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THE OLDER ADULT'S LEARNING PROJECTS
Roger Hiemstra
Adult and Extension Education
Iowa State University
This paper examines the learning activity of older adults. Utilizing the
methodology for identifying learning projects derived by Tough
(1971),
we interviewed 214
Nebraskans, 55 or
older (average age, 68.11).
Findings included the following:
(1) nearly 325
hours and 3.3
learning projects were the annual averages, (2) a
majority of the learning activity
was self-directed, (3) there
were no differences in the means for nine demographic
subgroupings on the number of annual hours in learning,
and (4) upper-middle- and
upper-class, college-graduated, and white-collar respondents carried out
significantly more learning projects than their counterpart subgroups. It
is suggested that adult educators must reexamine their roles as
supporters of formal institutional programs in light of the data
on learning projects.
Educational Gerontology, 1: 331-341, 1976
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.
INTRODUCTION
A great deal has been written on the older adult and learning, but much of
this information seems to be based more on myth than on reality. Just a few
years ago many authors were suggesting that learning needs, interests, and
capabilities declined rather rapidly with age, especially when a person reached
about age 40 or 45. However, recent research and writings have challenged
the assumption of rapid decline.
Havighurst (1972), for example, has pointed out that learning is necessary
throughout life because of continuously new developmental-task needs with
age. Some of the greatest changes in life prompting continual adaptation
and learning come with such events as retirement, death of spouse, and declining
health.
There is also increasing evidence that older learners can outstrip younger
learners in certain areas. One study (Woodruff & Birren, 1972) showed
that the elderly can learn certain biofeedback techniques more quickly than
younger people can, suggesting that the elderly are potentially better at
self-awareness or progressive-relaxation kinds of activities.
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Thus, a variety of stereotypes pertaining to older people are being challenged.
McClusky (1974) refers to these as myths that are being dispelled. He suggests
that many elderly are active, intelligent, and involved people who have positive
feelings about themselves and their potential.
However, negative attitudes remaining in society have adversely affected
older persons in their attempts to be successful in the conventional classroom.
As Oakes' (1971) research has shown, only an estimated 4.5% of people aged
55-64 and 1.6% of those aged 65 and over participate in formal adult education
programs.
To add to this low rate of participation in formal programs, only infrequently
are educational opportunities directed at real needs and goals of the elderly
(Hiemstra, 1972). Instead, "we tend to place them in 'playpens' by providing
recreation. . . while doing almost nothing to furnish
them with the means to keep mentally alert" (London, 1970).
There are recent indications that things may be changing relative to programs
and opportunities for the older person. For example, various national
organizations are beginning to provide educational opportunities for the
elderly. The National Institute for Senior Centers is working to upgrade
senior center personnel so that better educational programs can be provided
(National Council on Aging, 1974). In addition, the National Retired Teachers
Association has initiated a program entitled "The Institute of Lifetime
Learning," and the American Association of Retired Persons has developed
an educational program entitled the "Herman L. Donovan Senior Citizen's
Fellowship Program" (Kobasky, 1974).
De Crow (1974) completed a national study designed to uncover the extent
of learning opportunity in a variety of agencies. Some 3,500 different programs
were reported from all parts of the educational field and from a variety
of nonschool organizations. Of the 3,500 reporting
agencies, 58% had begun new activities within the year preceding the receipt
of the questionnaire. Such findings suggest a rapid growth in learning
opportunity for the older person. It is hoped that older people can be helped
to take advantage of the opportunities and that such opportunities will be
directed toward their crucial needs and goals.
Consequently, the problem for this study was to secure a better understanding
of the learning activities of the older adult. It is anticipated that such
information will help educators plan and implement better learning opportunities
for the older person.
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METHOD
Subjects
The population for the study consisted of 214 adults, 55 and older, living
in Nebraska. The entire sample consisted of 256 individuals. However, 42
did not provide answers on the amount of learning. Thus, the 214 figure includes
those individuals with one or more projects.
They were selected randomly from the voter registration cards in two communities
(one with a population of 160,000 and the other with a population of 3,000)
and 18 rural townships, from the rolls of two residential complexes built
especially for the elderly, and from the rolls of a Mexican-American community
center. The sample consisted of 42% male, 59% urban, 87% white American,
90% married or widowed, 22% college-graduated, and
46% white-collar subjects. The average age was 68.11, with 58% of the sample
over 64.
Procedure
An interview schedule, based on the work of Tough (1971), was used to determine
the amount and type of learning activity in a year. In this study
learning is defined as the acquisition
of knowledge, attitudes, or skills and the mastery of behavior in which facts,
ideas, or concepts are made available for the individual’s use.
Tough’s learning project notion was utilized to define a learning endeavor.
A learning project is defined as a series of clearly related learning efforts
adding to at least seven hours of effort within a six-month period. The 12
months preceding the day of the interview is the
time period in which projects are examined. Deciding and planning, traveling
time to a learning activity, and evaluating personal progress are also considered
part of the learning-project time. However, the learning had to fit our
definition. Thus, entertainment and recreation activities
were not included, nor was any time not directly related to the learning
activity.
The interviewing process involved one to two hours of probing questions with
accompanying word or topic reminder sheets to ascertain the number of different
learning projects, the types, the amount of time spent on each project, and
information as to the nature of involvement in the learning activity. Seven
trained interviewers were utilized. Copies of the interview materials and
a description of the training process are available in Hiemstra (1975).
The instrument was pilot tested with four randomly selected
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individuals over the age of 55. Questions were checked
for ambiguity, clarity, wording, and sequence. In addition, a minimal attempt
was made to examine interviewer reliability: A telephone follow-up interview
of one randomly selected respondent from each interviewer's group was conducted.
No observable differences in the data reported over the phone and that collected
by the interviewers were found.
The information on actual learning activity was also compared with the
respondents' interest in participating in formal adult education courses.
Interviewers read a list of courses and respondents said whether or not they
would like to enroll in each course. Each course had been previously classified
by a panel of judges as either instrumental or expressive in nature (Hiemstra,
1972). This reference describes the instrumental and expressive classification
scheme. For the current study, 32 courses were selected from course catalogs
and a panel of three judges classified 16 of them as instrumental and 16
as expressive.
The respondents were not aware of the classification scheme. The reported
learning projects were also classified as either instrumental or expressive
by the researcher and one independent judge. The total number of course
selections in either instrumental or expressive categories was compared with
the total number of learning projects in both categories. No significant
differences were found, suggesting that respondents in this study were actually
involved in the same type of learning activity as they said they would like
to become involved with in the future.
Variables used to compare and describe the data consisted of
subgroupings for nine
sociodemographic characteristics:
There are, of course, numerous difficulties in attempting to stratify an
individual according to some scheme of social distinction. For the current
study four groupings-lower, lower middle, upper middle, and upper-were discussed
by the interviewers during their training sessions. Subsequently, the researcher
felt that the interviewers were able to come to a unanimous agreement on
how to classify a person based on their personal.
Observations and the respondent's answers to other
questions. However, It is recognized that
an unknown amount of error is built into this variable.
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White-collar occupations consisted of professionals, executives, administrative
personnel, clerical workers, salespeople, and technicians. Blue collar people
consisted of skilled manual workers, semiskilled workers, operatives, and
unskilled workers. Homemakers were excluded for comparison on this variable
(a lower total is shown on the corresponding tables) because of the difficulties
in interpreting past job experiences or in assessing the impact of a
spouse’s occupation.
The t test for significant differences between means of subgroups
was utilized to compare the data. A 95% level of confidence and a table showing
critical values of t for the two-tailed test were used.
RESULTS
As Table 1 shows, the amount of learning engaged in by the average person
each year was nearly 325 hours. Although the average of 325 hours or 3.3
projects is considerably below Tough's (1971) 816 hours or 8.3 projects,
it must be remembered that his population consisted mostly of individuals
considerably younger than 68. Coolican (1974) studied a group of young mothers
and found only 244 hours or 4.2 learning projects, indicating the wide diversity
that will no doubt be found in the total adult population as more research
of this nature is conducted. Peters and Gordon (1974) also found that the
number of hours and projects decreased considerably when a large, relatively
random sample was used.
As Table 2 shows, the older person planned most of his or her own learning,
engaged in learning primarily for reasons of enjoyment, and did not very
often use experts as a source of information or content.
Table 1. Older Adults' Learning Projects: General Description
Informational descriptor
Hours
Projects
Average per person per year
324.56
3.33
Standard deviation
296.05
1.95
Median
237.43
3.04
Range
12-2300
1-9
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Table 2.
Learning Projects: Supportive Information
Informational descriptor
Number of projects
Percentage of projects
Current status of projects
Inactive
176
24.79
Active
534
75.21
Reason for doing project
To get credit
027
03.84
For a test or examination
009
01.28
For job improvement/acquisition
106
15.08
Enjoyment
485
68.99
Mixed reasons
076
10.81
Primary planner of project
A group or its leader/instructor
145
20.45
One person in one-to-one situation
073
10.30
Material/nonhuman resource
028
03.95
The learner him or herself
391
55.15
Mixed (no dominant type of planner)
072
10.16
Subject matter areaa
Occupational/vocational
115
16.17
Personal/family
144
20.25
Social/civic
067
09.42
Self-fulfillment
385
54.15
Source of information
Group/group instructor
086
12.11
Expert
032
04.51
Books, pamphlets, newspapers
222
31.27
Programmed materials
020
02.82
Television, radio, recordings
066
09.30
Displays, exhibits, museums, galleries
008
01.13
Friends, relatives, neighbors
053
07.47
Mixed sources
223
31.41
aThe occupational/vocational area included any learning
related to a job or in preparation for a job, including basic and literacy
education. The personal/family area included parent education, learning related
to marriage roles, and learning related to mental or physical health.
Social/civic referred to an individual’s role as a responsible citizen.
Self-fulfillment included efforts at learning for leisure, art, crafts, hobbies,
music, theater, religion, ethics, etc.
In addition, greater than 50% of the learning activity centered
around subject matter of a self-fulfillment nature.
The picture is that of an active learner, frequently engaged in self-directed
learning, and not very dependent on the traditional sources of information.
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As Table 3 shows, there were no significant differences among any of the
subgroup comparisons when the number of hours spent annually in learning
was examined. However, when the number of different learning projects was
examined, three significant t-test differences were found. An examination
of the data (see Table 4) reveals that upper-middle- and upper class,
college-graduated, and white-collar people carried out more learning projects
than their counterpart subgroups. The findings from both tables provide useful
information for more research on learning projects.
A comparison of the study data with 1970 census data on Nebraska found few
differences. The sample included more nonwhite, higher-educated, and urban
people than would be expected in a truly random sample.
DISCUSSION
Older people can, want to, and do learn. This study provides a little more
evidence to dispel some of the negative stereotypes about the elderly that
have persisted in the minds of some over time and supports some contentions
made by Saul (1974) regarding the learning potential of older persons. In
addition, other stereotypes regarding the inability or assumed unwillingness
of certain types of individuals to participate in education can be questioned.
Minority, less educated, blue-collar, and lower-class persons in this study
were all engaged in many hours of learning.
The older person belongs to the largest minority group in the United States,
a group that is growing each year. Many current writers (Havighurst, 1972;
Kimmel, 1974; Kobasky, 1974; Mason, 1974; McClusky,
1974) have suggested that this group could use additional educational
opportunities in order to lead more satisfying and productive lives. However,
available data (Oakes, 1971) show that few older people take advantage of
the formal educational programs that are offered. If many older persons are
engaged in hundreds of hours of learning each year for many different reasons
and in various subject matter areas (see Table 2), the question for adult
educators is why this includes such a small percentage of involvement in
formal and traditional programs.
Perhaps the clearest implication from this study is that educators must learn
how to remove their institutional blinders and recognize all the self-directed,
independent learning going on and needed outside institutional structures.
This will require educators to work in new roles, to make learning opportunities
available in new settings, and to make available more and better resources
for learning.
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TABLE
3.
t-Test Comparison of Various
Demographic Variables with the Number of Hours Spent Annually in
Learning
Comparison variable
Number in group
Number of hours - Mean
Number of hours - St. Dev.
t value
(N.S.)
Age
55-64
091
336.74
315.81
65 and older
123
315.54
304.91
0.49
Community
Urban
126
352.11
310.95
Rural
88
285.10
303.68
1.57
Gender
Male
089
327.65
327.29
Female
125
322.35
296.68
0.12
Race
White American
185
333.52
320.40
Other
029
267.34
219.02
1.07
Social class
Lower/lower middle
099
287.21
314.00
Upper middle/upper
115
356.70
302.38
-1.64
Living arrangement
Institution
027
255.85
145.30
Apartment/House
187
334.48
325.01
-1.24
Marital Statuse
Married/widowed
191
318.18
295.77
Not married
023
277.48
407.23
-0.87
Education
College graduate
048
366.73
298.73
Non-college graduate
165
312.74
312.68
1.09
Occupationd
Blue collar
049
314.86
407.19
White collar
098
339.93
262.71
0.45
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TABLE
4.
t-Test Comparison of Various
Demographic Variables with the Number of Annual Learning
Projects
Comparison variable
Number in group
Number of projects - Mean
Number of projects - St. Dev.
t value
Significance
Age
55-64
091
3.43
2.10
65 and older
123
3.26
1.85
0.61
N.S.
Community
Urban
126
3.44
2.01
Rural
88
3.17
1.87
1.02
N.S.
Gender
Male
089
3.19
1.94
Female
125
3.43
1.97
-0.89
N.S.
Race
White American
185
3.29
2.04
Other
029
3.62
1.32
-0.85
N.S.
Social class
Lower/lower middle
099
2.96
1.92
Upper middle/upper
115
3.65
1.94
-2.62
< .01
Living arrangement
Institution
027
3.67
2.13
Apartment/House
187
3.28
1.93
0.88
N.S.
Marital Statuse
Married/widowed
191
3.27
1.86
Not married
023
3.87
2.62
-1.40
N.S.
Education
College graduate
048
4.00
2.13
Non-college graduate
165
3.15
1.87
2.51
< .02
Occupationd
Blue collar
049
2.76
1.92
White collar
098
3.69
2.01
-2.75
< .01
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The study suggests, in conclusion, some philosophical and methodological
questions that must be debated at national adult education and gerontology
meetings and in the field's publications. How can the adult educator successfully
intervene in self-directed, non-institutionally sponsored learning? Should
such interventions take place? How can the self-directed learner be helped
to become more efficient? What kinds of resources can be developed for use
in self-directed, independent learning? The answers to these questions must
come through future study, discussion, and experimentation.
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