Peinado, & LezcanoLytle, 1998) have focused primarily on using the CBM reading scores of Spanish-speaking ELL students to evaluate their progress in general education programs. That research establishes levels of reliability and validity for the CBM procedures with ELL students in both their native and English languages that are comparable to those of native speakers of English. Furthermore, longitudinal analyses have revealed that students who begin with comparable proficiency in English often acquire English language skills at very different rates. The apparent technical adequacy of CBM has led at least one urban school system to use CBM procedures for developing norms across reading, writing, and arithmetic on their ELL students (M. Robinson, personal communication). CBM also has been used to predict differences in the success rates of middle school ELL students on state assessments as a function of their level of reading proficiency (Muyskens & Marston, 2002). In addition, research has been conducted using CBM with students in countries where languages other than English are spoken. The evidence from this body of research indicates that the procedures and tasks to be used for measurement need to be consistent with formal differences in the language. For example, oral reading can be used to measure growth in other phonetic 190 THE JOURNAL OF SPECIAL EDUCATION VOL. 37/NO. 3/2003 languages, such as Korean, but the maze procedure appears to be more appropriate for measuring growth in an iconic language, such as Chinese (Yeh, 1992). Predicting Success in Early Childhood Education The criterion validity of CBM oral reading scores has been sufficiently established to become an important criterion for establishing the predictive validity of prereading measures and the effectiveness of early literacy interventions. With the ascendant interest in the role played by phonological skills in learning to read, the utility of scores from measures of phonological skill has been established by examining their accuracy in predicting beginning oral reading scores (Kaminski & Good, 1996). As cited in Good, Simmons, and Kameenui (2001), evidence has developed that CBM oral reading performance at the end of first grade is a significant indication of subsequent reading success. Research in this area has established important linkages among measures of phonological skill in kindergarten, oral reading performance in Grades 1 through 3, and success on state assessments. Frequency of Use At least two studies have been conducted to examine the factors that can function as barriers to CBM implementation (Wesson, Deno, & King, 1984; Yell, Deno, & Marston, 1992). More than 15 years ago, Wesson et al. (1984) found that nearly 85% of the 300 teachers surveyed reported they were aware of direct and frequent measurement of student progress; yet, only half of those familiar with the procedures were using them. In Yell et al.’s (1992) study, only teachers using CBM were surveyed. Teachers in both studies consistently identified time as the single most important barrier to implementing the measurement procedures. An interesting related finding was that teachers using CBM estimated that it took less than 10% of their instructional time to conduct the measurement. Nevertheless, given the time constraints under which teachers operate, they seem, inevitably, to believe that any additional activity cannot be accommodated into their daily schedule. A Uniquely Special Education Development CBM is a procedure that was developed by special educators for special educators. Having said that, it is important to recognize that related work both in and outside of special education served as a basis for CBM and supported the use of CBM in general education. All CBM procedures involve the direct observation of behavior and use the single case analytical procedures that are characteristic of applied behavior analysis (ABA; Deno, 1997). ABA is a system developed for use with any behavior in any setting; thus, much of the work of ABA has addressed behavior in the mainstream of ordinary life. In that sense, CBM is, in part, based on procedures derived from sources outside of special education. At the same time, the most extensive applications of ABA have been in special education, and the early applications of ABA to academic instruction occurred most often within special education (e.g., Lovitt, 1976). The use of CBM to measure growth in reading has relied extensively on time-limited samples of oral reading. In the general literature of reading development, the speed with which students are able to translate text into spoken language is viewed as one of the most significant characteristics of skillful reading (Adams, 1990). In addition, psychologists interested in the study of reading have long viewed automatic responding as an essential element in reading comprehension (Laberge & Samuels, 1974). Although oral reading fluency is not always defined in terms of speed and accuracy of word recognition, that use of the term is so widespread that the recommendations from the National Reading Panel (2000) regarding fluency have been interpreted to mean speed and accuracy of oral reading. However oral reading fluency is defined, the current broad interest in this subject has contributed to the rapid dissemination of CBM reading procedures. As continued research on the relationship between rapid and accurate reading of words and comprehension reveals the close connection between these key elements of reading (L. S. Fuchs, Fuchs, Hosp, & Jenkins, 2001; Jenkins, Fuchs, von den Broek, Espin, & Deno, 2002), CBM is likely to become an everincreasing source of interest from special and general educators alike. Whether similar accelerated interest in CBM will occur for other basic skills remains to be seen. The most effective uses of CBM in the formative evaluation of individual student programs almost certainly occur in settings where individual (special) education teachers have the time and skills to respond to the charted progress of individual students. Special educators designed the formative evaluation model that has been demonstrably effective in improving the achievement of individual students for use in special education. Initially, this meant evaluating the success of teachers at accelerating the progress of their special education students in the mainstream curriculum. As caseload limits for special educators have been raised or eliminated, and as inclusive education has received more attention, teachers have had less time and too many students to use CBM effectively in formative evaluation. The shift, then, has been to use CBM to support general educators’ efforts to accommodate the increased diversity in classrooms produced, in part, by inclusion of students with disabilities (L. S. Fuchs, Fuchs, Hamlett, Phillips, & Bentz, 1994). CBM has proven to be a useful tool for this purpose. L. S. Fuchs and Fuchs (1998) provided an interesting and important illustration of the efforts required to tailor CBM for use in the general education classroom. Their work clearly demonstrates the effort that must be made to effect CBM im- THE JOURNAL OF SPECIAL EDUCATION VOL. 37/NO. 3/2003 plementation with teachers who are working with large groups of students in general education classrooms. Even as those efforts are successful, it is unlikely that CBM with large groups can contribute to improved student achievement to the degree that it does when used to tailor individual student programs. In those settings where special education is organized for individual students, the unique contributions of CBM most certainly will be the greatest. REFERENCES Adams, M. J. (1990). Beginning to read: Thinking and learning about print. Cambridge: MIT Press. Baker, S. K., & Good, R. H. (1995). Curriculum-based measurement of English reading with bilingual Hispanic students: A validation study with second-grade students. School Psychology Review, 24, 561–578. Baker, S. K., Plasencia-Peinado, J., & Lezcano-Lytle, V. (1998). The use of curriculum-based measurement with language-minority students. In M. R. Shinn (Ed.), Advanced applications of curriculum-based measurement (pp. 175–213). New York: Guilford Press. Deno, S. L. (1985). Curriculum-based measurement: The emerging alternative. Exceptional Children, 52, 219–232. Deno, S. L. (1989). Curriculum-based measurement and alternative special education services: A fundamental and direct relationship. In M. R. Shinn (Ed.), Curriculum-based measurement: Assessing special children (pp. 1–17). New York: Guilford Press. Deno, S. L. (1997). “Whether” thou goest: Perspectives on progress monitoring. In E. Kameenui, J. Lloyd, & D. Chard (Eds.), Issues in educating students with disabilities (pp. 77–99). Mahwah, NJ: Erlbaum. Deno, S. L., & Fuchs, L. S. (1987). Developing curriculum-based measurement systems for databased special education problem solving. Focus on Exceptional Children, 19(8), 1–16. Deno, S. L., Fuchs, L. S., Marston, D. B., & Shin, J. (2001). Using curriculum-based measurement to establish growth standards for students with learning disabilities. School Psychology Review, 30, 507–524. Deno S. L., & Mirkin, P. K. (1977). Data-based program modification: A manual. Reston, VA: Council for Exceptional Children. Deno, S. L., Reschly-Anderson, A., Lembke, E., Zorka, H., & Callender, S. (2002). A model for school wide implementation: A case example. Paper presented at the annual meeting of the National Association of School Psychology, Chicago, IL. Espin C. A., Scierka, B. J., Skare, S. S., & Halvorson, N. (1999). Criterionrelated validity of curriculum-based measures in writing for secondary students. Reading and Writing Quarterly, 15, 5–28. Espin, C. A., & Tindal, G. (1998). Curriculum-based measurement for secondary students. In M. R. Shinn (Ed.), Advanced applications of curriculum-based measurement (pp. 214–253). New York: Guilford Press. Fuchs, D., Roberts, P. H., Fuchs, L. S., & Bowers, J. (1996). Reintegrating students with learning disabilities into the mainstream: A two-year study. Learning Disabilities Research & Practice, 11, 214–229. Fuchs, L. S., & Deno, S. L. (1994). Must instructionally useful performance assessment be based in the curriculum? Exceptional Children, 61, 15–24. Fuchs, L. S., Deno, S., & Mirkin, P. (1984). Effects of frequent curriculumbased measurement and evaluation on pedagogy, student achievement, and student awareness of learning. American Educational Research Journal, 21, 449–460. Fuchs, L. S., & Fuchs, D. (1998). Treatment validity: A unifying concept for reconceptualizing the identification of learning disabilities. Learning Disabilities Research & Practice, 13, 204–219. Fuchs, L. S., Fuchs, D., & Hamlett, C. L. (1993). Technological advances linking the assessment of students’ academic proficiency to instructional planning. Journal of Special Education Technology, 12, 49–62. Fuchs, L. S., Fuchs, D., Hamlett, C. L., Phillips, N. B., & Bentz, J. (1994). Class wide curriculum-based measurement: Helping general educators 191 meet the challenge of student diversity. Exceptional Children, 60, 518–537. Fuchs, L. S., Fuchs, D., Hamlett, C. L., & Stecker, P. M. (1991). Effects of curriculum-based measurement and consultation on teacher planning and student achievement in mathematics operations. American Educational Research Journal, 28, 617–641. Fuchs, L. S., Fuchs, D., Hosp, M., & Jenkins, J. R. (2001). Oral reading fluency as an indicator of reading competence: A theoretical, empirical, and historical analysis. Scientific Studies of Reading, 5, 239–256. Fuchs, L. S., Fuchs, D., & Maxwell, L. (1988). The validity of informal reading comprehension measures. Remedial and Special Education, 9, 20–28. Good, R., & Jefferson, G. (1998). Contemporary perspectives on curriculumbased measurement validity. In M. R. Shinn (Ed.), Advanced applications of curriculum-based measurement (pp 61–88). New York: Guilford Press. Good, R. H. III, Simmons, D. C., & Kameenui, E. J. (2001). The importance and decision-making utility of a continuum of fluency-based indicators of foundational reading skills for third-grade high stakes outcomes. Scientific Studies of Reading, 5, 257–288. Jenkins, J. R., Fuchs, L. S., van den Broek, P., Espin, C. A., & Deno, S. L. (2002). Reading fluency: Criterion validity and sources of individual difference. Unpublished manuscript. Kaminski, R. A., & Good, R. H. (1996). Toward a technology for assessing early literacy skills. School Psychology Review, 25, 215–227. Laberge, D., & Samuels, S. J. (1974). Toward a theory of automatic information processing in reading. Cognitive Psychology, 6, 293–323. Lovitt, T. C. (1976). Applied behavior analysis techniques and curriculum research: Implications for instruction. In N. G. Haring & R. L. Schiefelbush (Eds.), Teaching special children (pp. 112–156). New York: McGrawHill. Marston, D. B. (1989). Curriculum-based measurement: What it is and why do it? In M. R. Shinn (Ed.), Curriculum-based measurement: Assessing special children (pp. 18–78). New York: Guilford Press. Marston, D. B., & Magnusson, D. (1988). Curriculum-based assessment: District-level implementation. In J. Graden, J. Zins, & M. Curtis (Eds.), Alternative educational delivery systems: Enhancing instructional options for all students (pp. 137–172). Washington, DC: National Association of School Psychologists. Marston, D. B., Mirkin, P. K., & Deno, S. L. (1984). Curriculum-based measurement: An alternative to traditional screening, referral, and identification. The Journal of Special Education, 18, 109–117. Minneapolis Public Schools. (2001). Report of the external review committee on the Minneapolis Problem Solving Model. Muyskens, P., & Marston, D. B. (2002). Predicting success on the Minnesota Basic Skills Test in reading using CBM. Unpublished manuscript, Minneapolis Public Schools. National Reading Panel. (2000). Teaching children to read: An evidencebased assessment of the scientific research literature on reading and its implications for reading instruction: Reports of the subgroups. Bethesda, MD: National Institutes of Health. Powell-Smith, K. A., & Stewart, L. H. (1998). The use of curriculum-based measurement on the reintegration of students with mild disabilities. In M. R. Shinn (Ed.), Advanced applications of curriculum-based measurement (pp. 254–307). New York: Guilford Press. President’s Commission on Excellence in Special Education. (2002). A new era: Revitalizing special education for children and their families. Retrieved from http://www.ed.gov/inits/commissionsboards/whspecialeducation/reports/index.html Reschly, D. (1988). Special education reform: School psychology revolution. School Psychology Review, 17, 459–475. Shinn, M. R. (Ed.). (1989). Curriculum-based measurement: Assessing special children. New York: Guilford Press. Shinn, M. (1995). Best practices in curriculum-based measurement and its use in a problem-solving model. In J. Grimes & A. Thomas (Eds.), Best practices in school psychology (Vol. 3, pp. 547–568). Silver Spring, MD: National Association of School Psychologists. 192 THE JOURNAL OF SPECIAL EDUCATION VOL. 37/NO. 3/2003 Shinn, M. R. (Ed.). (1998). Advanced applications of curriculum-based measurement. New York: Guilford Press. Shinn, M. (2002). Best practices in using curriculum-based measurement in a problem-solving model. In A. Thomas & J. Grimes (Eds.), Best practices in school psychology (Vol. 4, pp. 671–697). Silver Spring, MD: National Association of School Psychologists. Shinn, M. R., Habedank, L., & Good, R. H. (1993). The effects of classroom reading performance data on general education teachers’ and parents’ attitudes about reintegration. Exceptionality, 4, 205–228. Shinn, M. R., Tindal, G., & Spira, D. (1987). Special education referrals as an index of teacher tolerance: Are teachers imperfect tests? Exceptional Children, 54, 34–40. Tilly, W. D., & Grimes, J. (1998). Curriculum-based measurement: One vehicle for systematic educational reform. In M. R. Shinn (Ed.), Advanced applications of curriculum-based measurement (pp. 32–88). New York: Guilford Press. Tilly, W. D., Reschly, D. J., & Grimes, J. (1999). Disability determination in problem-solving systems: Conceptual foundations and critical components. In D. J. Reschly, W. D. Tilly, & J. Grimes (Eds.), Special education in transition: Functional assessment and noncategorical programming (pp. 221–254). Longmont, CO: Sopris West. Wesson, C., Deno, S. L., & King, R. (1984). Direct and frequent measurement of student performance: If it’s good for us, why don’t we do it? Learning Disability Quarterly, 7, 45–48. Yeh, C. (1992). The use of passage reading measures to assess reading proficiency of Chinese elementary school students. Unpublished doctoral dissertation, University of Minnesota. Yell, M., Deno, S. L., & Marston, D. E. (1992). Barriers to implementing curriculum-based measurement. Diagnostique, 18, 99–105.
research report Using Curriculum-Based Measurement to Improve Achievement Suzanne Clarke A data-driven method provides the most reliable indicator of student progress in basic academic areas. R esponse to intervention (RTI) is on the radar screen of most principals these days—finding out what it is, how it can improve teaching and learning, and what needs to be done to implement it effectively. One critical component of RTI that will require particular attention from principals is student progress monitoring, which is required in every tier of RTI. The most commonly used and well-researched method of monitoring progress is curriculum-based measurement (CBM). Nearly 30 years of empirical evidence tells us that CBM provides a valid and reliable indicator of student progress in basic academic areas, especially reading, math, and writing, and that it can have a positive impact on student achievement (Foegen, Jiban, & Deno, 2007; McMaster & Espin, 2007). Yet CBM was not commonly used by teachers, particularly in general education classrooms (Hosp & Hosp, 2003; Ardoin et al., 2004), until the advent of RTI. Research has shown that the data gathered from CBM can be used in numerous educational decisions, such as screening, eligibility for special education, and re-integration. More recently, researchers have been examining the effectiveness of CBM in other areas as well, such as predicting performance on high-stakes tests and measuring growth in content areas (Deno, 2003). Mellard and Johnson (2008) discuss the use of CBM from an RTI perspective: Within an RTI model, the types of decisions that a system of progress monitoring can inform include whether a student is making adequate progress in the general classroom, whether a student requires a more intensive level of intervention, and whether a student has responded 30 Principal n January/February 2009 successfully to an intervention and, therefore, can be returned to the general classroom. What Is CBM? “CBM is a scientifically validated form of student progress monitoring that incorporates standard methods for test development, administration, scoring, and data utilization” (Stecker & Lembke, 2005). It was developed so that teachers would have measurement and evaluation procedures that they could “use routinely to make decisions about whether and when to modify a student’s instructional program” (Deno, 1985). In contrast to standardized achievement tests, which do not provide immediate feedback, CBM tests are given frequently to track student progress toward annual goals, monitor the effectiveness of interventions, and make instructional changes as needed throughout the year. As Wright (n.d.) points out, “much of the power of CBM … seems to lie in its ability to predict in a short time whether an intervention is working or needs to be altered.” In an RTI context, CBM can help identify students in need of interventions, decide which level of intervention is www.naesp.org most appropriate, and determine if an intervention is successful (Mellard & Johnson, 2008). Unlike classroom assessments that test mastery of a single skill, each CBM test samples the year-long curriculum and, therefore, measures small student gains toward long-term goals (Stecker, Fuchs, & Fuchs, 2005; Deno, Fuchs, Marston, & Shin, 2001). For example, Bek Shakirov/Getty Images a third-grade teacher typically tests students on their mastery of multiplication immediately after completing that unit. However, the math CBM would include problems that test each skill that students are expected to master by the end of third grade (e.g., addition, subtraction, multiplication, and division problems). In this way, CBM provides educators with an overall indicator of student competence and progress in the curriculum. In addition to being an assessment tool that allows educators to frequently measure student progress in the yearlong curriculum, there are some additional benefits of CBM: n I t can provide documentation of student progress for accountability Principal n January/February 2009 31 purposes, including adequate yearly progress and individualized education programs; n It can facilitate communication about student progress with parents and other professionals; n It may result in fewer special education referrals; n It allows teachers to compare students against other students in the classroom, rather than against national norms; and n It allows schools and districts to develop local norms that can then guide teachers when interpreting data (National Center on Student Progress Monitoring, n.d.; HollandCoviello, n.d.). How Does CBM Work? One of the key aspects of CBM is that the “mechanics”—how the test is administered, the directions given to students, the procedures for scoring— are standardized (Deno & Fuchs, 1987). Standardization is important because it ensures that the data are valid and reliable indicators of a student’s proficiency, allows for individual and group data to be compared across time, and facilitates the development of local norms (Deno, 2003; Wright, n.d.). CBM probes, or tests, are easy and quick to administer, and are generally given once or twice per week. Each test is different but of equivalent difficulty. “Because CBM converts student academic behaviors into numbers (e.g., number of words read correctly per minute), teachers can easily chart the resulting data over time” (Wright, n.d.) and see when instructional changes need to be made. For example, the oral reading fluency probe has students read aloud from a passage for one minute as the teacher follows along, marking words that are read incorrectly. The number of words read correctly is recorded and graphed. It takes approximately five minutes to administer, score, and graph the result. On a CBM graph, baseline data indicate a student’s initial level of proficiency and a goal line is drawn 32 Principal n January/February 2009 to connect the baseline data to the desired year-end proficiency level. Following each CBM test, the teacher plots the student’s score on the graph to determine whether the student is scoring above or below the goal line, and uses a predetermined rule to decide if instruction needs to be modified. Using the four-point rule, for example, the teacher looks at the four most recent of the first six data points. If all four are above the goal line, the teacher raises the goal; if all four fall below the goal line, an instructional change may need to be implemented (Stecker, Fuchs, & Fuchs, 1999). Researchers have proposed several decision rules, in addition to the fourpoint rule, that educators can use to determine if a teaching change is needed. It is critical that one rule is chosen and then applied consistently across time and among all students being monitored. Teacher Support and Training Studies have shown that teachers who use CBM to monitor progress, adjust instruction, and determine the effectiveness of interventions have higher rates of student achievement and learning than those who do not use CBM (Bowman, 2003; Mellard & Johnson, 2008; Hosp & Hosp, 2003). As a principal, what factors do you need to consider and address to help prepare and support teachers in the use of CBM? One research review that examined the effect of CBM on the achievement of students with learning disabilities concluded the following:  rogress monitoring alone will not P have a significant impact on student achievement. Teachers must modify their instruction based on what the data indicate. n The use of data-based decision rules is important and they should be n Bek Shakirov/Images.com used by teachers to make necessary instructional changes. n Computer applications that collect, store, manage, and analyze data make using CBM more efficient and contribute to teacher satisfaction. n Ongoing teacher support, including a system that provides teachers with instructional recommendations, may be needed (Stecker, Fuchs, & Fuchs, 2005). While CBM is designed to be timeefficient for teachers, it is important to note that time is cited as the biggest barrier to its implementation. Teachers need time for training and practice in all aspects of CBM, such as how to administer the various probes, how to set annual performance goals, and how to analyze graphs. Actually using the data to make instructional changes may be one of the most difficult steps for teachers. Wesson (1991) suggests that as districts train teachers to use CBM, they should encourage them to meet regularly with one another, rather than with outside experts, to discuss what they are finding. A “seamless and flexible system of progress monitoring” (Wallace, Espin, McMaster, Deno, & Foegen, 2007) remains a goal of researchers. In the meantime, three decades of study have produced a significant research base of reliable and valid CBM measures that schools can use to monitor student progress and support RTI implementation. P Suzanne Clarke is an issues analyst at Educational Research Service. Her e-mail address is sclarke@ers.org. References Ardoin, S. P., Witt, J. C., Suldo, S. M., Connell, J. E., Koenig, J. L., Resetar, J. L., et al. (2004). Examining the incremental benefits of administering a maze and three versus one curriculumbased measurement reading probes when conducting universal screening. School Psychology Review, 33(2), 218-233. Bowman, L. J. (2003). Secondary educators promoting student success: Curriculumbased measurement. Retrieved February 7, 2008, from http://coe.ksu.edu/esl/ www.naesp.org lasestrellas/presentations/Lisa_CBM. ppt Deno, S. L. (1985). Curriculum-based measurement: The emerging alternative. Exceptional Children, 52(3), 219-232. Deno, S. L. (2003). Developments in curriculum-based measurement. The Journal of Special Education, 37(3), 184192. Deno, S. L., & Fuchs, L. S. (1987). Developing curriculum-based measurement systems for data-based special education problem solving. Focus on Exceptional Children, 19(8), 1-16. Deno, S. L., Fuchs, L. S., Marston, D., & Shin, J. (2001). Using curriculumbased measurement to establish growth standards for students with learning disabilities. School Psychology Review, 30(4), 507-524. Foegen, A., Jiban, C., & Deno, S. (2007). Progress monitoring measures in mathematics. The Journal of Special Education, 41(2), 121-139. Holland-Coviello, R. (n.d.). Using curriculumbased measurement (CBM) for student progress monitoring. Retrieved August 26, 2008, from www.studentprogress.org/player/ playershell.swf Hosp, M. K., & Hosp, J. L. (2003). Curriculum-based measurement for reading, spelling, and math: How to do it and why. Preventing School Failure, 48(1), 10-17. McMaster, K., & Espin, C. (2007). Technical features of curriculum-based measurement in writing: A literature review. The Journal of Special Education, 41(2), 68-84. Mellard, D. F., & Johnson, E. (2008). RTI: A practitioner’s guide to implementing response to intervention. Thousand Oaks, CA: Corwin Press and Alexandria, VA: National Association of Elementary School Principals. National Center on Student Progress Monitoring. (n.d.). Common questions for progress monitoring. Retrieved August 26, 2008, from www.studentprogress.org/ progresmon.asp#2 Stecker, P. M., Fuchs, L. S., & Fuchs, D. (1999). Using curriculum-based measurement for assessing reading progress and for making instruction decisions. Retrieved February 25, 2008, from www.onlineacademy.org/ modules/a300/lesson/lesson_3/xpages/ a300c3_40200.html Stecker, P. M., Fuchs, L. S., & Fuchs, D. (2005). Using curriculum-based measurement to improve student achievement: Review of research. Psychology in the Schools, 42(8), 795-819. Stecker, P. M., & Lembke, E. S. (2005). Advanced applications of CBM in reading: Instructional decision-making strategies manual. Washington, DC: National Center on Student Progress Monitoring. Wallace, T., Espin, C. A., McMaster, K., Deno, S. L., & Foegen, A. (2007). CBM progress monitoring within a standardsbased system. The Journal of Special Education, 41(2), 66-67. Wesson, C. L. (1991). Curriculum-based measurement and two models of followup consultation. Exceptional Children, 57(3), 246-256. Wright, J. (n.d.). Curriculum-based measurement: A manual for teachers. Retrieved February 5, 2008, from www.jimwrightonline.com/pdfdocs/ cbaManual.pdf W eb Resou rc es On the National Center on Student Progress Monitoring Web site, educators can download articles, presentations, and webinars that address a range of CBM topics, such as improving instruction with CBM and using progress monitoring to develop individualized education programs. The site also has a section for families, which includes resources that can be used with parents to explain progress monitoring. www.studentprogress.org This site offers step-by-step manuals and guides on how to use CBM, including how to administer the various probes and graph the results. It also includes forms for recording data and scoring sheets that can be downloaded. www.interventioncentral. org/htmdocs/interventions/ cbmwarehouse.php The Research Institute on Progress Monitoring Web site includes an in-depth training manual for implementing reading CBM and procedures for scoring writing samples. www.progressmonitoring.net Principal n January/February 2009 33

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