Instructing Adolescents with Learning Disabilities ...

Instructing Adolescents with Learning Disabilities: Converting a Meta-Analysis to Practice H. Lee Swanson and Donald Deshler

Abstract A previous meta-analysis indicated that eight instructional factors— Questioning, Sequencing and Segmentation, Skill Modeling, Organization and Explicit Practice, Small-Group Setting, Indirect Teacher Activities (e.g., homework), Technology, and Scaffolding— captured the majority of successful intervention programs for adolescents with learning disabilities (LD). Most important was the Organization/Explicit factor, which contributed significant variance (16%) to effect size. This factor included two important instructional components: advance organization and explicit practice. In this article, we convert these findings into practical guidelines to direct instructional practice.

A

dolescents with learning disabilities (LD) are a heterogeneous group, and therefore no general instructional model can be recommended for all of them. However, some common general principles for teaching adolescents with LD have emerged in the scientific literature, and effective programs capitalize on these principles (Bulgren, Deshler, Schumaker, & Lentz, 2000; Deshler, 1998; Swanson, 2001). Although these principles often operate in different ways with different students in different content areas and different settings, nevertheless these principles underlie effective remediation programs for such students. In this article, we summarize findings related to a metaanalysis of educational intervention research for adolescents with LD (Swanson & Hoskyn, 2001), paying particular attention to the instructional principles that underlie the most effective intervention programs (see Levin, 1986, and Swanson, 1989, 1993, for a review of instructional principles derived from basic research). We then translate these findings to instructional practice. There are at least two reasons

why this translation would be helpful to teachers. First, teachers who work with adolescents with LD consistently face the challenge of keeping them in school and keeping them engaged in the learning process. Because of the enormous demands presented by the general education curriculum, it is a struggle to prepare these adolescents to successfully respond to heavy curriculum demands at the middle school and high school levels. The magnitude of this challenge is underscored by the findings of the National Longitudinal Transition Study (Wagner, Blackorby, & Hebbeler, 1993). Not only does a disproportionate percentage of adolescents with LD drop out of school compared to the general education population, but many of these students evidence a broad array of performance and adjustment problems, including higher rates of absenteeism, lower grade point averages, higher course failure rates, more prevalent feelings of low self-esteem (Wagner et al., 1993), and higher rates of inappropriate social behaviors (Schumaker, 1992) than the student population at large. In short,

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the majority of adolescents with LD are ill prepared to succeed in high school and beyond. To meet these challenges, teachers need to provide students with instruction organized around researchvalidated principles. Second, several recent trends have exacerbated the designing of effective instructional programs for these students. Foremost among these trends are 1. the expectation that all learners, including those with LD, meet curriculum standards adopted by states and professional organizations (Erickson, Ysseldyke, Thurlow, & Elliot, 1998); 2. the prevailing practice of including students with LD in the general education classroom for the vast majority of the school day (Hock, Schumaker, & Deshler, 1999; Wagner et al., 1993); 3. the explosion of knowledge and information and the growing expectation that all students not merely acquire but integrate thinking skills within subject areas (e.g., history, science) in authentic

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problem-solving activities (Kameenui & Carnine, 1998); and 4. the clear expectation set forth in the Individuals with Disabilities Education Act (IDEA) Amendments of 1997 that programming for students with disabilities be outcome based within the context of successfully mastering—and not merely gaining access to—the general education curriculum (Turnbull, Rainbolt, & Buchele-Ash, 1997).

Review of Meta-Analysis Before translating the findings related to the meta-analysis to practice, a selective review of those findings is necessary. This review provides the reader with a context for the breadth of the analysis and a rationale for why some components of instruction are more important than others. Meta-analysis is a statistical reviewing technique that provides a quantitative summary of findings across an entire body of research (Cooper & Hedges, 1994). The results of individual studies are converted to a standardized metric or effect size. The scores are then aggregated across the sample of studies to yield an overall estimate of effect size. In this context, the effect size is used to examine the differences between an experimental group and a control group. Particular attention is given to the magnitude of the effect size estimate. According to Cohen (1988), .80 is considered a large effect size estimate, .50 a moderate estimate, and .20 a small estimate. The meta-analysis of Swanson and Hoskyn (2001) drew data from a comprehensive meta-analysis on the experimental intervention literature for students with LD (Swanson, 1999a, 2001; Swanson & Hoskyn, 1998). This portion of the data set included a collection of group design studies (N = 93) published between 1963 and 1997 that focused on experimental interventions for adolescents with LD, ages 12 to 18. These studies were selected based on a

number of criteria, but emphasis was given to high methodological quality (e.g., all studies had a well-planned instructional control condition). The mean effect size of aggregated measures across the 93 studies was .80 (SD = .57; range = .11–2.76). According to Cohen’s (1988) threshold of .80 for a large effect, this meta-analysis suggests that various instructional approaches have a significant beneficial effect for adolescents with LD. The majority of these studies (90%) focused on reading (e.g., comprehension, vocabulary; 44%); mathematics (8%); writing/spelling (26%); and cognitive processing (e.g., metacognition, memory; 12%). A prototypical intervention study included 40 minutes of daily instruction four times a week over 20 sessions. The typical sample size for a study was 25 adolescents who ranged in age from 11 to 17. Mean standard scores of those studies that reported psychometric information included average IQ scores (M = 96) and below-average standard scores in reading (M = 84). The most important contribution of the Swanson and Hoskyn (2001) metaanalysis was the uncovering of key components of instruction. This was probably the most difficult aspect of the analysis for two reasons. First, any array of instructional components identified in a study would be limited by the coding procedure selected. Although the array of instructional components evaluated by Swanson and Hoskyn was gleaned from several comprehensive reviews of the instructional literature that reflected various theoretical orientations, the components coded may not have matched the components emphasized by the original authors. Second, descriptions of the same teaching practice may vary considerably by authors of different theoretical orientations, thereby introducing some artifacts in the coding procedure. This issue has been addressed in previous studies (e.g., Swanson, 1999a, 1999b; Swanson, Carson, & Lee, 1996; Swanson & Hoskyn, 1998) by using multiple examples for each

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component category, using several terms that share key concepts, creating hierarchical (categories within categories) and overlapping (allowing various degrees of overlap) categories, and coding by representation rather than by the absolute quantity of statements within a category (see Swanson, 1999b, footnote 4, p. 527). Nevertheless, attempts were made in the present synthesis to match treatment classifications with the authors’ general theoretical model or label of the treatment conditions (see Swanson & Hoskyn, 1998, pp. 284–286, for a discussion). It is important to note that one theoretical model that emerged frequently in the meta-analysis was related to strategy instruction. Most of these studies held to the view that access to knowledge is underused by adolescents with LD unless they are explicitly prompted to use certain strategies (see Swanson, 1993, for a review). Thus, students with LD are primarily seen as inefficient processors of information. Within this context, strategy instruction was broadly defined in the meta-analysis to include those studies that used, in their experimental condition, teaching methods organized in such a manner as to solve a problem. These teaching methods included two or more goal-oriented tactics (see Palincsar, Winn, David, Snyder, & Stevens, 1993, for another example of a broad application of strategy instruction). A tactic reflected a single processing technique (such as elaboration) or a means of monitoring information (such as reducing information-processing demands with prompts or cues). These tactics were usually mediated by the teacher, text, or peers or generated by the student. Thus, studies that used methods that combined two or more goal-oriented tactics (e.g., elaboration was coupled with verbal dialogue between teacher and students in a small group) were considered a form of strategy instruction. There are several excellent examples of strategy instruction models in the literature (see Montague, 1997; Scruggs & Mastropieri, in press; Wong, Butler, Harris, & Graham, in press, for

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reviews). Principles related to strategy instruction models that emanate from basic research are also outlined in Swanson (1993) and Levin (1986). Another difficulty encountered in isolating the key components of instruction was whether to focus on the content of instruction or on the activities of instruction. Swanson and Hoskyn (1998) decided, after several preliminary analyses, not to focus on the independent variables as to what was taught (e.g., inferential comprehension, editing); rather, they focused on how information was taught and sustained. Quite simply, they focused on how to influence good information processing (Pressley, 1991; Pressley, Borkowski, & Schneider, 1989). They reasoned that one cannot adequately assess what should be taught unless one can clearly identify how information should be taught, sustained, and retrieved. As shown by their previous syntheses (Swanson & Hoskyn, 1998), there are tremendous differences in instructional activities that moderate treatment outcomes. Unless these variables are identified and their influence on outcomes clearly delineated, testing what should or should not be taught— or more appropriately, what information content should or should not be emphasized—becomes a moot point. No doubt, good information processing is situated in the interplay between the knowledge base of the student, the nature of the content, and the context that constrains or activates learning. However, even when analyzing direct instruction models with explicit content variations (e.g., Necheochea & Swanson, in press, reviewed all NICHD-funded reading interventions that varied the content of phonics instruction), instructional activities (e.g., advance organizers, explicit practice) accounted for the majority of variance in treatment outcomes and, therefore, serve as an important focus of analysis. The two aforementioned issues aside, which instructional components characterized effective instructional programs? To answer this question, Swanson and Hoskyn (1998) first nar-

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rowed a large array of instructional components to 18. These are listed in Table 1 (see Swanson, 2001, for a detailed description). As the reader may surmise from Table 1, these components can be associated with a multitude of instructional models. Those components most often associated with strategy instruction programs are reflected in Components 4, 8, 9, 11, 13, 15, and 17 (e.g., Graham & Harris, 1989). For example, the advance organizer (Component 1) characterizes treatment approaches that activate prior knowledge or provide a precursor to the main instructional activity, as in Meichenbaum’s (1977) cognitive– behavioral model. Another example is Component 3, reflecting the control of the difficulty or processing demands of a task, including variations in teacher support (e.g., the teacher provided necessary assistance; tasks sequenced from easy to difficult; help was provided to the student that covaried with the learner ’s ability) and mediated scaffolding; this component characterized reciprocal teaching (e.g., Palincsar & Brown, 1984). More generally, following an explicit set of steps and prompts to ensure the activation of specific mental processes (strategy cues) is considered an important activity that underlies most strategy instruction programs (Rosenshine, 1995). Table 1 also shows the percentage of studies in the meta-analysis that included each of the 18 components. As shown in the right-hand column of Table 1, more than 40% of all the studies included instructional components that related to sequencing, new content/skills, task reduction, one-to-one instruction, control of task difficulty, technology, and large-group learning. More infrequently (< 15%) reported instructional components related to attribution training, explicit reinforcement, peer modeling, elaboration, and supplements to teacher instruction. When all these variables were entered into a regression equation, they accounted for approximately 30% of the variance in the positive outcomes (increases in effect size).

The difficulty with this “everything but the kitchen sink” analysis, of course, is that the independent contribution of particular components to effect sizes is unclear. This is an important issue, given the fact that teachers have a limited time to work with students and, therefore, must be parsimonious in their selection of instructional activities. To address this issue, Swanson and Hoskyn (2001) performed a weighted least squares regression analysis that assessed the independent contribution of each component (Hedges & Olkin, 1985). Only one component, explicit practice, contributed significant variance to predicting effect size. The key finding was that those studies that emphasized explicit practice yielded higher effect sizes than those that did not. Studies that included this component included in their treatment program activities that related to distributed review and practice, repeated practice, sequenced reviews, daily feedback, or weekly reviews. Of course, explicit and repeated practice related to learning new information cannot operate in a vacuum. The teacher must include other components to support instruction. What should those other components reflect? To answer this question, Swanson and Hoskyn (2001) identified those components that occurred together in effective programs. This was done through an exploratory factor analysis of all the 18 components. As shown in Table 2, the analysis yielded an eightfactor solution. To simplify the table, only factor loadings greater than .50 are reported (see Swanson & Hoskyn, 2001, for further discussion). As shown in Table 2, Factor 1 loaded on the components related to attribution training and instruction that included verbal questioning or dialogue. This factor also loaded negatively on one-to-one instruction. This factor included components characteristic of several strategy models that rely on reciprocal teaching and attribution training during small-group interactions (e.g., Borkowski, Weyhing, &

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TABLE 1 Description and Frequency of Inclusion of Selected Instructional Components in the Studies Examined (N = 93) Component

Description

Incl. %

1. Advance organizers

Statements in the treatment description about directing adolescents to look over material before instruction, directing adolescents to focus on particular information, providing prior information about the task, or teacher stating objectives of instruction.

34.4

2. Attribution

Statements in the treatment description about teacher presenting the benefits of taught strategies.

3. Control of difficulty or processing demands of tasks

Statements in the treatment description about probing learning, fading of probes or prompts, providing short activities so that the level of difficulty is controlled, or teacher providing necessary assistance.

4. Elaboration

Statements in the treatment description about additional information or explanation provided about concepts, or redundant text or repetition within text.

5. Explicit practice

Statements in the treatment description related to distributed review and practice, repeated practice, sequenced reviews, daily feedback, or weekly reviews.

32.3a

6. Large-group instruction

Statements in the treatment description about instruction in large groups or teacher-only demonstration.

49.5

7. New content/skills

Statements in the treatment description about the implementation of a new curriculum or emphasis on teacher presenting new material from the previous lesson.

44.1

8. One-to-one instruction

Statements in the treatment description about activities related to independent practice, tutoring, individually paced instruction, or individually tailored instruction.

74.2

9. Peer modeling

Statements in the treatment description about peers presenting or modeling instruction.

1.0 43.0

8.6

6.5

10. Questioning

Statements in the treatment description related to directing students to ask questions, teacher and student or students engaging in dialogue, or teacher asking questions.

11. Reinforcement

Statements in the treatment description about intermittent or consistent use of rewards and reinforcers.

12. Sequencing

Statements in the treatment description about breaking down the task into subtasks or sequencing short activities.

52.7

13. Skill modeling

Statements or activities in the treatment description that involved modeling by a teacher in terms of skills.

31.8

14. Small-group instruction

Statements in the treatment description about instruction in a small group or verbal interaction occurring in a small group with other students or teacher.

16.3

15. Strategy cues

Statements in the treatment description about reminders to use strategies or multi-step procedures, teacher verbalizing steps or procedures to solve problems, or use of think-aloud models.

18.3

16. Activities supplementary to teacher instruction

Statements in the treatment description about homework or parents helping to reinforce instruction.

6.5

17. Task reduction

Statements in the treatment description about breaking down the targeted skill into smaller units, mastery criteria, or task analysis.

49.5

18. Technology

Statements in the treatment description about developing pictorial representations, using specific materials or computers, or using media to facilitate presentation and feedback.

45.2

Note. Incl. % = percentage of studies that included this component. aThis component contributed significant variance to the prediction of effect size.

17.2

2.2

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TABLE 2 Factor Loadings of Instructional Components Factor Component 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18.

Advance organizers Attribution Control of difficulty Elaboration Explicit practice Large-group instruction New content/skills One-to-one instruction Peer modeling Questioning Reinforcement Sequencing Skill modeling Small-group instruction Strategy cues Supplementary activities Task reduction Technology

1

2

3

4

5

6

7

8

.57 .53 .73 .51 .72 –.72 –.63 –.69 .52 .75

ture the contributions of different composites of instructional components, the factor scores, along with chronological age and a methodological composite score (studies were weighted on a number of factors related to internal and external validity), were entered into several regression models. The results are shown in Table 3 of Swanson and Hoskyn (2001). The bottom line of this analysis was that the Organization/ Explicit Practice factor was the only factor that contributed significant variance (16% of the variance) to effect sizes.

.82 .61

The Big Picture

.79 .82 .82 .59 .74

Note. Only factor loadings higher than .50 are shown. Factors are labeled as follows: 1. Questioning; 2. Sequencing/Segmentation; 3. Skill Modeling; 4. Organization/Explicit Practice; 5. Small-Group Setting; 6. Indirect Teacher Activities; 7. Technology; 8. Scaffolding.

Carr, 1988; Palincsar & Brown, 1984). Swanson and Hoskyn referred to this factor as Questioning. It is important to remember when interpreting this factor that negative loadings reflect the absence of or lack of emphasis on a particular component in a study. Thus, questions related to strategy instruction could certainly occur in a one-toone setting, but small-group interactions in the set of studies sampled were a key component of studies using strategy models. Factor 2 reflected instruction that focused on the sequencing and segmentation of skills. These components are characteristic of direct instruction models (Lovett et al., 1994). This factor was labeled Sequencing/Segmentation. Factor 3 reflected the use of reminders to use multiple processing steps (strategy cues) and the teacher ’s modeling of skills. This factor loaded negatively on the presentation of new content or skills. This factor was labeled Skill Modeling. Again, the negative loading does not imply the absence of new content; rather, the focus was on using previously taught steps to access

previously presented (i.e., new when initially presented) information. Factor 4 (Organization/Explicit Practice) focused on organization prior to the task commencement and on repeated practice. Factor 5 contrasted the large-group setting with the smallgroup setting. This factor was labeled Small-Group Setting. Factor 6 loaded highly on components related to peer modeling and ancillary activities (e.g., homework, parent help). This factor also loaded highly on elaboration. This factor was labeled Teacher Indirect Instruction. Factor 7 loaded highly on the medium of instruction (computer presentations, strategy flow charts, etc.). This factor was labeled Technology. Factor 8 reflected the presentation and fading of prompts and providing of necessary assistance. This factor was labeled Scaffolding. Thus, the instructional components that made up the instructional programs were boiled down to eight factors. Which of these factors were more important than others in positively influencing treatment outcomes? To cap-

Before we proceed to its application, what can be concluded from this meta-analysis when we talk about a foundational model of instruction for adolescents with LD? There are two important points to be made. First, only eight instructional factors captured the majority of intervention programs investigated for adolescents with LD. These factors are referred to as Questioning, Sequencing and Segmentation, Skill Modeling, Organization and Explicit Practice, Small-Group Setting, Indirect Teacher Activities (e.g., homework), Technology, and Scaffolding. Second, the Organization/Explicit Practice factor was the only model to contribute significant variance to effect size. This factor accounted for 16% of the variance in the magnitude of effect size. This factor includes only two instructional components: advance organization and explicit practice. The finding that these two components enhance intervention outcomes is consistent with the existing literature (see Rosenshine, 1995, for a review). For example, providing statements about a subject to be learned has been shown to provide a structure for new information and to relate it to information that the student already possesses. Advance organizers provide students with a mental scaffold on which to build a new understanding of information. This scaffolding may consist of helping stu-

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dents to access information already in their minds and of introducing new concepts or principles that can organize this information in a form that will aid in learning. Likewise, the retention of many types of knowledge is enhanced by practice distributed at different time periods, and explicit practice is important at several stages of learning. Although intensive practice of newly learned information in the early stages of learning is necessary, the cognitive intervention literature suggests that distributed practice is better for retention. Several studies have also suggested that the long-term retention of all kinds of information and skills is greatly enhanced by distributed practice (e.g., Dempster, 1987). Although we isolated these 2 components from an array of 18, the practicality of these findings needs consideration. No intervention program would be sufficient with just these two components, and, therefore, our findings must be put in the context of daily instruction. Thus, the question arises as to where these two components fit within the context of other components. Several authors, both in mainstream general education and special education (e.g., Borkowski et al., 1988; Graham & Harris, 1989; Scruggs & Mastropieri, 1989), have suggested that effective instruction follows a sequence of events such as the following: 1. State the learning objectives and orient the students to what they will be learning and what performance will be expected of them. 2. Review the skills necessary to understand the concept. 3. Present the information, give examples, and demonstrate the concepts and materials. 4. Pose questions (probes) to students, assess their level of understanding, and correct misconceptions. 5. Provide group instruction and independent practice. Give students an opportunity to demonstrate new skills and to learn the new information on their own.

6. Assess performance and provide feedback. Review the independent work and give a test. Give feedback for correct answers and reteach skills if answers are incorrect. 7. Provide distributed practice and review. No doubt, this sequence has variations within instruction models (e.g., Bulgren, Deshler, & Schumaker, 1997). The components in the Swanson and Hoskyn (1998) synthesis that matched these basic instructional core practices are explicit practice (Component 5), orientation to a task (Component 1), presentation of new material (Component 7), teacher modeling of steps (Component 15), sequencing (Component 12) and systematic probing (Component 17). However, their findings as applied to adolescents with LD (Swanson & Hoskyn, 2001) suggested that two of these aforementioned steps are critical of adolescents with LD— advance organizers (Component 1) and explicit practice (Component 5).

Instructional Practice The factors that emerged in the metaanalysis just summarized should provide teachers with a solid sense of direction for the myriad of instructional decisions they must make and with standards against which to judge the nature and quality of their instructional practices. In short, to be effective, the instruction provided to students with LD must be delivered in a fashion that employs these factors in combination. To illustrate how the two most important factors from this metaanalysis—advance organizers and explicit practice—can be effectively integrated into instructional routines for adolescents, several interventions developed by the staff at the University of Kansas Center for Research on Learning (CRL) will be described. It is important to note that we realize that several other programs could be drawn

upon. For example, several robust research programs reflected in the work of Fuchs and Fuchs (in press), Scruggs and Mastropieri (in press), Wong et al. (in press), and Bottge and Hasselbring (1999), to name a few, could illustrate many of the applications we will provide. However, because the CRL program has its primary focus on adolescents, we draw examples from their curriculum.

Examples of the Organizer Factor As students progress into secondary schools, the volume of content, especially the number of facts and details, to be learned and remembered increases dramatically (Schumaker, Deshler, & McKnight, in press). The pressure is significant for typically achieving students; for adolescents who are saddled with a learning disability, these expectations can be overwhelming. In short, anything teachers can do to help students “see the forest for the trees” can aid the learning process. Two lines of intervention research developed by the CRL have made liberal use of various organizing strategies, including advance organizers, to make learning a more manageable task and outcomes more favorable. Content Enhancement Routines. Content enhancement is an approach to planning instruction for and teaching content to diverse groups of students in the general education classroom. It involves making decisions about what content to teach, manipulating and translating that content into easy-to-understand formats, and presenting it in memorable ways (Deshler et al., 2001). This approach includes 1. selecting the central concepts that make the details and facts hang together, and identifying relationships among the concepts; 2. selecting and constructing instructional devices that will make the content more understandable and memorable; and

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3. presenting the content in a way that actively involves students while enhancing their learning. Three of the content enhancement routines validated through CRL research were explicitly designed as organizer routines. They are the lesson organizer routine (Lenz, Marrs, Schumaker, & Deshler, 1993), the unit organizer routine (Lenz, Schumaker, Deshler, Bulgren, & Boudah, 1994), and the course organizer routine (Lenz, Bulgren, Schumaker, & Deshler, 1998). The unit organizer routine capitalized on foundational research on advance organizers (Ausubel, 1963; Ausubel & Robinson, 1969; Lawton, 1977; Lenz, Alley, & Schumaker, 1987). It has been frequently used in successful secondary classrooms that include students with disabilities. The routine is used to help students to understand

how the unit is part of bigger course ideas, to see a way of organizing information, to define the relationships associated with knowledge, to clarify what has been done in relation to what needs to be done, to monitor learning accomplishments, and to recognize what has been learned through selfquestioning. Figure 1 shows a sample unit organizer for a unit on the Civil War. The top part of the figure depicts the relationship of the current unit being taught (i.e., the causes of the Civil War) to the previous unit (i.e., the growth of the nation) and the next unit to be covered (i.e., the Civil War). The part of the device above these three boxes provides students with a description of the overarching idea that binds these three units together (i.e., the roots and consequences of civil unrest). This feature gives students some additional

language and ideas with which to think about and understand the organization of the topic. Another element of the unit organizer device is the unit map (the area in the middle of the figure). The unit map depicts the major chunks of content that will be covered, their relationship to one another, and the sequence that will be followed in going through the unit. Hence, with the unit map, students are provided with an advance organizer of the key information to be included in the unit. When teachers describe the material that will be taught in a block of instruction with the aid of a visual device, students can both hear and see how the material will be organized. Each student is provided with a copy of the unit organizer device, so they can have it to refer to multiple times throughout the course of the unit to remind them of the overall organiza-

Elida Cordon

The roots and consequences of civil war Growth of the Nation

Quiz

was based on

Sectionalism

emerged because of "Influe ntia l pe rso na litie s" pro je ct d ue Quiz

The Civil War

Causes of the Civil War

Differences between the areas

became greater with

Events in the U.S.

Review for test Review for test Test

What was sectionalism as it existed in the U.S. of 1860?

descriptive

How did the differences in the sections of the U.S. in 1860 contribute to the start of the Civil War?

compare/contrast

What examples of sectionalism exist in the world today? FIGURE 1. Sample unit organizer for a unit on the causes of the Civil War.

cause/effect

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tional structure and of the key concepts and relationships being taught. Learning Strategy Instruction. Learning strategies are techniques, principles, or rules that enable students to learn, and to solve problems and complete tasks independently (Schumaker & Deshler, 1992). A broad array of taskspecific learning strategies have been studied (e.g., Hughes, Schumaker, Deshler, & Mercer, 1988; Nagel, Schumaker, & Deshler, 1986; Schumaker, Denton, & Deshler, 1984). Central to the effective instruction of each of these learning strategies is the use of an instructional methodology that involves an eight-stage teaching sequence: pretest and make commitments, describe, model, verbal practice, controlled practice and feedback, advance practice and feedback, posttest, and generalization (Ellis, Deshler, Lenz, Schumaker, & Clark, 1991). CRL research studies on various learning strategies have shown that in the process of taking students through these eight instructional stages to ensure mastery and fluent use of the strategy, it is easy for students to lose sight of the bigger picture. Hence, as teachers begin a new instructional stage (e.g., controlled practice and feedback), they provide students with an advance organizer to remind them of where they are in the instructional sequence and what is going to be covered in today’s lesson. Each advance organizer includes the following components: a review of the previous lesson, the purpose of this lesson, a rationale for the lesson, and a statement of expectations. Through the use of an advance organizer, students are oriented not only to the major content to be taught but to how it relates to what they have learned previously, why it is important to learn this material, and what the expectations are for their performance.

Examples of Explicit Practice Content Enhancement Routines. Opportunities for explicit practice and feedback have been built into each of

the content enhancement routines. Initially, teachers use the instructional device to present critical content and to model how to use the device to understand the critical content being taught. However, to ensure that students have a well-grounded understanding of the content and can apply it appropriately, they are provided with opportunities to independently practice using the device on a new set of contents. Teachers then provide feedback so students can learn from the practice they have independently completed. An example of this can be seen in the concept mastery routine (Bulgren, Deshler, & Schumaker, 1993). The purpose of this content enhancement routine is to help students understand and master the key concepts essential for understanding a discipline (e.g., democracy, photosynthesis). Specifically, the routine is used to identify a target concept, place it within a larger framework, explore what students already know about the concept, identify important characteristics of the concept, analyze examples and nonexamples, construct a definition of the concept, and engage students in testing whether new examples belong to the target concept. (It is during this last stage that students are provided with opportunities to practice using and applying the content.) A concept mastery diagram for mammals is shown in Figure 2. After leading students through a teaching sequence in which the concept is described in terms of its salient characteristics, students have an opportunity to demonstrate their understanding of the concept by practicing with several possible examples of the concept. To do this, students are taught a process for confirming whether a particular animal is a mammal or not. To begin with, they place the animal to be confirmed in the testing ground (in the example provided in Figure 2, they are practicing with the duckbill platypus). To be an example of the concept of mammal, the animal listed in the testing ground must possess each of the always characteristics and none of the never characteristics. In the process of

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conducting this practice exercise, students place a + or a 0 next to each characteristic. By engaging students in this type of practice, teachers give them an opportunity to deliberately engage and interact with the content. Too frequently, students in secondary classes are passive recipients of content that is delivered to them, and they do not have an opportunity to practice applying their knowledge of the content. This teaching routine deliberately builds opportunities for practice into the instructional process by actively engaging the students (Bulgren, Schumaker, & Deshler, 1988). Learning Strategy Instruction. Our research on learning strategy instruction has repeatedly shown that unless students are provided with ample opportunities to practice using a strategy, they will not use the strategy correctly and will rarely use it independently (Scanlon, Deshler, & Schumaker, 1996). In order to get students to a point of fluent, automatic usage, they must get both explicit practice and informative feedback on their attempts to use the strategy. The teaching sequence includes several stages devoted to explicit practice: 1. verbal practice, designed to help students understand and talk about the intent of each step of the strategy and to learn each strategy step to a mastery level so that it can be automatically applied to respond to a curricular demand; 2. controlled practice and feedback, designed to give students practice using the strategy in controlled materials (i.e., ones written at the students’ instructional level) so that they focus on applying the strategy to materials that are not overly difficult; 3. advance practice and feedback, designed to give students practice using the strategy on materials that approximate actual grade-leveldifficulty materials; and 4. generalization, designed to give students practice applying the

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elephant walks on 2 legs

cold-blooded

warm-blooded can fly moves on the ground

whale

walks on 4 legs

human

snake

elephant

alligator

whale

duckbill platypus

cold-blooded

FIGURE 2. Concept mastery diagram for mammals.

strategy to a broad array of new materials and circumstances. Clearly, each practice stage has a specific instructional goal and is essential to help students master the strategy to an automatic level. In order to bring students to mastery, it is important that multiple opportunities for practice be provided along a continuum from teacher-mediated to student-mediated instruction. That is, the ultimate goal of learning strategy instruction is to put students into a position to use the strategy independently. To accomplish this, initially, teachers will be more actively involved in guiding their learning—in using more teacher-mediated, explicit instruction. As the students gain confidence, teachers remove their support and shift the responsibility for the learning process more to the stu-

dents—to more student-mediated, less explicit instruction. During all phases of practice, teacher feedback is a vital element of effective practice routines (Kline, Deshler, & Schumaker, 1991). Each of the sample interventions described here, as well as those of Bottge and Hasselbring (1999), Fuchs and Fuchs (in press), Scruggs and Mastropieri (in press), and Wong et al. (in press), share some common instructional elements in how they are designed to capitalize on the power of advance organizers and explicit practice as instructional principles. Namely, these principles 1. are integrated throughout the intervention package, 2. constitute major features of each instructional program, and 3. are designed into the interventions in such a way as to move from a

heavy reliance on teacher mediation in the early stages of instruction to a position of ultimately having students mediate the learning process. For example, Fuchs and Fuchs’ (in press) research program on mathematical problem solving focused on students’ mastery of solution methods so they can allocate less working memory capacity to the details of the solution. Their work showed that explicit instruction is necessary for transfer. They optimized the quality of instruction by providing effective explanation and feedback. Their research program placed a heavy reliance on curriculumbased procedures. They used repeated measurements where teachers assess the student’s mastery of a single skill, and after this mastery, they move the student on to different or more difficult

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skills. Because information is collected on students in a time series format, the teacher is able to provide explicit practice and feedback to the student. Another example is the intervention program of Scruggs and Mastropieri (in press), which focused on content learning in science and social studies. Their procedure made use of textprocessing strategies, mnemonic strategies, elaborative integration, and inquiry-oriented or activities-oriented instruction. However, enhancing student performance in the instructional model was related to specifying instructional objectives and maximizing opportunities to respond. They viewed students with learning disabilities as typically having difficulty in both the creation and the application of effective learning strategies, and therefore, their tasks required learning strategies that must be explicitly and repeatedly demonstrated.

Conclusions Since the initial passage of the Education for All Handicapped Children Act in 1975, a great deal has been learned about what is required to bring about significant gains in the performance of adolescents with LD (e.g., Deshler, Ellis, & Lenz, 1996). A careful analysis of various intervention approaches has underscored the fact that an array of instructional factors, if carefully designed into intervention protocols and applied on a consistent basis with fidelity, can help students make significant gains (e.g., Swanson, 1999). The findings of this meta-analysis and the instructional applications of some of its most heavily weighted factors demonstrate that the performance of adolescents with LD can indeed be favorably influenced. We can pinpoint successful shortterm interventions with adolescents as relating to two instructional components: advance organizers and explicit practice. We believe that the potential of making significant advances in de-

vising programs for students with LD will be partially realized if these components are included in various remediation programs. We also think we will have a better chance of providing more robust treatments for students with LD if both control and treatment conditions include these components. In this way, the unique aspects of novel treatment programs in terms of the nature of the content can be more adequately assessed. ABOUT THE AUTHORS

H. Lee Swanson, PhD, is a professfor of educational psychology and special education at the University of California–Riverside. His primary research interests are in the areas of memory, intelligence, and learning disabilities. Don Deshler, PhD, is professor of special education and director of the Center for Research on Learning at the University of Kansas. He and his colleagues have validated several academic and social interventions for adolescents with disabilities designed to increase access to and success in the general education curriculum. Address: H. Lee Swanson, Graduate School of Education, University of California, Riverside, CA 92521-0128. AUTHORS’ NOTES

1. This article is based on a project funded by the National Center for Learning Disabilities (NCLD) related to the 1999 May Summit in Washington, DC. 2. This study was also supported by a U.S. Department of Education Grant (H023E40014), the Chesapeake Institute, Peloy Endowment, and funds awarded to H. L. Swanson. 3. The applications of this study draw heavily from several interventions developed by staff at the University of Kansas Center for Research on Learning (CRL) funded by the U.S. Office of Education. The views in this article do not necessarily reflect those of the U.S. Office of Education, the Chesapeake Institute, or NCLD. 4. This data set has been discussed previously in greater detail (Swanson, 2001; Swanson & Hoskyn, 1998; Swanson, Hoskyn, & Lee, 1999), and the reader is referred to these sources. 5. The authors are thankful to two anonymous reviewers and to Scott Baker and Russell Gersten for their insightful comments on an earlier version of this article.

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