Monday, March 9, 2009
Assessment in the Affective Domain
The cognitive domain of student learning is an area in which educators have much experience teaching and assessing. Music educators, however, spend a significant amount of time teaching to the affective domain, which can prove difficult to assess.
In order to assess students, educators need to look for behavioral indicators. Abeles, Hoffer and Klotman (1995) note that a student’s behavior, which is “an overt action reflecting the student’s values,” is not always the same as a student’s behavioral intentions due to environmental factors (p. 314). Abeles summarizes the problem in the formula BI ≈ BH = AS + En, where BI stands for behavioral intentions, BH for behavior, AS for affective set, and En for environmental factors. For example, a student’s behavioral intentions may be to listen to a piano concerto in his free time because his affective set represents a value for this type of music, but the environmental factor of his friend telling him it’s not “cool” may cause a behavior (such as not listening to the concerto or not admitting to listening to the concerto) that doesn’t align with the affective set. Although educators must assess student behaviors in order to assess at all, there is clearly a challenge in doing so for the affective domain.
Abeles et al. (1995) point out, “The well-developed techniques employed to measure the products of cognitive processes, such as multiple-choice tests, are not successful in measuring affective behaviors” (p. 238). Reasons include that changes in affective behaviors are very gradual and that affective terminology such as “appreciate” or “enjoy” doesn’t lend itself to readily observable behaviors. The authors suggest two types of assessment in the affective domain: Likert scales and behavioral assessments. Although Likert scales are a quick and efficient way to assess values, “Verbal measures… will not be as accurate an indication of attitudes as observations of behaviors” (Abeles et al., 1995, p. 314). However, frequent observations of different behaviors “may begin to neutralize the environmental factor…and eventually provide the most accurate assessment of affective set” (Abeles et al., 1995, p. 314). Observations should be systematic, not casual, and can include behavioral-evidence categories such as physical characteristics, expressive movement, physical location, language and time duration (Abeles et al., 1995). However, this method of assessing in the affective domain is obviously more time-consuming.
Regardless of the greater difficulty in assessing affective over cognitive behaviors, the task remains essential to music educators if they wish to validate the inclusion of the affective domain in curricula. Krathwohl’s taxonomy of the affective domain can assist educators in writing attainable and observable behavioral objectives.
Abeles, H. F., Hoffer, C. R., & Klotman, R. H. (1995). Foundations of music education (2nd ed.). Belmont, CA: Thomas Higher Education.
In order to assess students, educators need to look for behavioral indicators. Abeles, Hoffer and Klotman (1995) note that a student’s behavior, which is “an overt action reflecting the student’s values,” is not always the same as a student’s behavioral intentions due to environmental factors (p. 314). Abeles summarizes the problem in the formula BI ≈ BH = AS + En, where BI stands for behavioral intentions, BH for behavior, AS for affective set, and En for environmental factors. For example, a student’s behavioral intentions may be to listen to a piano concerto in his free time because his affective set represents a value for this type of music, but the environmental factor of his friend telling him it’s not “cool” may cause a behavior (such as not listening to the concerto or not admitting to listening to the concerto) that doesn’t align with the affective set. Although educators must assess student behaviors in order to assess at all, there is clearly a challenge in doing so for the affective domain.
Abeles et al. (1995) point out, “The well-developed techniques employed to measure the products of cognitive processes, such as multiple-choice tests, are not successful in measuring affective behaviors” (p. 238). Reasons include that changes in affective behaviors are very gradual and that affective terminology such as “appreciate” or “enjoy” doesn’t lend itself to readily observable behaviors. The authors suggest two types of assessment in the affective domain: Likert scales and behavioral assessments. Although Likert scales are a quick and efficient way to assess values, “Verbal measures… will not be as accurate an indication of attitudes as observations of behaviors” (Abeles et al., 1995, p. 314). However, frequent observations of different behaviors “may begin to neutralize the environmental factor…and eventually provide the most accurate assessment of affective set” (Abeles et al., 1995, p. 314). Observations should be systematic, not casual, and can include behavioral-evidence categories such as physical characteristics, expressive movement, physical location, language and time duration (Abeles et al., 1995). However, this method of assessing in the affective domain is obviously more time-consuming.
Regardless of the greater difficulty in assessing affective over cognitive behaviors, the task remains essential to music educators if they wish to validate the inclusion of the affective domain in curricula. Krathwohl’s taxonomy of the affective domain can assist educators in writing attainable and observable behavioral objectives.
Abeles, H. F., Hoffer, C. R., & Klotman, R. H. (1995). Foundations of music education (2nd ed.). Belmont, CA: Thomas Higher Education.
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