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Roger Hiemstra

Syracuse University


Several researchers have examined elderly learning preferences and involvement in terms of the instrumental (basic or skill mastery) and expressive (enjoyment or self-fulfillment) dichotomy. An overall prefer­ence for instrumental types of learning usually is found; however, certain types of older individuals will report preferences for expressive types of activities. A factor analysis of data on expressive and instrumental choices resulted in ten factors with more than one item loading at 0.40 or higher. The first factor, Expressive Arts Interest, accounted for 31% of the variance. Five other factors were also expressive in nature. Some implications in terms of assessing needs, planning programs, teaching, and research are presented.


Educational Gerontology, 8: 143-153, 1982

Copyright © by Hemisphere Publishing Corporation, A Taylor and Francis Journal.

Reprinted by Permission of the Journal’s editor

Stylistically, the article has been converted to APA, 5th Edition.




Havighurst (1964, 1976) was perhaps the first U.S. researcher to suggest that instrumental and expressive aspects of education are important dichotomies to consider by planners of older adult programs.


Instrumental education is education for a goal that lies outside and beyond the act of education. In this form, education is an instrument for changing the learner's situation. . . . Expressive education is education for a goal that lies within the art of learning, or is so closely related to it that the act of learning appears to be the goal (1976, pp. 41-42).


Instrumental learning activities, then refers to basic or skill mastery areas. Expressive learning centers on enjoyment or self-fulfillment education. Londoner (1971, 1978) also argued that the two domains are important for both planning and needs assessment activities.


The apparent first empirical  look at this notion was a study of 83 older adults' learning interests in which an overall preference for instrumental types of learning was found (Hiemstra, 1972). Further analysis, however, determined some preference differences; younger, female, urban, white collar, and college-graduated individuals were more likely to report expressive preferences (Hiemstra, 1973). A later study of 256 older persons again resulted in an overall preference for instrumental course titles (Hiemstra, 1975, 1976, 1977/78). In this case, Younger, female, urban


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upper-class, single, caucasian, and college-graduated persons were more likely to select expressive titles. When actual learning activity was classified according to the dichotomy, older, female, urban, college-graduated, single, and upper-class subjects engaged in more expressive projects.


Several related studies have been conducted in the past eight years. Whatley (1974) found her group of elderly more likely to make expressive selections than gerontologists or adult educators. Goodrow (1974) found an overall preference for instrumental course titles. Burkey (1975) found a greater expressive orientation in those subjects with higher amounts of education, those older overall, and younger females as a separate group. Bauer (1975) found a preference by elderly for participation in expressive types of classes and activities. Irby (1978) determined that neither instrumental nor expressive types of learning affected participation rates. Finally; Ralston (1978, 1981) found an overall instrumental preference by older adults although a black subgroup with higher socioeconomic and education levels had need scores higher than her remaining sample on both mental and expressive measures.


Such mixed findings with different populations and in different settings suggest a conclusion that several unidentified moderating variables exist. In addition, one person may perceive a potential course to be instrumental in nature while another person believes it to be expressive. Even the methodologies involved in determining instrumental or expressive preferences can be biased by rater ages, socioeconomic backgrounds of subjects, and learners' educational levels.


Marcus examined the area of instrumental and expressive preferences in terms of participation motives (1976, 1978). He looked at older persons' perceptions of their educational activities as having either instrumental or expressive utility. This study, in essence, examined the decision to participate in light of individual motivations rather than through possible interferences or interactions between rater or program planner perceptions and prospective student perceptions. He found that a person's practical needs, practical goals, and perceived time orientation affect perceptions of activities having instrumental utility. Be concluded that the interactions of the variables furnished evidence of the complex nature of participatory behavior (1978).




The notion of perceived instrumental or expressive utility and the attempt to understand educational participation behavior in later


years have relevance for programming in the arts area. Understanding differences in preferences toward certain courses in terms of gender, art style preference, degree of cautiousness, education level or other variables may be important in predicting who will participate in arts activities labeled "expressive."


Heisel (1980) hypothesized that there might be conditions where expressive educational experiences would be more successful in motivating the older person to participate. Perhaps if the teacher wished to promote both instrumental and expressive learning in a course of instruction, an "introduction to oil painting" advertisement could be used to entice the learner; other types of needs could be assessed during the course and then met later.


Hoffman (1978) makes a strong case for the elderly as a ready audience for arts programs. Graney and Hayes (1976) also found that older persons expressed considerable interest in arts and crafts. Hiemstra and Brown (1979) also found high interest in art and music appreciation. Certainly the interest appears to exist. Needed now is research focused on better understanding factors like the decision-making process, perceptions of utility, and whether learn­ing activities related to the arts can be used to meet differing needs in various groups of older adults.


Thus in an effort to contribute to such research needs, data from an earlier described study (Hiemstra, 1975) were reexamined using a factor analysis procedure. The specific problem was to further refine the expressive/instrumental dichotomy, particularly in terms of various art courses or topics of interest. The objective was to provide better information by which art education professionals could make decisions in terms of such activities as assessing learner needs, placing learners in the most appropriate courses, and course planning.




In an effort to better understand older adults and their learning interests and to carry out the refinement activity described above, data from a study conducted in Nebraska (Hiemstra, 1975) were reexamined by factor analysis. In that study 256 randomly selected individuals 55 and older (average age was 68.11) were interviewed. During one phase of the interview the individuals were asked to indicate their potential enrollment preferences by selecting as many courses as desired from a list of 16 instrumental and 16 expressive courses as follows:


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Suppose you had an opportunity tomorrow to enroll in an adult education course that met once a week for two hours for six consecutive weeks. By this I mean that you had the time, the finances, and the transportation to wherever the course would be offered. In which of the following courses might you be interested in enrolling (Hiemstra, 1975, p. 83).


A panel of judges had previously categorized courses into the two types. A list of the 32 randomly ordered course titles was read and interviewees could select courses by indicating a yes or no.


Searching for preferencing patterns, data on the expressive and instrumental choices were subjected to a factor analysis. A factor is an underlying, unobservable variable that is presumed to explain relationships or measures. Given the knowledge of potential relationships through available correlation coefficients, the factor analysis procedure can be used to provide some sense of whether or not certain patterns exist. When used in an exploratory manner the procedure can facilitate discovering new concepts or meanings for observed interrelations in a set of data; often, as in the case of this study, it serves to reduce the data into smaller units or components (factors).


For the analysis a principal, factoring with interactions solutions (PA2) was used through the SPSS computer package (Nie, Hull, Jenkins, Steinbrenner, & Bent, 1975). Iterations are used to improve estimates of communality or the proportion that variables or items share in common with each other. Eleven factors emerged from the data, each including several items (course titles) of shared variance. Factors with eigenvalues—a measure of the relative importance of each factor—less than 1.0 were deleted.


Thus, such factors can be looked at as indices that report the degree of relationship between each item and the presumed underlying dimension. To a certain extent, the value of this relationship can be viewed as a correlation between the item and the factor. The higher the value (loading) the more the item reflects or measures the factor. Usually those items with high values have common names or logical relationships with each other that clearly give rise to a name for the factor. Loadings equal to or surpassing 0.40 typically are considered great enough to utilize in interpreting, explaining, or exploring underlying meanings (Kerlinger, 1979).


After the initial factors that best account for variance among the data are determined, the procedure calls for a rotation of the


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coordinate axes for each factor to arrive at some theoretically meaningful or stable interpretation of the data. Often such rotation will also reduce the number of variables (in this case, course titles) loading significantly on a factor until it "finds" the closest relationship to only those variables tending to cluster together. In this study to produce independent, parsimonious, and simplest solutions, the axes were moved using an orthogonal rotation technique (varimax in the SPSS package). The orthogonal solution aims for zero correlations between the various factors to truly differentiate them. Thus, 10 factors with two or more items loading at 0.40 or higher emerged (see Table 1). The first five factors accounted for 75% of the variance and contained 14 of the 32 course titles. One expressive and six instrumental course titles did not appear in any of the ten factors.


Factor 1 contained four of the course titles and accounted for 31 % of the variance. This "first" factor clearly was expressive in nature. However, only three of the titles in the factor Expressive Art Interests were pure (i.e., they did not load significantly on any other factor; e.g., Introduction to Crafts also appears in Factor 10).


Factors 2, 3, 5, 7, and 8 also were expressive in nature, with two or three course titles loading solely on each factor. Factor 10 was a combined instrumental and expressive factor with one expressive (Introduction to Crafts) and three instrumental course titles loading at 0.40 or higher. The ambiguous nature of Factor 10, even though only a small amount of the total variance of correlated relationships among course titles is accounted for, points up the complexities in designing course titles and interpreting differences among courses.


Factors 4, 6, and 9 contained two or three titles and were instrumental in nature. All loadings were pure except that Stretching Your Retirement Dollar appeared in both Factors 4 and 6.


The various groupings that clearly emerged as being either expressive or instrumental in nature are not very surprising when examined within the meaning of the name given each factor. As a matter of fact, it is somewhat comforting to know that the interviewees appeared to be consistent in their response patterns. Obviously, though, names given for each factor are only tentative labels) the reader may be able to suggest alternative interpretations.


In addition, the set of course titles used in this study is by no means representative of all the various types of learning opportunities available to older adults. However, whatever the name


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Table 1. Course Titles, Factor Loadings, and Variance Accounted for After Orthogonal Rotationa


Factor and course names



Variance accounted for each factor



FACTOR 1 – Expressive: Expressive Art Interests




Beginning Painting




Art Appreciation




Music Appreciation




Introduction to Crafts




FACTOR 2 – Expressive: Spanish Culture Interests




The Archaeology of Mexico




Conversational Spanish




FACTOR 3 – Expressive: Liberal Interests




The Nature of Prejudice




The Black Authors




Modern Religions




FACTOR 4 – Instrumental: Money Matter Interests




Tax Benefits for Older Americans




Tourism and Your Travel Dollar




Stretching Your Retirement Dollar




FACTOR 5 – Expressive: Photography Interests




Films and Photography




Nature Photography




FACTOR 6 – Instrumental: Financial Interests in Retirement Planning




Wills and Estate Planning




Stretching Your Retirement Dollar




Fundamentals of Investing




FACTOR 7 – Expressive: Outdoor Collecting Interests




Mushroom Hunting




Rock Collecting




FACTOR 8 – Expressive: Outdoor Viewing Interests




Mid-Western Birds




Outdoor Flora




FACTOR 9 – Instrumental: Physical Concerns




Nutrition and the Aging Process




Reading Efficiency




FACTOR 10 – Instrumental/Expressive: Positive Retirement Interests




New Opportunities in Retirement




Financial Aspects of Retirement Counseling




Introduction to Crafts




Leisure Activities for Retirement Years





aOnly loadings of 0.40 or higher are included.


given each factor or the exact nature of specific courses, the program planner now has some further evidence to assist in grouping course offerings or in grouping participants if their initial interests can be determined.




Although a greater overall preference for instrumental activities generally will be reported by older learners in most needs assessment efforts, such variables as perceived course utility, differences in interpreting the definition or meaning of a proposed learning experience, and socio-demographic characteristic differences often will interact with participation choices. The factor analysis results described above depict the potential importance of expressive domain groupings. Other course titles could be used in subsequent studies, but it is speculated that the expressive domain importance will remain. Thus, as Hiemstra and Long (1974) suggest, needs assessment activities may require obtaining perceived preferences through methods like interest surveys combined with determining real needs or actual participation patterns through interviews, subject matter tests, and even post-course evaluations.


A potential derivative of the factor analysis results is a short form for helping learners assess primary and secondary learning interests. One or two course titles from each factor could be combined on a brief check list that learners and teachers use to isolate probable starting points for initial learning endeavors. The consistency of response is another derivative of a factor analysis. For example, if a person indicated an interest in a course that represented Factor 1, it is likely such an individual would be interested in all other courses included in the factor. Another way of utilizing the information is to examine the courses listed within each factor for their interrelated meaning. Note from this study (Table 1), that all courses in Factor 1 appear either to be introductory in nature or to represent a general aesthetic interest in art. What are the common threads that link introductory interests with general aesthetic interests? Or are such linkages spurious? Further research is required to answer such questions and to determine where additional courses or substituted courses would locate within-the ten factors or, perhaps, into new factors.


It would also be useful to have the factor analysis results serve to provide educators and course planners with some predictive help. For example, another data analysis effort with the data used in this study was carried out to provide information. for the author


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to use in a research seminar. A prediction of the number of different learning efforts an older person is likely to undertake per year was obtained. The number of expressive preferences but not the number of instrumental preferences was included art1ong significant prediction variables. By multiple-variate techniques the following regression equation was derived: The dependent variable Y′ (number of different learning activities per person) = 0-.4986X1 (number of hours in learning activities) + 0.2445X2 (number of expressive preferences) + 0.2014X3 (percent of self-directed learning activities) + 0.1657X4 (number of years of formal education) + 0.1120X5 (number of perceived obstacles).


Thus, one can look to high interest in Factor 1 courses by a person, for example, as a predictor of involvement in many different learning activities during a year.


Obviously, not all people interested in expressive domain learning activities will fall into traditional visual art and music education cate­gories. The data do suggest, however, that a person who indicates interest in one expressive area also may be interested in another expressive course or topic. The expressive domain is quite broad and, thus, someone attracted to an art center may also be searching for help with other topics such as language, literature, or even outdoor education. Art education professionals may need to put on "resource locater" and "referral" hats at times rather that assuming a prospective student has accurately established personal goals. "Getting to know that learner" often involves such skills as interviewing, listening, testing, and advising.


It also may be of interest to art education professionals to analyze certain of the factors for specific meaning. For example, Factor 5 resulted from an expression by many of interest in some sort of photography. However, the fact that such interests did not load with other expressive courses suggests that there is a real difference in the nature of the appeal of different types of expressive (and instrumental) courses to older adults. The Introduction to Crafts course also is interesting to think about in that it loaded on two different factors. Perhaps interest in crafts has a special function for older adults during those times when they are planning for their retirement; maybe such people turn to activities that they believe they should be doing or that they have heard other retirees are doing. Further research is required to better understand such special meanings suggested here and to provide those art education professionals operating under such constraints as tight budgets or limited staff with information to help in determining just how broad a range of interests can be met.


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A related research task is to examine older adults' actual learning activities and categorize them in terms of mutually exclusive titles. Then a factor analysis procedure could be used to determine common involvement dimensions or patterns. Such patterns could be compared with the factors described in this report, for example, to provide a better picture of how art education is used by different groups of people.


In conclusion, it is suggested that older adults cannot be treated as a single, homogenous group desiring stereotypic "arts and crafts" activities. Interests vary across a wide variety of possible course areas and within both the expressive and instrumental domains. Programming is not made easier by such a statement. However, the factor analysis procedure did provide more information about the instrumental/expressive dichotomy. The expressive domain is an important area in which to provide educational opportunities, but as suggested elsewhere (Hiemstra, 1980a, b), many complexities must be better understood and taken into consideration in planning and carrying out instructional activities with older adults.




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