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Council for Exceptional Children: standards for evidence-based practices in special education.

This statement presents an approach for categorizing the evidence base of practices in special education. The quality indicators and the criteria for categorizing the evidence base of special education practices is intended for use by groups or individuals with advanced training and experience in educational research design and methods.

These quality indicators and criteria only apply to studies examining the effect of an operationally defined practice or program on student outcomes. For example, programs or practices that improve instructor or parent behaviors, even if those behaviors have been shown to improve student outcomes, do not fall within the purview of this approach. Moreover, reviews of practices should be specific to an outcome area and learner population. That is, reviews should set clear parameters on a targeted outcome (e.g., reading comprehension) and a targeted learner population (e.g., children with learning disabilities, preschoolers with developmental delays, adolescents with autism, K-3 struggling readers, K-12 students with disabilities). Reviews might also be specific to a setting (e.g., public schools, inclusive classes) or type of interventionist (e.g., paraprofessionals).

Studies need not be published in a peer-reviewed journal to be included in a review using these standards. However, studies must be publicly accessible.

The work of Gersten et al. (2005) and Horner et al. (2005) guided the development of these standards, which may be viewed as a refinement of their foundational and exceptional scholarship. In developing the standards, Council for Exceptional Children (CEC)'s Evidence-Based Practice Workgroup also drew from a number of other sources for categorizing the evidence base of practices (e.g., What Works Clearinghouse) and incorporated the feedback of 23 anonymous special education researchers who kindly participated in a Delphi study. The CEC is indebted to Gersten et al., Horner et al., and the Delphi study participants, without whom this work would not have been possible.

RESEARCH DESIGNS

CEC's approach to categorizing the evidence base of practices in special education considers two research methods: group comparison research (e.g., randomized experiments, nonrandomized quasi-experiments, regression discontinuity designs) and single-subject research. The rationale is that causality can be reasonably inferred from these designs when they are well designed and conducted.

In experimental group comparison designs, participants are divided into two or more groups to test the effects of a specific treatment manipulated by the researcher. The standards consider group comparison studies in which researchers study treatment and comparison groups through random (in randomized controlled trials) and nonrandom (e.g., group quasi-experimental designs, including regression discontinuity designs) assignment. Single-subject experimental designs use participants (individuals or groups) as their own control and collect repeated measures of dependent variables over time to test the effects of a practice manipulated by the researcher. The standards consider single-subject designs that systematically address common threats to validity and reasonably demonstrate experimental control. For example, appropriately designed and conducted ABAB/ reversal, multiple-baseline, changing-criterion, and alternating-treatment designs are acceptable. AB (i.e., baseline-intervention) designs, for example, are not considered.

Although CEC recognizes the important role that correlational, qualitative, and other descriptive research designs play in informing the field of special education, the standards do not consider research using these designs because identifying evidence-based practices involves making causal determinations, and causality cannot be reasonably inferred from these designs.

QUALITY INDICATORS

The intent of identifying quality indicators essential for methodologically sound, trustworthy intervention studies in special education is not to prescribe all the desirable elements of an ideal study but to enable special education researchers to determine which studies have the minimal methodological features to merit confidence in their findings. CEC's approach to classifying the evidence base of practices considers the number and effects of group comparison and single-subject studies determined to be of sound methodological quality. Methodologically sound studies must meet all the quality indicators specified for the relevant research design. Requiring studies to address all quality indicators in order to be classified as methodologically sound will necessarily limit the consideration of studies conducted before quality indicators were developed and emphasized in published studies. However, this conservative approach increases the likelihood that only the highest quality and most trustworthy studies are considered when classifying the evidence base of practices.

Quality indicators (see Table 1) may be rated as met when the study under review addresses the underlying intent. A study is considered to have addressed a quality indicator when reviewers agree that the methodological issue is addressed satisfactorily such that it does not represent a meaningful threat to the validity of study findings.

Whether a quality indicator is addressed in a study is commonly determined explicitly by what is reported in a research report. However, reviewers might sometimes need to use their informed judgment to determine whether a quality indicator has been met. In these cases--when reviewers can reasonably infer that the quality indicator is met on the basis of other, related information reported-- they can decide that a study has met a quality indicator, even if the research report does not explicitly report addressing it.

Although social validity is not assessed with a distinct set of quality indicators, all studies must have socially important outcomes (see the first quality indicator under Outcome Measures/ Dependent Variables in Table 1). Furthermore, magnitude of change in outcome variables must be socially valid for studies to be classified as having positive effects (see Classifying Effects of Studies).

CLASSIFYING THE EVIDENCE BASE OF PRACTICES

The criteria for evidence-based classifications use the study as the unit of analysis. Studies are considered only when they (a) use either a group comparison (e.g., randomized experiments, nonrandomized quasi-experiments, regression discontinuity design) or single-subject research (e.g., reversal, multiple baseline, changing criterion, alternating treatment) design and (b) are categorized as methodologically sound.

Methodologically sound studies meet all of the quality indicators listed in Table 1 relevant to their research design. On the basis of the quantity, effects, and research design of methodologically sound studies reviewed, practices are classified in one of five categories: evidence-based practices, potentially evidence-based practices, mixed effects, insufficient evidence, or negative effects.

CLASSIFYING EFFECTS OF STUDIES

The criteria for categorizing the evidence base of practices in special education require that methodologically sound studies be classified as having positive, neutral or mixed, or negative effects.

Group comparison studies. For group comparison studies, review teams set their own effect size criteria for classifying studies as having positive, neutral or mixed, or negative effects a priori. Effect size criteria must be justified, based factors such as what constitutes a meaningful (i.e., socially valid) level of improvement in student performance for the target population on the outcome variable and empirical benchmarks related to the outcome measure (e.g., specialized, researcher-developed measures are associated with larger effects than standardized measures), intervention (e.g., higher effects are associated with teaching techniques than whole-school interventions), and targeted recipients (e.g., interventions targeting individuals and small groups are associated with larger effects than those targeting whole classes and schools; see Lipsey et al., 2012).

To illustrate, when conducting a review of a teaching technique that targets individual learners and is typically assessed using researcher-developed outcome measures, the research team should set relatively high criteria for effect sizes. For example, using the What Works Clearinghouse (2011) effect size guidelines (d [is greater than or equal to] 0.25 = positive effects, d [is less than or equal to] -0.25 = negative effects, with neutral/mixed effects indicated by -0.25 < d < 0.25) as a baseline, the review team might set an effect size cutoff of d [is greater than or equal to] 0.40 = positive effects and d < -0.40 = negative effects, with neutral or mixed effects indicated by -0.40 < d < 0.40. Demonstrating the social validity of outcome changes associated with an effect size of 0.40 for the target population would further justify using these cutoff points for the review. Any effect size statistic appropriate for representing differences between groups can be used (e.g., Cohen's d, Hedge's G, Glass's [DELTA], [chi square]).

If a study measures multiple outcomes, reviewers should only consider effect sizes for outcomes relevant to their review. For example, for a review of the effect of a practice on reading fluency, if a study measured effects of the practice on both reading fluency and reading comprehension, only the former effects should be considered. If a study examines the effects of a practice on two or more measures of the outcome of focus (e.g., two measures of reading fluency), those effect sizes should be averaged to compute a mean effect size for the study.

Single-subject studies. Single-subject research studies are classified as having positive, neutral or mixed, or negative effects on the basis of (a) the number and proportion of participants in a study for whom a functional relationship between the independent variable and the dependent variable was established and (b) the direction of the functional relationships. The presence of a functional relationship is established by reviewers' use of standard methods of visual analysis. This may include examining data across phases for changes in (a) level (mean scores within phases), (b) trend (slope of data within a phase), and (c) variability (range of scores around a level or trend line), as well as assessments of the (d) immediacy of any observed treatment effect and (e) overlap of data points across phases (for additional information on visual analysis, see Kazdin, 2010; Kratochwill et al., 2010). Note that authors of research reports being reviewed might describe the extent to which a functional relationship is established and the effects are meaningful, as well as the methods used to determine such. However, reviewers should conduct their own visual analysis of data and graphs included in the report to draw their own conclusions.

A single-subject study is considered to have positive effects when a functional relationship is established between the independent and dependent variables, resulting in a meaningful, therapeutic change in the targeted dependent variable for at least three fourths (75%) of the cases (depicted by tiers on a graph) in a study. There should be a minimum of three total cases, and the data for none of the cases show evidence of a functional relationship between the independent and dependent variables that results in change in a nontherapeutic (harmful) direction. For example, an ABAB study with four participants from the population targeted by the review would be classified as having positive effects if meaningfully positive, functional relationships are established for three participants, even if no functional relationship is established between the independent and dependent variables for the fourth participant. The magnitude of change in the dependent variable is considered meaningful or therapeutic when it is socially or practically important (e.g., as determined by social comparison, subjective evaluation, or other evidence that change in outcome was meaningful for participants).

A study is considered to have negative effects when a functional relationship is established between the independent and dependent variables, resulting in a nontherapeutic change (i.e., data intended to increase actually decrease or vice versa) in the targeted dependent variables for at least three fourths (75%) of relevant cases (e.g., participants from the population targeted by the review) in a study. There should be a minimum of three cases.

A study is considered to have neutral or mixed effects when the criteria for neither positive nor negative effects are met. For example, a study would be considered to have neutral or mixed effects if a functional relationship were established between the independent and dependent variables with positive effects for two of four participants in an ABAB study, but no effects or negative effects were observed for the remaining participants.

If a study measures multiple outcomes, reviewers should consider effects only for outcomes relevant to their review. For example, for a review of the effect of a practice on reading fluency, if a study measured effects of the practice on both reading fluency and reading comprehension, only the former effects should be considered. If a study examines the effects of a practice on two or more measures of the outcome of focus (e.g., two measures of reading fluency), each dependent variable is treated as a separate case when determining the overall effect of the study. For example, in an ABAB study examining the impact of a practice on two different measures of reading fluency for three participants, meaningful, positive effects of the independent variable on the dependent variable must occur for at least five of the six graphed outcomes (>75%) for the study to be categorized as having positive effects. In addition, reviewers should only consider participants who are part of the population targeted by their review. For example, for a review targeting learners categorized as having emotional or behavioral disorders (EBDs), in an ABAB study involving three participants with EBDs and two with learning disabilities, reviewers only consider (i.e., visually analyze) the outcomes for participants with EBDs.

EVIDENCE-BASED CLASSIFICATIONS

These standards establish criteria for five evidence-based classifications: evidence-based practices, potentially evidence-based practices, mixed effects, insufficient evidence, or negative effects (see Table 2).

REFERENCES

Gersten, R., Fuchs, L. S., Compton, D., Coyne, M., Greenwood, C., & Innocenti, M. S. (2005). Quality indicators for group experimental and quasi-experimental research in special education. Exceptional Children, 71, 149-164.

Horner, R. H., Carr, E. G., Halle, J., McGee, G., Odom, S., & Wolery, M. (2005). The use of single-subject research to identify evidence-based practice in special education. Exceptional Children, 71, 165-179. Kazdin, A. E. (2010). Single-case research designs: Methods for clinical and applied settings (2nd ed.). New York: Oxford University Press.

Kratochwill, T. R., Hitchcock, J., Horner, R. H., Levin, J. R., Odom, S. L., Rindskopf, D. M., & Shadish, W. R. (2010). Single-case designs technical documentation. Retrieved from http://ies.ed.gov/ncee/pdf/wwc_scd.pdf

Kratochwill, T. R., Hitchcock, J. H., Horner, R. H., Levin, J. R., Odom, S. L., Rindskopf, D. M., & Shadish, W. R. (2013). Single-case intervention research design standards. Remedial and Special Education, 34, 26-38. http://dx.doi.org/10.1177/0741932512452794

Lipsey, M. W., Puzio, K., Yun, C., Hebert, M. A., Steinka-Fry, K., Cole, M. W., ... Busick, M. D. (2012). Translating the statistical representation of the effects of education interventions into more readily interpretable forms (NCSER 2013-3000). Washington, DC: National Center for Special Education Research, Institute of Education Sciences, U.S. Department of Education. Retrieved from http://ies. ed.gov/ncser/pubs/20133000/pdf/20133000.pdf

Song, M., & Herman, R. (2010). Critical issues and common pitfalls in designing and conducting impact studies in education: Lessons learned from the What Works Clearinghouse (Phase I). Educational Evaluation and Policy Analysis, 32, 351-371. http://dx.doi .org/10.3102/0162373710373389

What Works Clearinghouse. (2011). Procedures and standards handbook (Version 2.1). Retrieved from http://ies.ed.gov/ncee/wwc/pdf/reference_resources/ wwc_procedures_v2_1_standards_handbook.pdf

DOI: 10.1177/0014402914531388

This report was commissioned by the CEC Board of Directors. A workgroup comprising seven special education researchers developed, vetted, and piloted the new standards for determining evidence-based practices in special education. CEC's goal is that the standards will be applied to better understand the effectiveness of a range of practices for learners with disabilities.

CEC President Robin Brewer acknowledged CEC's appreciation to its expert members in the workgroup including Bryan Cook, Chair; Virginia Buysse; Janette Klingner; Tim Landrum; Robin McWilliam; Melody Tankersley; and Dave Test.
TABLE 1

Quality Indicators
Quality Indicator                                                Notes

1.0. Context and setting. The study provides sufficient            B
     information regarding the critical features of the context
     or setting.

1.1  The study describes critical features of the context or       B
     setting relevant to the review, for example, type of
     program or classroom, type of school (e.g., public,
     private, charter, preschool), curriculum, geographic
     location, community setting, socioeconomic status,
     physical layout.

2.0. Participants. The study provides sufficient information to
     identify the population of participants to which results
     may be generalized and to determine or confirm whether the
     participants demonstrated the disability or difficulty of
     focus.

2.1  The study describes participant demographics relevant to the
     review (e.g., gender, age/grade, race/ ethnicity,
     socioeconomic status, language status).

2.2  The study describes disability or risk status of the
     participants (e.g., specific learning disability, autism
     spectrum disorder, behavior problem, at risk for reading
     failure) and method for determining status (e.g.,
     identified by school using state IDEA criteria, teacher
     nomination, standardized intelligence test,
     curriculum-based measurement probes, rating scale).

3.0. Intervention agent. The study provides sufficient
     information regarding the critical features of the
     intervention agent.

3.1  The study describes the role of the intervention agent
     (e.g., teacher, researcher, paraprofessional, parent,
     volunteer, peer tutor, sibling, technological
     device/computer) and, as relevant to the review,
     background variables (e.g., race/ethnicity, educational
     background/licensure).

3.2  The study describes any specific training (e.g., amount of
     training, training to a criterion) or qualifications (e.g.,
     professional credential) required to implement the
     intervention and indicates that the interventionist has
     achieved them.

4.0. Description of practice. The study provides sufficient
     information regarding the critical features of the practice
     (intervention), such that the practice is clearly
     understood and can be reasonably replicated.

4.1  The study describes detailed intervention procedures (e.g.,
     intervention components, instructional
     behaviors, critical or active elements, manualized or scripted
    procedures, dosage) and intervention agents' actions (e.g.,
prompts, verbalizations, physical behaviors, proximity) or cites
one or more accessible sources that provide this information.

4.2 When relevant, the study describes materials (e.g.,
manipulatives, worksheets, timers, cues, toys) or cites one or more
accessible sources providing this information.

5.0. Implementation fidelity. The practice is implemented with
fidelity.

5.1 The study assesses and reports implementation fidelity related
to adherence using direct, reliable measures (e.g., observations
using a checklist of critical elements of the practice).

5.2 The study assesses and reports implementation fidelity related
to dosage or exposure using direct, reliable measures (e.g.,
observations or self-report of the duration, frequency, curriculum
coverage of implementation).

5.3 As appropriate, the study assesses and reports implementation
fidelity (a) regularly throughout implementation of the
intervention (e.g., beginning, middle, end of the intervention
period) and (b) for each interventionist, each setting, and each
participant or other unit of analysis. If either adherence or
dosage is assessed and reported, this item applies to the type of
fidelity assessed. If neither adherence nor dosage is assessed and
reported, this item is not applicable.

6.0. Internal validity. The independent variable is under the
control of the experimenter. The study describes the services
provided in control and comparison conditions and phases. The
research design provides sufficient evidence that the independent
variable causes change in the dependent variable or variables.
Participants stayed with the study, so attrition is not a
significant threat to internal validity.

6.1 The researcher controls and systematically manipulates the
independent variable.

6.2 The study describes baseline (single-subject studies) or
control/comparison (group comparison studies) conditions, such as
the curriculum, instruction, and interventions (e.g., definition,
duration, length, frequency, learnen:instructor ratio).

6.3 Control/comparison-condition or baseline-condition participants
have no or extremely limited access to the treatment intervention.

6.4 The study clearly describes the assignment to groups, which
involves participants (or classrooms, schools, or other unit of
analysis) being assigned to groups in one of the following ways:

(a) randomly;

(b) nonrandomly, but the comparison groups are matched very closely
to the intervention group (e.g., matched on prior test scores,
demographics, a propensity score; see Song & Herman, 2010);

(c) nonrandomly, but techniques are used to measure differences
and, if meaningful differences are identified--for example,
statistically significant difference, difference greater than 5% of
a standard deviation (What Works Clearinghouse, 2011)--to
statistically control for any differences between groups on
relevant pretest scores or demographic characteristics (e.g.,
statistically adjust for confounding variable through techniques
such as ANCOVA or propensity score analysis); or

(d) nonrandomly on the basis of a reasonable cutoff point
(regression discontinuity design).

6.5 The design provides at least three demonstrations of
experimental effects at three different times. S

6.6 For single-subject research designs with a baseline phase
(alternating treatment designs do not require S a baseline), all
baseline phases include at least three data points (except when
fewer are justified by the study author due to reasons such as
measuring severe or dangerous problem behaviors and zerobaseline
behaviors with no likelihood of improvement without intervention)
and establish a pattern that predicts undesirable future
performance (e.g., increasing trend in problem behavior,
consistently infrequent exhibition of appropriate behavior, highly
variable behavior).

6.7 The design controls for common threats to internal validity
(e.g., ambiguous temporal precedence, S history, maturation,
diffusion) so plausible, alternative explanations for findings can
be reasonably

ruled out. Commonly accepted designs such as reversal (ABAB),
multiple-baseline, changing criterion, and alternating treatment
address this quality indicator when properly designed and executed,
although other approaches can be accepted if study authors justify
how they ruled out alternative explanations for findings or control
for common threats to internal validity.

6.8 Overall attrition is low across groups (e.g., <30% in a 1-year
study). G

6.9 Differential attrition (between groups) is low (e.g., [less
than or equal to] 10%) or is controlled for by adjusting for G
noncompleters (e.g., conducting intent-to-treat analysis).

7.0. Outcome measures/dependent variables. Outcome measures are
applied appropriately to gauge the effect of the practice on study
outcomes. Outcome measures demonstrate adequate psychometrics.

7.1 Outcomes are socially important (e.g., they constitute or are
theoretically or empirically linked to B improved quality of life,
an important developmental/learning outcome, or both).

7.2 The study clearly defines and describes measurement of the
dependent variables. B

7.3 The study reports the effects of the intervention on all
measures of the outcome targeted by the B review (p levels and
effect sizes or data from which effect sizes can be calculated for
group comparison studies; graphed data for single-subject studies),
not just those for which a positive effect is found.

7.4 Frequency and timing of outcome measures are appropriate. For
most single-subject studies, a B minimum of three data points per
phase is necessary if a given phase is to be considered as part of
a possible demonstration of experimental effect (except when fewer
are justified by the study author due to reasons such as measuring
severe or dangerous problem behaviors and zero baseline behaviors
with no likelihood of improvement without intervention). For
alternating treatment designs, at least four repetitions of the
alternating sequence are required (e.g., ABABABAB; see Kratochwill
et ah, 2013).

7.5 The study provides evidence of adequate internal reliability,
interobserver reliability, test-retest B reliability, or
parallel-form reliability, as relevant (e.g., score reliability
coefficient > .80, interobserver agreement [greater than or equal
to] 80%, kappa [greater than or equal to] 60%).

7.6 The study provides adequate evidence of validity, such as
content, construct, criterion (concurrent or G predictive), or
social validity.

8.0. Data Analysis. Data analysis is conducted appropriately. The
study reports information on effect size.

8.1 Data analysis techniques are appropriate for comparing change
in performance of two or more G groups (e.g., t tests,
ANOVAs/MANOVAs, ANCOVAs/MANCOVAs, hierarchical linear modeling,
structural equation modeling). If atypical procedures are used, the
study provides a rationale justifying the data analysis techniques.

8.2 The study provides a single-subject graph clearly representing
outcome data across all study phases S for each unit of analysis
(e.g., individual, classroom, other group of individuals) to enable
determination of the effects of the practice. Regardless of whether
the study report includes visual or other analyses of data, graphs
depicting all relevant dependent variables targeted by the review
should be clear enough for reviewers to draw basic conclusions
about the experimental control using traditional visual analysis
techniques (i.e., analysis of mean, level, trend, overlap,
consistency of data patterns across phases).

8.3 The study reports one or more appropriate effect size
statistics (e.g., Cohen's d, Hedge's G, G Glass's [DELTA], [chi
square]) for all outcomes relevant to the review being conducted,
even if the outcome is not statistically significant, or provides
data from which appropriate effect sizes can be calculated.

Note. B = applies to both group comparison and single-subject
research studies; G = indicator applies only to group comparison
studies; S = indicator applies only to single-subject research
studies; IDEA = Individuals With Disabilities Education Act.

TABLE 2

Evidence-Based. Classifications

1. Evidence-based practice

(a) Must be supported by at least:

    * two methodologically sound group comparison studies with random
      assignment to groups, positive effects, and at least 60 total
      participants across studies;

    * four methodologically sound group comparison studies with
      nonrandom assignment to groups, positive effects, and at least 120
      total participants across studies; or

    * five methodologically sound single-subject studies with positive
      effects and at least 20 total participants across studies; OR

(b) Meet at least 50% of criteria for two or more of the study
    designs described in (a). For example, the practice is supported
    by:

    * one methodologically sound group comparison study with random
      assignment, positive effects, and at least 30 total participants,
      as well as three methodologically sound single-subject research
      studies with positive effects and at least 10 total participants;
      or

    * three methodologically sound single-subject studies with positive
      effects and at least 10 total participants, as well as two
      methodologically sound group comparison studies with nonrandom
      assignment, positive effects, and at least 60 total participants;
      AND

(c) Include no methodologically sound studies conducted with
    negative effects and at least a 3:1 ratio of methodologically sound
    studies with positive effects to methodologically sound studies
    with neutral/mixed effects. For this item, CEC considers group
    experimental, nonrandomly assigned group comparison, and
    single-subject design studies collectively.

2. Potentially evidence-based practice

(a) Must be supported by:

    * one methodologically sound group comparison study with random
      assignment to groups and positive effects;

    * two or three methodologically sound group comparison studies with
      nonrandom assignment to groups and positive effects; or

    * two to four methodologically sound single subject studies with
      positive effects; OR

(b) Meet at least 50% of criteria for two or more of the study
    designs described in (a). For example, practice is supported by one
    methodologically sound single-subject study with positive effects
    and one methodologically sound nonrandomly assigned group
    comparison study with positive effects; AND

(c) Include no methodologically sound studies conducted with
    negative effects and at least a 2:1 ratio of methodologically sound
    studies with positive effects to methodologically sound studies
    with neutral/mixed effects. For this item, CEC considers group
    experimental, nonrandomly assigned group comparison, and
    single-subject design studies collectively.

3. Mixed evidence

(a) Must meet criterion (a) or (b) for evidence-based practice or
    potentially evidence-based practice (regarding number of
    methodologically sound studies with positive effects supporting the
    practice) AND

(b) The ratio of methodologically sound studies with positive
    effects to methodologically sound studies with neutral/mixed
    effects is less than 2:1; OR one or more methodologically sound
    studies conducted with negative effects, as long as
    methodologically sound studies with negative effects do not
    outnumber methodologically sound studies with positive effects.

4. Insufficient evidence

Insufficient research exists to meet the criteria for any of the
other evidence-based categories.

5. Negative effects

(a) Must include more than one methodologically sound study (of any
    acceptable design) conducted with negative effects, AND

(b) The number of methodologically sound studies conducted with
    negative effects outnumbers the number of methodologically sound
    studies with positive effects.
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