Formative Evaluation of Gifted Programs: A Process and Model

Controlled studies of the effectiveness of gifted programs are rare. An evaluative study of the Depth gifted program in South Bend, Indiana, was out using a control group, pre-post measurement, and multiple outcome measures. It was found that on a general test of cognitive ability, program participants exhibited significantly higher gains than did controls, and participants rated the quality of their school life more highly at the end of the The study lends support to the benefits of self-contained gifted programs.Very little research has focused on the effects of student participation in gifted programs. In a review of the research literature, Gallagher, Weiss, Oglesby, & Thomas (1983) cited fewer than forty such studies, and most of them involved no control or comparison group. Generally, a simple pre-post model was employed to demonstrate growth. In a more recent study, Traxler (1987) found that while evaluations of gifted programs were now more frequently carried out, only 50% were designed before program implementation and slightly less than 30% involved trained evaluators. Feldhusen and Treffinger (1985) reviewed all the research on full-time, self-contained classes for the gifted and concluded that such classes are needed truly to meet the needs of gifted students.Part of the problem rests with the evaluation methodology available to demonstrate effectiveness in gifted programs. Tests must be carefully selected and piloted for potential ceiling effects. Another part of the problem is understanding how evaluation results can be utilized to improve programs for the gifted. Too frequently evaluation reports are merely shelved. Callahan and Caldwell (1984) synthesized the literature on effective utilization of evaluation results and found that the conceptualization of the evaluation process, the credibility of information, the timing, and the feasibility of the evaluation are the most critical elements determining usefulness. Carter and Hamilton (1985) noted the problem of relying on attitudinal data rather than data on student growth or change to validate program effectiveness.Approaches that should be used in evaluating gifted programs have also been delineated in the literature. Archambault (1984) advocated the use of better quantitative designs in gifted education to measure program outcomes as well as qualitative procedures. Some researchers have viewed naturalistic evaluation as useful in special program areas like gifted education as long as systematic procedures are followed and triangulation of results is obtained from multiple data sources (Stake, 1975;Barnette, 1984). Kulieke (1986) presented a model for evaluation that rated various designs according to the major purposes of the program so that a good match of program approach and evaluation methodology might be effected. Method

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confidence: 99%

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confidence: 99%

Evaluation Of A Full-Time Self-Contained Class For Gifted Students

VanTassel‐Baska

Willis²,

Meyer³

1989

“…The aim was to determine which of these independent variables, singly or in combination, were significant predictors of performance in the Soweto Gifted Child Program (the dependent variable), and how much of the variance in performance could be accounted for by these measures. This approach is in line with the prediction equation proposed by Carter and Hamilton (1985). It was hoped that it would provide the basis for developing an appropriate assessment battery for the identification of suitable candidates for the program.…”

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confidence: 53%

Predictors of Performance of Disadvantaged Adolescents in a Gifted Program

Skuy

Gaydon

Hoffenberg

et al. 1990

This study investigated the relative value of different measures in selecting disadvantaged South Africans for an enrichment program. Results on the measures for 99 13-18-year-old students were intercorrelated with achievement in the Soweto Gifted Child Program (SGCP). Regression analyses indicated that 50-58% of the variance in performance in the SGCP was accounted for by several significant predictors; namely, two subtests (the Verbal Analogies Test and the Organiser) of the Learning Potential Assessment Device, school performance, and the combined Similarities subtests of the WAIS-R and WISC-R. For all measures which emerged as predictors, assessment of performance followed an opportunity for learning. Baldwin (1987) illustrates how the use of IQ as the criterion for giftedness might lead to the unjustifiable exclusion of black children from gifted programs. Yet the Wechsler Scales were found by Klausmeier, Mishra, and Maker (1987) to be the most extensively used ability measures for identifying the gifted in the United States. There have been attempts to develop and test the effectiveness of nondiscriminatory approaches to the identification of giftedness in minority and low socioeconomic status populations (e.g.

“…In this paper, the discussion is limited to outcome evaluations. I have selected this type of evaluation because of the current emphasis on educational outcomes (for example, see &dquo;A Nation at Risk,&dquo; 1983) and because I am an advocate of that approach (Carter and Hamilton, 1985).There are three reasons why evaluation designs must be judged against criteria different from the experimental designs in the laboratory. First, field based evaluations must be designed around administrative constraints such as time, money and logistics.…”

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confidence: 99%

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confidence: 99%

Evaluation Design: Issues Confronting Evaluators of Gifted Programs

Carter

1986

Self Cite

How should one evaluate a program for the gifted? Unique design concerns need to be taken into account when selecting a method for assessing gifted program outcomes. The author reviews design issues and proposes creative solutions to omnipresent dilemmas facing the would-be evaluator.Educational evaluation can take on different forms depending upon the questions asked. For example, sponsors of evaluations of gifted programs might ask one or more of the following questions: &dquo;Who should be served by the program?&dquo;, &dquo;Is the curriculum consistent with the goals and objectives of gifted education?&dquo;, &dquo;Do students become more creative as a result of the program?&dquo;, and &dquo;Is the program worth the cost?&dquo; These questions represent different types of evaluations. Respectively, they are needs assessment, process evaluation, outcome evaluation and evaluation of cost effectiveness.Evaluation design refers to the procedures and conditions employed by the evaluator to collect data. Since data collection is often different across the four major types of evaluations, design issues depend upon the type of evaluation conducted. In this paper, the discussion is limited to outcome evaluations. I have selected this type of evaluation because of the current emphasis on educational outcomes (for example, see &dquo;A Nation at Risk,&dquo; 1983) and because I am an advocate of that approach (Carter and Hamilton, 1985).There are three reasons why evaluation designs must be judged against criteria different from the experimental designs in the laboratory. First, field based evaluations must be designed around administrative constraints such as time, money and logistics. These constraints restrict the evaluator's ability to manipulate and control variables. Consequently, evaluations in the school setting are not as &dquo;tight&dquo; as more traditional laboratory studies. Second, Popham (1975), points out that program evaluations are not concerned with external validity, i.e., the ability to generalize beyond the program setting. Sponsors of program :evaluations desire to know how effective &dquo;their&dquo; programs is in &dquo;their&dquo; setting. Third, it is often impossible to determine whether participant outcomes are due to the program or some other variable(s)-a matter of internal validity (Campbell and Stanley, 1963) -unless controls are imposed which ironically, create a setting that is atypical of the program. In fact, Snow (1974) argues that true program effects can only be determined when a &dquo;representative design&dquo; is employed. Snow recommends designs that are representative of the natural environment because he assumes that experimental manipulation causes the learners to act differently than they would under normal conditions. These reasons illustrate the dilemma of program evaluators. They seek designs that control extraneous variables but do not disturb the natural setting nor violate the school's administrative structure. I have yet to find a design to accomplish this goal. Howev...