자연주의적 탐구조사(Naturalistic Inquiry)

Experience and Educationis the best concise statement on education ever published by John Dewey, the man acknowledged to be the pre-eminent educational theorist of the twentieth century. Written more than two decades after Democracy and Education(Dewey's most comprehensive statement of his position in educational philosophy), this book demonstrates how Dewey reformulated his ideas as a result of his intervening experience with the progressive schools and in the light of the criticisms his theories had received. Analysing both "traditional" and "progressive" education, Dr. Dewey here insists that neither the old nor the new education is adequate and that each is miseducative because neither of them applies the principles of a carefully developed philosophy of experience. Many pages of this volume illustrate Dr. Dewey's ideas for a philosophy of experience and its relation to education. He particularly urges that all teachers and educators looking for a new movement in education should think in terms of the deeped and larger issues of education rather than in terms of some divisive "ism" about education, even such an "ism" as "progressivism." His philosophy, here expressed in its most essential, most readable form, predicates an American educational system that respects all sources of experience, on that offers a true learning situation that is both historical and social, both orderly and dynamic.

经验与教育 = Experience and education

Scale developers often provide evidence of content validity by computing a content validity index (CVI), using ratings of item relevance by content experts. We analyzed how nurse researchers have defined and calculated the CVI, and found considerable consistency for item-level CVIs (I-CVIs). However, there are two alternative, but unacknowledged, methods of computing the scale-level index (S-CVI). One method requires universal agreement among experts, but a less conservative method averages the item-level CVIs. Using backward inference with a purposive sample of scale development studies, we found that both methods are being used by nurse researchers, although it was not always possible to infer the calculation method. The two approaches can lead to different values, making it risky to draw conclusions about content validity. Scale developers should indicate which method was used to provide readers with interpretable content validity information.

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The content validity index: Are you sure you know what's being reported? critique and recommendations

Social scientists frequently study complex constructs. Despite the plethora of measures for these constructs, researchers may need to create their own measure for a particular study. When a measure is created, psychometric testing is required, and the first step is to study the content validity of the measure. The purpose of this article is to demonstrate how to conduct a content validity study, including how to elicit the most from a panel of experts by collecting specific data. Instructions on how to calculate a content validity index, factorial validity index, and an interrater reliability index and guide for interpreting these indices are included. Implications regarding the value of conducting a content validity study for practitioners and researchers are discussed. Key words: constructs; content validity; measure; psychometric testing ********** Researchers in the social sciences study complex constructs for which valid and reliable measures are needed. The measures should be brief, clear, and easy to administer. Measures that are too long or difficult to read may result in a lowered response rate or inaccurate responses. In addition, the measure must be appropriate for use in the targeted population. For example, measures designed for use with heterogeneous populations may not be appropriate for a specific population with certain characteristics. A plethora of measures exist with known psychometric properties, but researchers may need to develop a new measure for a particular construct because no measure exists that operationalizes the construct as the researcher conceptualized it. In these circumstances, a content validity study should be conducted. VALIDITY Traditionally, three types of validity may be demonstrated: content, criterion, and construct validity. Content Validity Content validity refers to the extent to which the items on a measure assess the same content or how well the content material was sampled in the measure. Content validity can be characterized as face validity or logical validity. Face validity indicates that the measure appears to be valid, "on its face." Logical validity indicates a more rigorous process, such as using a panel of experts to evaluate the content validity of a measure. Nunnally and Bernstein (1994) did not distinguish among different types of content validity; but presented alternative ways of assessing content validity. They suggested evaluating content validity by demonstrating internal consistency through correlating the scores from the measure with another measure of the same construct and by showing change in posttest scores over pretest scores. Criterion Validity Criterion validity is demonstrated by finding a statistically significant relationship between a measure and a criterion (Nunnally & Bernstein, 1994). Criterion validity is considered the "gold standard," and usually a correlation is used to assess the statistical relationship. For example, the Graduate Record Examination (GRE) has been found to predict graduate school success (as measured by the first-year grade-point average) for certain disciplines (Rubio, Rubin, & Brennan, 2003). Three types of criterion validity are postdictive, concurrent, and predictive. If the criterion has occurred, the validity is postdictive. The validity is concurrent if the criterion exists at the same time as the construct measured. The GRE example demonstrates predictive validity, because graduate school success (criterion) occurs after taking the GRE (measure). According to Nunnally and Bernstein, a correlation of .30 indicates adequate criterion validity. Construct Validity Anastasi and Urbina (1997) described construct validity as "the extent to which the test may be said to measure a theoretical construct or trait" (p. 126). Three kinds of construct validity are factorial, known groups; and convergent and discriminant (or divergent) validity. …

Objectifying Content Validity: Conducting a Content Validity Study in Social Work Research

This study sought to conduct a review of content validity, which is an important phase of processes of construction and adaptation of measurement instruments. Research of comprehensive literature was conducted by means of a review of national and international databases. Initially, a description of the conceptual basis and the measurement methods used in content validity was made, with emphasis on its application in the healthcare area. It was seen that controversy exists in the literature on the terminology and concept of content validity. The recommended procedures used to check content validity during the construction and adaptation processes of instruments were described, especially the judges' assessment, which can involve qualitative and quantitative procedures. The number, selection and qualification of these judges were also described. The different methods used to quantify the level of agreement among the experts were verified, mainly the Content Validity Index (CVI). This study described aspects of the content validity process, one of the procedures to be considered by healthcare researchers and professionals who are interested in using reliable and appropriate measurements and instruments scales for given population groups.

https://www.scielosp.org/pdf/csc/2011.v16n7/3061-3068/pt

Validade de conteúdo nos processos de construção e adaptação de instrumentos de medidas

Using a strengths-based perspective, this paper looks at the experiences of family caregiving to the chronically ill. Qualitative research allows researchers and practitioners to gain a deeper understanding of the family caregiver experience, adding breadth to the assessment and intervention process. Themes generated from a qualitative inquiry on the impact of the caregiving experience for the caregiver are explored and discussed in terms of implications for strengths-based practice, thus providing a positive experience for the caregiver and care recipient.

Strengths-Based Practice with Family Caregivers of the Chronically Ill: Qualitative Insights:

Unidimensionality is an assumption of many statistical techniques that examine the psychometric properties of measures In fact, unidimensionality is necessary for construct validity This article illustrates how structural equation modeling can be used to test the multidimensionality of a measure By using data collected on a multidimensional measure, we compare an oblique factor model with a higher order factor model Results indicate that the oblique factor model fit the data significantly better, because the measure is multidimensional If the measure was unidimensional, then the higher order factor should explain the correlation between the latent variables Implications for researchers and measurement development are discussed

Using Structural Equation Modeling to Test for Multidimensionality

To aid medical social workers in the promotion and support of well-being among older family caregivers, a simple, valid, and reliable scale was developed. This scale has two subscales, one that assesses the extent to which a caregiver's basic human needs are being met and one that assesses the extent to which a caregiver can satisfactorily meet his or her predictable activities of daily living. Developed from a model that focuses on a person's strengths, this tool was created to help social work practitioners enable caregivers to become more in touch with their own abilities. Both subscales had high internal reliability and construct validity. This scale may have value in other areas of caregiving. Implications for using this scale in practice are presented.

An Aid to Empowerment: A Caregiver Well-Being Scale

Relatively little is known about the psychometric properties of measures that assess the constructs of caregiver strain and well-being. Using structural equation modeling, the authors validated two scales used in the caregiving literature: Caregiver Well-Being Scale and Caregiver Strain Index. Two models were generated for the Well-Being Scale that demonstrate the measure's validity and reliability. Nineteen of the 45 items on the Well-Being Scale validated the scale. Of the original 13 items on the Strain Index, 11 are valid indicators of their respective factors. Structural equation modeling is a useful technique to evaluate these measures, because it identifies the most reliable and valid items for each scale. Key words: caregivers; psychometric properties; stress; structural equation modeling; well-being Well-being and stress are important constructs in measuring the caregiving experience, because they represent both a strengths-based perspective and a detrimental outcome of care-giving. They present particular measurement challenges to researchers studying caregivers. These constructs are viewed as multifaceted, complex phenomena that incorporate both subjective and objective dimensions (George, 1994). Neither construct can be measured by a single observable variable, but each requires multiple items to assess it. Definitions of the concepts are many and varied. Caregiving stress (strain or burden) is defined as "enduring problems that have the potential for arousing threat, a meaning that establishes strain and stressor as interchangeable concepts" (Pearlin & Schooler, 1978, p. 3). Well-being is defined as "at least some periodic states of security and structure within the turbulence of life" (Goldstein, 1990, p. 273). Because of the complexity of each construct and the methodology used to evaluate the measures, further research is needed to determine the reliability and validity of measures of stress and well-being. Such techniques as factor analysis, correlation, and coefficient alpha have been used to estimate the validity and reliability. There are several limitations inherent in these techniques (Nunnally & Bernstein, 1994). For example, coefficient alpha assumes that the items are homogeneous (Miller, 1995). If the measure consists of heterogeneous items, use of coefficient alpha is not appropriate. Another limitation of coefficient alpha is that it is affected by the number of items in a measure. The measure becomes more reliable by adding more items (Nunnally & Bernstein, 1994). Furthermore, none of the aforementioned techniques is useful with a multidimensional measure. A more sophisticated technique, structural equation modeling (SEM), overcomes many of these limitations when assessing measures' psychometric properties. The capacity to estimate a model's measurement error makes SEM an alternative for assessing validity and reliability of a measure. Because well-being and stress are multifaceted and require multiple indicators, SEM can model different dimensions of the constructs. Research demonstrates a need for more advanced statistical techniques to assess fully the validity and reliability of existing measures. This article presents the results of an assessment of the psychometric properties of two measures--well-being and stress. Using two separate samples, we used SEM to evaluate the reliability and validity of each measure. SEM is presented as an additional method to evaluate the reliability and validity of caregiver well-being and strain. Earlier research evaluated these measures with factor analysis or coefficient alpha (Robinson, 1983; Tebb, 1995). LITERATURE REVIEW Measuring well-being and stress presents challenges for social scientists. Researchers use well-being to explain life satisfaction, emotional status, affective disorder, and stress (Stetz, 1992). Both constructs are used to study family caregiving, but additional data is needed on the psychometric properties of current instruments. …

Susan Tebb

Papers

Objectifying Content Validity: Conducting a Content Validity Study in Social Work Research

Strengths-Based Practice with Family Caregivers of the Chronically Ill: Qualitative Insights:

Using Structural Equation Modeling to Test for Multidimensionality

An Aid to Empowerment: A Caregiver Well-Being Scale

Assessing the validity and reliability of well-being and stress in family caregivers