THE OLDER ADULT AND LEARNING

Roger Hiemstra

1975

A paper developed for ERIC (ED 117 371)

 

Foreword

 

Much has been written about the older adult and learning. A large number of such writings have focused on the premise that learning needs and capabilities decline with age. However, recent research and discussion have been. centered around a changing theme: declines in learning abilities and interest may be considerably less than has been historically thought. In fact, there is some evidence now available that shows older adult learners outstripping younger learners in certain areas of endeavor.

 

The purpose of the research presented in this report was to obtain an even greater understanding of the older learner. Consequently, learning interests, obstacles, and actual activities were examined. The Adult and Community Education Section of the State Department of Education supported, in part, this research with the expectation that additional information about a particular group of adults would eventually benefit the state's entire adult education program. Thus, the encouragement and support of Dr. Leonard Hill is greatly appreciated.

 

The work of Marsha Fangmeyer and Jim Gingles in assisting with the data analysis is highly appreciated. In addition, the excellent work of Olie Ahlquist, Judy Amber, Frank Bomberger, Romeo Guerra, Vern Jacobs, Neal Jennings, and Gary Whiteley -- graduate student interviewers -- is gratefully acknowledged. The scope of this research would have been greatly 1imited without the assistance of these excellent students. Finally, the cooperation of all those individuals interviewed was most rewarding. Hopefully, this report will repay them for their efforts and contribute to better educational opportunity for all older adults in the State of Nebraska.

 

Roger Hiemstra

Project Coordinator

September 1, 1975

(updated to APA, 5th Edition, April, 2005)

 


 

TOPICS COVERED IN THIS PAPER

 

Foreward

Table of Contents

List of Tables

CHAPTER 1. INTRODUCTION

General Statement

Problem Setting

Purpose of the Study

Questions to be Answered

Limitations of the Study

Definition of Terms

Outline of the Study

CHAPTER 2. REVIEW OF SELECTED LITERATURE

Introduction

Inhibitors to Learning

Learning Needs

Learning Activity

CHAPTER 3. DESIGN OF THE STUDY

Type of Study

Hypotheses

Data Collection Procedures

The Interview Schedule

Interviewing Process

Reliability

Validity

Population for the Study

Data Analysis

The Respondents

General Information

Hypothesis Testing

CHAPTER 4. FINDINGS

Introduction

Obstacles to Learning

Instrumental and Expressive Learning

Learning Projects

CHAPTER 5. SUMMARY, CONCLUSIONS, AND IMPLICATIONS

An Overview

Recommendations

General Information

The Adult and Continuing Educator

Additional Research Needs

Conclusions

An Invitation

REFERENCES

APPENDIX A: DATA COLLECTION MATERIALS AND RELATED INFORMATION

APPENDIX B: MISCELLANEOUS TABLES; INSTRUMENTAL AND EXPRESSIVE PREFERENCES

APPENDIX C: COMPARISON DATA ON LEARNING PROJECTS

 

LIST OF TABLES

TABLE 1. Participants in Formal Adult Education Programs as a Percentage of the Total Eligible Population by Age, United States, May, 1969

TABLE 2. A Comparison of Summary Statistics from Five Research Studies on Learning Projects

TABLE 3. Various Demographic Characteristics for the Study’s Respondents

TABLE 4. Crossbreak Comparison of Selected Study Demographic Variables with 1970 U. S. Census Data for Nebraskans (55 Years of Age and Older)

TABLE 5. Obstacles to Learning Activity Ranked by the Numbers Indicating Yes

TABLE 6. Course Selection Preferences Ranked by the Numbers Indicating No

TABLE 7. Preferences Toward Instrumental and Expressive Forms of Learning

TABLE 8. Crossbreak Comparisons of Various Demographic Variables with Instrumental or Expressive Learning Preferences

TABLE 9. T-test Comparisons of Various Demographic Variables with the Instrumental and Expressive Learning Projects

TABLE 10. Older Adults’ Learning Projects: General Descriptive Information

TABLE 11. Number of Learning Projects Conducted in a Year

TABLE 12. Number of Hours Spent in Learning in a Year

TABLE 13. Comparisons of Learning Projects Information with Demographic Variables

TABLE 14. Learning Projects: Supportive Information

TABLE 15. Frequency of Type of Primary Planners of Learning Projects

TABLE 16. Comparison of Subject Matter Area by Various Demographic Variables

TABLE 17. T-test Comparison of Various Demographic Variables with the Number of Hours Spent Annually in Learning

TABLE 18. T-test Comparison of Various Demographic Variables with the Number of Annual Learning Projects

TABLE 19. Crossbreak Comparisons of Various Demographic Variables with Instrumental or Expressive Learning Projects

TABLE 20. Crossbreak Comparisons of Various Demographic Variables with All Instrumental or Expressive Learning Preferences

TABLE 21. T-test Comparisons of Various Demographic Variables with the Number of Instrumental and Expressive Learning Projects

TABLE 22. A Comparison of Summary Data from Six Research Studies on Learning Projects

 

CHAPTER 1

INTRODUCTION

 

General Statement

 

The largest minority group in the nation today is the elderly and it ;is proportionately growing larger each year. Yet equal educationa1 opportunity for the elderly at this point in time is more a myth than a reality. Out of "the 1971 White House Conference on Aging" came a very powerful statement related to education and the aging:

 

Education is a basic right for all persons of all age groups. It is continuous and henceforth one of the ways of enabling older people to have a full and meaningful life, and means of helping them develop their potential as a resource for the betterment of society. (1971 White House Conference on Aging, p. 6)

 

Few individuals would think that an older citizen should be denied an equal education, but the fact remains a very small percentage of the individuals over the age of 55 do involve themselves in formal educational programs (see Table 1). However, a review of almost any flyer or catalog describing the adult education programs will reveal an increasing desire to provide courses and activities to older people.

 

Table 1. Participants in Formal Adult Education Programs As a Percentage of the Total Eligible Population by Age, United States, May, 1969.

 

Age

Population in Each Age Group

% Who Participated in Adult Education

17-24

24,800,000

18.0

25-34

23,600,000

18.2

35-44

22,700,000

13.5

45-64

22,700,000

09.4

55-64

17,900,000

04.5

65 & Over

18,600,000

01.6

Oakes (1971), p. 11.

 

If a variety of educational opportunities are available to older citizens, the question may be raised as to why the elderly are not more involved. Are they just not interested, or are there subtle discriminating factors that inhibit equality in educational opportunities? Before dealing with such a question, a closer look at the older American is in order.

 

Of the total population of 210 million, according to recent census information, 21 million Americans are over the age of 65. Having this large a percentage of our society 65 or older is only a current day phenomenon, and it appears that the percentage will increase. The 65 and over population has been growing faster than the rest of the population for several decades, there now exist seven times as many people over the age of 65 as there were in 1900. With further advances in the medical field, the number of years a person 65 years of age would expect to live could double or triple.

 

California, New York, Pennsylvania, Florida, Illinois, Ohio, Texas and Michigan account for over 50% of the older population in the United States. Over 60% live in metropolitan areas, mostly in the city center areas. Some 40% of the older population live in nonmetropolitan areas, mostly living in small towns. Over 95% live within the community, and not in an institution. Of this group, over 25% live alone or with individuals other than relatives. There are approximately 140 women to every 100 men, and 4 widows to every widower, in the over 65 age group (U.S. Bureau of the Census, 1974).

 

Transportation and mobility is often a problem for this age group. Simple shopping excursions and medical visits can create major problems due to lack of adequate travel facilities for the elderly. Of the total elderly population living outside of institutions, 86% have some chronic health condition. While the majority of the chronic conditions do not interfere to a great extent with mobility, 6% of the elderly population need to be helped by another person, and 5% are housebound. Some of the major chronic conditions affecting the elderly are arthritis, rheumatism, hearing impairment, and digestive problems. About 90% of the elderly population wear some form of corrective lens, and 5% wear hearing aids (Weg, 1974).

 

Many of the elderly are subjected to inadequate housing, poor nutrition, and sub-standard hea1th care due to a low income level. In 1972, the average income of a retired couple was $4,967 while 53% of all individuals living alone or with non-re1atives made less than $2,500 (Weg, 1974). Although in the general population the number of individuals classified as poor is decreasing, the elderly poor compose a slowly growing proportion of the total.

 

As of 1972 there were more than 2 million individuals over the age of 65 who were "functionally illiterate." More than 12% of the total elderly population had completed less than 5 years of school. Of the racial minorities included in this group, 38.7% had completed less than 5 years of school. Only 32% of the total elderly sample had completed four years of high school, with only 12.9% of the minority group members having completed four years of high school. Only 7% of all individuals over the age of 65 have college degrees (Weg, 1974).

 

The Nebraska Commission on Aging's series "Aging in Nebraska" pointed out some interesting facts about the elderly in Nebraska. The past century has seen persons 65 and over grow from 1% of the Nebraska population to nearly 12.4%. The past decade has seen a 43.1% increase in women aged 74 and older which makes them, percentage wise, the fastest growing segment of the Nebraska population. Between the years 1960 to 1970, an average of 5.3 persons age 65 and older joined the Nebraska population each day (Nebraska Commission on Aging, 1973). While many states, as previously discussed, have more total numbers of elderly than Nebraska, on a percentage basis Nebraska and Iowa are tied for second for having the highest proportion of its population over the age of 65. Only Florida has a higher percentage total (Nebraska Commission on Aging, 1973).

 

Problem Setting

 

There has been a great amount of literature about the older adult and learning, but much of this material seems to be based more on myth than reality. Many authors have thought that learning needs as well as other needs and capabilities decline with age. Recent research has challenged this assumption, centering around the premise that such declines might be considerably less than has been historically thought. In fact, there is some evidence now available showing that older learners can outstrip younger learners in certain areas. Havighurst, for example, has pointed out that learning is necessary throughout life because of continuously new developmental task needs with life (Havighurst, 1972). As a matter of fact, some of the greatest changes in life and needs for continual adaptation come with such events as retirement, death of spouse, and declining health.

 

Thus, a variety of stereotypes about the elderly are rigorously being challenged. McClusky refers to these as myths that are being dispelled. He suggests that the elderly, in general, are active, intelligent, and involved people who have positive feelings about themselves and their potential (McClusky, 1974).

 

A theory in direct opposition to classifying the elderly as individuals with declining needs and capacities is a theory that has been called the “activity theory” (Maddox, 1970). The main assumption of this theory is that an elderly persons morale will be high as long as he or she is able to stay active even if faced with role reductions and changes. This would mean replacing lost roles with other new areas of interest and activities. This suggests that there is even a greater need for continuing education in the elderly years than in the younger years.

 

Several other researchers have found additional reasons for supplemental education to start at approximately age 55 and extend on through the elderly years. For example, a longitudinal study uncovered data that suggests a process of disengagement does occur in later years, but that psychological disengagement proceeds physical disengagement from society by as much as ten years (Havighurst, 1972). Another finding was that a measure of life satisfaction not only remained stable for those actively involved in various activities, during their elderly years, but tended to increase with age for many individuals (Havighurst, Neugarten, & Tobin, 1963).

 

Thus, it appears as though those, individuals who remain active retard the advent of the disengagement process and experience continued or increasing life satisfaction. It is suggested here, therefore, that a functional adult education program for the older adult learner is a societal necessity.

 

Purpose of the Study

  

This research project was based in part on the work completed by Tough (1971) and some research by Hiemstra (1972a). Tough and his associates found that by defining learning as a series of related learning episodes totaling at least seven hours of effort within a six month period, the typical adult they surveyed annually spends 700 hours in learning activities. Deciding and planning, traveling time to a learning activity, and evaluating personal progress were included in their definition.

 

Coolican reported on five similar follow-up studies with various populations (1974). These studies revealed that the range of average times spent annually in learning varied from 244 hours for young mothers to 1244 for male professionals.

 

Hiemstra (1972a) studied both inhibitors to participation and learning interests in adults over 65. This study revealed that transportation limitations and a dislike of going out at night were the top reported factors affecting participation in adult education activities. When asked to select learning activities they might participate in if the various participation problems could be overcome, the respondents showed a much greater preference for instrumental categories of learning as compared to expressive categories. The research to be reported here combined the approaches and areas of focus in both of the above studies.

 

Consequently, the primary purpose of this study was to secure a better under standing of the learning interests, activities, and obstacles of older adults, 55 years of age and older. It is anticipated that such information will help adult educators in Nebraska and in other states plan and implement better programs of education for the older adult.

 

Questions to be Answered

 

The following questions served as guides for the study:

 

  1. What are the obstacles older adults perceive as limiting to their participation in learning activities?
  2. What are the relationships among various demographic/biographic characteristics and perceived obstacles to learning?
  3. What are the perceived preferences for instrumental and expressive forms of education?
  4. What are the relationships among various demographic/biographic characteristics and the perceived preferences?
  5. How much learning activity is undertaken by older adults in a given year?
  6. What is the nature of such learning activity?
  7. What are the relationships among various demographic/biographic characteristics and the amount of learning undertaken in a year?
  8. What are the relationships between instrumental or expressive preferences and the amount of learning undertaken in a year?

 

In Chapter 4 these questions will provide guidelines for the display, comparison, and discussion of findings.

 

Limitations of the Study

 

In a study of this nature one major limitation will always be the representativeness of the sample. As will be discussed in Chapter 3, an attempt was made to include an element of randomness in the selection of respondents. However, such factors as voter registration card biases, the selection of individuals in residences designed exclusively for the elderly, and obtaining a minority group population contained limitations that prevented a totally random and representative sample. Certainly, the entire State of Nebraska was not represented.

 

Each interviewer was trained in an identical manner. However, one limitation would be the consistency among interviewers in asking questions, interpreting responses, and recording responses. For purposes of the study it was assumed that interviewers would work in as professional a manner as possible and that respondents would answer questions to the best of their ability.

 

A final limitation dealt with the fact that there exists an incomplete theoretical framework for asking relevant questions pertaining to older adults and learning. As will be described in the next chapter, a great deal of information presently exists; however, more information is needed and some of what exists conflicts with other information. Consequently, although research hypotheses are described in later chapters  it is assumed that follow-up research will be required to better understand the areas addressed in this study.

 

Definition of Terms

 

Activity – the term "activity" is utilized to describe any general pursuit of learning that is achieved through a sequence of progressive tasks and/or actual experiences (Verner, 1964).

 

Adult   Any person who has reached the maturity level where he or she has assumed responsibility for himself or herself and sometimes others and who has assumed a productive role in the community (Verner, 1964).

 

Adult Education  Relationship between a student and an educational agent in which the agent provides, facilitates, and/or supervises a series of related learning experiences for the student (Verner, 1962).

 

Clientele – Refers to the person or types of persons benefiting from a specific educational service – the customer.

 

Continuing Education - "That idealistic and timeless conceptual thread that connects all deliberate efforts to help the human organism learn through life. . . It has become common for adult educators who function within the (formal) context of colleges and universities to refer to their activities as continuing education (Smith, Aker, & Kidd, 1970, p. 28).

 

Course – Term used to designate a specific type of adult learning which has an identifiable purpose, content, structure, and time period.

 

Expressive education – Courses designed to help older adults increase the enjoyment of life, to add new experiences, and to express themselves (Hiemstra, 1972a).

 

Facilitator – An educational change agent who makes particular action possible by being available as resource, information source, and/or learning director.

 

Instrumental education – Basic or skill mastery courses necessary for the effective mastery of the aging process (Hiemstra, 1972a).

 

Knowledge and skill – The entire range of behavioral changes: Cognitive, attitudinal, perceptive, feeling; and psychomotor.

 

Learning – The acquisition of knowledge, attitudes, or skills and the mastery of behavior in which facts, ideas, or concepts are made available for individual use (Verner, 1964).

 

Learning project -- A series of clearly related learning efforts adding up to at least seven hours of effort within a six month period. The last 12 months from the day of the interview will be the time period in which projects will be examined. Deciding and planning, traveling time to a learning activity, and evaluating personal progress will also be considered as part of the learning project time (Tough, 1971).

 

Learning for self-fulfillment – The learning projects included here are efforts at learning for leisure, arts and crafts, hobbies, and recreation; included, too, is learning related to music, art, dance, theatre, religion, ethics, or moral behavior.

 

Lifelong Learning – A process of learning that continues throughout life (Hesburgh, Miller, & Wharton, 1973). It is usually thought of in connection with the need to learn throughout one's lifetime in order to cope with a constantly changing society.

 

Non-Credit Adult Education – An educational process which does not grant academic credit for application to a specific academic degree.

 

Occupational, vocational, and professional competence – This includes learning related to preparing to enter the labor market, on-the-job training, retraining for a shift in occupation, and also basic and literacy education. Graduate courses taken by a teacher to meet state requirements is counted here, too.

 

Personal or family competence – This includes learning for the individual's role as parent spouse and homemaker; it also includes learning related to mental and physical health. An extensive counseling session on estate planning or family finances would be included here, for example.

 

Program – An activity which is planned and organized with specific objectives.

 

Social and civic competence – This area covers the individual's role as a responsible citizen, including voting and po1itics, current events, community government, and development pollution, and ecology.

 

Outline of the Study

 

The second chapter reviews literature related to inhibitors to learning learning needs and learning activities. Some more general reports concerning the projected growth of educational projects related to the elderly are also described.

 

Chapter 3 describes the study’s design and includes a methodological look at the following: (a) population, (b) instrumentation (c) the interviewing process, (d) how validation/reliability was accomplished, and (e) how the data were analyzed.

 

Chapter 4 contains a display and discussion of the study findings including a testing of the study's hypotheses. Tables will be included where they help explain or clarify the data.

 

The final chapter discusses the implication of the findings and attempts to draw some general conclusions. A brief summary of the findings with suggested implications for further research are also included.

 

CHAPTER 2

REVIEW OF SELECTED LITERATURE

 

Introduction

 

Elderly people have been stereotyped in many ways varying from culture to culture and from century to century. In the American society the general perception of the elderly has been essentially negative. In the American society the general perception of the elderly has been essentially negative. Old age is often seen as a period characterized with ever increasing social withdrawal and isolation. The elderly individual is seen as a passive physical and psychologically dependent individual who is oriented toward the past rather than the future (Tuckman & Lorge, 1958). It was found in one research study that young people of college age often misperceive that elderly individuals will be resentful of youth, more often than not in need of assistance, overly interested in their families, and preoccupied with their own death (Kogan & Shelton, 1962).

 

As was suggested in the first chapter, most of the above stereotypes and many others are being disproved with research. However, it can still be theorized that negative attitudes permeating our culture have affected elderly individuals in their attempts to be successful in conventional classrooms. To add to this problem it is suggested that only on very few occasions have educational opportunities been directed at real needs and goals of the elderly. 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, p. 15).

 

Having now obtained zero population growth, the average age of the United States population will rise. Two other factors contributing to the rise in average age are low immigration levels and a reduction in the death rate. All of these factors point to a need for an adjustment of attitude on society’s part in relation to the elderly, an attitude adjustment that would specifically include those societal members working with the elderly in some educational capacity.

 

In addition, it seems safe to assume that the educational level of all age groups will rise with time because of increased opportunity and because of the greater educated young growing older. Thus, it should not be too presumptuous to predict a dramatic increase in demand by the elderly for greater educational opportunities in the next few years. Hopefully, this research will help adult educators understand more about older people and their learning needs, interests, and problems.

 

Inhibitors to Learning

 

There are a variety of known or believed inhibitors to learning and educational activity relative to the elderly person. Some of the cognitive inhibitors relate to such beliefs that the elderly face declining memory potential, increasing inabilities to perform paired associate learning tasks, slowness in developing conditional responses, and difficulties in sorting out learning that is related to long, sequentially-related learning tasks. On the other hand, others believe when such factors as time requirements are removed these problems disappear (Arenberg & Robertson, ca 1974; Chown, 1972). Thus, more and continued research will be required before such beliefs can become facts with which a learning facilitator can deal.

 

Many authors feel more comfortable talking about non-cognitive inhibitors, although the evidence on such factors is probably not even as sound as what is known about the cognitive area. Some of the non-cognitive factors discussed include slowness due to. physiological reasons (e.g., hearing and vision problems), lack of interest, and lack of educational attainment. Other inhibitors described in the literature involve transportation problems, fear of going to learning activities that are held in the evening, lack of awareness of what is available, prohibitive costs, and lack of time. (DeCrow, 1974; Eklund, 1968-70; Grabowski & Mason, ca. 1974; Hiemstra, 1972a).

 

The United Sates Congress and Senate Special Committee on Aging found income to be a major concern for the elderly. The elderly have an income that is less than half of the income of the younger generation. In most parts of the country that gap is widening. Families headed by an older person had a median family income of $5,453 in 1972, while those elderly individuals still living as a family unit had a median family income of $2,199 (U.S. Congress, 1973). Thus,e1derly individuals numbering as high as 4.3 million are living in households which are considered to be below the poverty level.

 

A variety of disabling health problems also act as inhibitors to elderly participants in educational activities. High medical cost, the time involved with medical visits, decreasing energy reserves, handicaps, and crippling diseases are only a few of the problems many older people face (Peterson, ca. 1974).

 

Still another problem to be discussed here is the fact that in planning programs adult educators simply are not considering the older adult as a possible participant (Kabosky, ca. 1974). The fact that only 1.6% of those individuals over 64 participated in adult education during 1969 (as reported in Table 1, Chapter 1) is some indication of this problem. Consequently, it is suggested that adult educators must examine a variety of approaches to overcoming the various inhibitors if the many learning needs of the older person are to be met.

 

Learning Needs

 

There are a variety of needs that can be discussed relative to the older person. McClusky suggested several types of needs that education has a potentially powerful role to play in fulfilling: coping, expressive, contributive, influence, and transcendence (McClusky, ca. 1974). He suggests various implications related to education for each category.

 

Coping needs refer to the more basic needs that fulfill the requirements for psycho-social adjustments and physical well being, Educational programs related to such needs would be adult basic education, health education programs involving economic improvement training and retraining, family life education, and leisure activities. Programs related to the expressive need category would include activities that were being engaged in for their own sake. These could include liberal arts hobbies, and physical education activities. Contributive needs might include in-service training, leadership skill building, and community service awareness activities. Programs related to influence needs could be represented by community action education and programs dealing with leadership or management. The need for transcendence learning could be met through such courses as the study of literature, philosophy, and even theology.

 

Hiemstra completed a study in which the expressive vs. instrumental concept of need was explored, a broader classification scheme than the one described above. The study revealed that a significantly higher preference for instrumental activities (competency areas designed for effective mastery of old age challenges) was elicited from older people as compared to preferences given for expressive activities (experiences designed to increase a person's enjoyment of life) (Hiemstra, 1972a). Instrumental type learning activities would include course titles such as "Stretching your Retirement Dollar,” "Wills and Estate Planning," "Nutrition and the Aging Process," and “Medical Care in the Retirement Years." Expressive examples would include "Art Appreciation," "Nature Photography," The Archaeology of Mexico," "Three Black Authors," and "Introduction to Crafts."

 

Other researchers have studied the instrumental and expressive classification scheme. Studies by Goodrow (1974), Marcus (in process), and Whatley (1974) have supported the preference for instrumental courses finding. An important point, however, is that the information on such preferences needs to be supplemented by research on demonstrated actual learning needs in comparison with perceived needs and interests (Hiemstra & Long, 1974). DeCrow (1974) further cautions that the instrumental and expressive categories are quite broad and that dichotomizing all educational opportunities has some drawbacks. Finally, further analysis of what older persons are actually participating in is needed to more fully understand what should be offered.

 

Another means for describing some learning needs of the older person is to examine those circumstances of life that primarily only the elderly face, i.e., retirement, bereavement, and death. Pre-retirement education, financial planning workshops, and loneliness seminars are likely topics for adult education planners to consider. Perhaps, though, there are better means for meeting these type of needs. Kimmel (1974), for example, suggests that the older person themselves are potentially the best sources to provide expertise and to facilitate learning on these topics.

 

An important thing to remember is that each elderly adult is a unique individual and different individuals with different needs will demand different educational programs. Birren believes that when age-related differences in learning are found, it is not a primary capacity to learn that makes the difference, but an individual's basic perceptual differences, a mind set, the motivation of the individual, or the physiological state (including that of disease and disability status) (Birren, 1964). All these factors have implications for educational programming and in analyzing learning activity by older people.

 

Learning Activity

 

There are many interesting endeavors already taking place to meet some of the learning needs of the older person. Many institutions of higher education are beginning to graduate professional adult educators who have specialized in the area of Gerontology. Some universities and colleges are also offering means for the elderly to enroll in regular programs or to participate in non-traditional programs. The North Hennipen (Minnesota) College, as one specific example, has built a large program for senior citizens with many participants involved in both credit and non-credit college courses.

 

Various national organizations have also become involved with providing educational to the older person. The National Institute for Senior Centers is currently working to upgrade senior center personnel so that better opportunities for learning can be provided (National Council on Aging, 1974). In addition, the National Retired Teachers Association has a program entitled “The Institute of lifetime Learning,” and the American Association of Retired Persons has a program entitled the “Herman L. Donovan Senior Citizens' Fellowship Program” (Kobasky, ca. 1974).

 

DeCrow completed a national study aimed at uncovering the extent of learning opportunity in a variety of agencies. Some 3500 different programs were reported from all parts of the "educational field and from a variety of non-school organizations. The study revealed that of the 3500 reporting agencies, 58% had begun new activities within the year preceding the receipt of the questionnaire (DeCrow, ca. 1974). Such findings show the rapid growth in opportunity and the fluidity of the situation.

 

Within the State of Nebraska a fluid and growth situation exists, too. Within the past year a special state-wide pre-retirement education program has been initiated by the Gerontology Program of the University of Nebraska-Omaha (Nebraska Commission on Aging, 1975a). Many older people have already participated in the program and more will in the coming year. In addition, about 1000 people over the age of 68 participated in adult education programs supported through grants by the State Department of Education (Nebraska Commission on Aging, 1975b). Finally, several community colleges and state colleges in Nebraska have special programs for the elderly (Nebraska Commission on Aging, 1975b).

 

A fascinating area of study in examining the topic of learning activity by older people is bio-feedback. The controlling of hypertension through bio-feedback, for example, has tremendous implications for the older person (Wilkie & Eisdorfer, 1971). Some researchers have shown that the elderly can learn certain bio-feedback techniques quicker than younger people, suggesting that the elderly are potentia1ly better at self-awareness or progressive relaxation kinds of activities (Woodruff & Birren, 1972). Perhaps these types of endeavors, when more is understood about their potentials and dangers, can be utilized to help the older person become much more skilled at personal problem solving.

 

A related 1iterature area is the emerging theory base pertaining to adults' learning projects (Coolican, 1973, 1974; Denys, 1973; Johns, 1973; McCatty, 1973; Tough, 1971). Although not specifically concerned with the older adult learner, the material on learning projects is reviewed here because part of the interview schedule used for the studies reported above was adapted for use in the current study.

 

The research utilized to determine learning project activity has created a good deal of excitement in adult education circles. New attention is being given to the potential of the adult learner, especially in the area of self-directed learning. Table 2 details some of the findings; the data suggest that a great deal of self-motivated learning is taking place.

 

Table 2. A Comparison of Summary Statistics from Five Research Studies on Learning Projects

 

Study

Average No. of Projects per Person per Year

Average No. of Hours per Person per Year

Estimate Age Range

Number of People

Coolican (1973)

4.2

244

20-30

48

Denys (1973)

4.8

430

30-55

54

Johns (1973)

8.4

1046

25-50

39

McCatty (1973)

11.1

1244

35-60

54

Tough (1971)

8.3

816

20-55

66

 

As will be reported in Chapter 4 support for the idea that the older person should have more learning opportunities has been found. Certainly many opportunities already exist and more are being provided each year; however, it is hoped that this research report will help adult educators understand more about the older person, their problems, and their needs so that an even better job can be done in the future.

 

CHAPTER 3

DESIGN OF THE STUDY

 

The theme developed thus far in the report points out the great need for lifelong learning to facilitate adequate adjustment in the later years. At the same time, there exists evidence that current learning opportunities being offered to the older adult for purposes of personal growth and development are not being used extensively. What are the reasons for this low participation rate? It is an intent of this study to supply some answers to this question by securing a better understanding of learning interests, obstacles, and activities of older people. Hopefully, such answers will help promote more functional educational programs for the elderly.

 

Type of Study

 

This research endeavor utilized the contribution of field study techniques and the survey method involving a personal interview. Katz (1953) suggests that exploratory field studies have three purposes: “To discover significant variables in the field situation, to discover relations among variables, and to lay a ground work for later, more systematic and rigorous testing of hypotheses” (p. 17). It was anticipated that the information gained by combining an interview approach with the field study technique would provide the most comprehensive accumulation of information possible given the current state of knowledge regarding learning activity and the older adult.

 

Several tentative hypotheses were formulated for the study based on a limited number of related studies. It is expected that a testing of these hypotheses and additional results of the study will provide a better understanding of some existing variables, prompt continued research, and promote a more rigorous testing of hypotheses in subsequent research.

 

Hypotheses

 

1. One aspect of the study was to obtain as representative a sample as possible. Consequently, the following null hypothesis was examined:

 

H1: There will be no differences between demographic data for the study sample and 1970 census data for Nebraska.

 

2. The study also examined the instrumental and expressive course classifications (see Chapter 2). The following null hypotheses were examined:

 

H2: There will be no preference differences in course selection according to instrumental or expressive categories. (The predicted direction is preference for instrumental courses.)

 

H3: There will be no preference differences according to instrumental or expressive categories based on various demographic characteristics. (Directional predictions are described in Chapter 4.)

 

3. The study examined the amount of learning activity undertaken in a year by older adults. Data collection on learning activity was based on the information by Tough and Coolican described in Chapter 2.

 

H4: There will be no significant differences in the average number of learning projects or hours spent in learning according to various demographic characteristics. (No direction is predicted.)

 

Data Collection Procedures

 

Data collection for this study involved the use of an interview schedule. Appendix A shows the instrument, the accompanying sheets for the interviewer’s use, and the corresponding computer code sheet.

 

The Interview Schedule

 

The instrument contained four major sections:

 

1. The first section sought answers to questions on sex, age, marital status, formal education attainment, and profession or occupation. The interviewers made personal judgements in recording race social class, and type of housing in which the interviewee resided.

 

2. Part two was designed to obtain information on some potential inhibitors to participation in learning endeavors. Yes/no responses were required to 25 obstacles the respondents felt would prevent older people from participating in learning activities. The obstacles were ascertained through a review of the literature.

 

3. The third section examined the instrumental versus expressive categorization notion. Yes/no responses were required to indicate interest in 32 different course titles, given that the participants had no obstacles to prevent them from enrolling in each. The 32 titles were taken from a pool of 75 course titles gleaned from the literature, course catalogues from five institutions offering courses or programs to the elderly, and the earlier study (Hiemstra, 1972a). A panel of three adult education/gerontology experts were utilized to determine whether a course title was deemed instrumental or expressive in nature. Where there was unanimous agreement, 16 instrumental and 16 expressive, those courses were included in the pilot-test interview schedule.

 

4. The final section utilized the interview schedule from Tough’s work as a basis to determine the amount of learning activity within the year preceding the interview. This section utilized a probing technique 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.

 

Interviewing Process

 

Eight interviewers (advanced graduate students in adult education) were trained in a four hour session that included an orientation to the research project and process, a simulation interviewing activity, and a practice session on two individuals in the age 55 or older range who were selected at random. The researcher observed the interviewing procedure during the simulation activity, examined the data sheets after the practice sessions, and answered interviewers’ questions as they arose. Each interviewer was given information pertaining to the sample from which he or she was to choose respondents. Interviewers then carried out the interviews, completed the corresponding code sheets, and turned in their information. The average time for each interview was slightly more than one hour. Tough (1971) averaged about two hours per interview in this work. As will be seen in Chapter 4, the number of projects and hours devoted to learning were fewer in this study as compared to Tough’s findings. Perhaps the interviewers for this study did not do an adequate ob of probing to uncover all learning projects. However, if subsequent research reveals that the older person does indeed spend fewer hours in learning each year, then the less than two hours in interviewing is probably all that is required to gather the data.

 

The interviewing process requires an extensive probing technique to help respondents recall all learning activities in a given years, especially those that are primarily self-planned or self-initiated. Thus, each interviewer was taught to approach the stimulation of recall through several related questions through the use of reminder lists for the respondents to see or listen to, and through final follow-up questions. A sheet with reminder interviewing tips and supplemental sheets to the interview schedule were made available to each interviewer (see Appendix A).

 

Reliability

 

Several efforts were made to ensure that as reliable an instrument as possible was designed.

 

1. The initial draft of an instrument was pilot-tested by the researcher with four people aged 57, 60, 68, and 81, respectively. Individual questions were checked for ambiguity, clarity, wording, and sequence. Some minor corrections were made and the final form of the instrument developed.

 

2. The definition of learning utilized originally by Tough was redefined slightly to facilitate each interviewer in having a common understanding of a  learning project. The definition utilized was as follows: A series of clearly related learning efforts adding up to at least seven hours of effort within a six-month period. The learning effort must include activities designed to obtain new information, to develop new skills, or to re-examine existing attitudes and beliefs. Activities undertaken primarily for entertainment or recreational purposes are not to be included, nor is any time to be included that is not directly related to the learning activity.

 

3. A research assistant in the Department of Adult Education at the University of Nebraska examined each interviewer schedule and code sheet for consistency, interviewer problems, learning projects recorded that did not fit the above definition, and code sheet errors. Any problems were discussed with the researcher and the interviewer if necessary.

 

4. One interviewer was obviously having difficulties with the process because of his frequent questions and the nature of the data being collected. Subsequently, he was asked to drop out of the interviewing process and data from his completed interviews were not included in the final tabulations.

 

5. A telephone follow-up of one respondent from each of the interviewer's group of respondents approximately one month after the interview was carried out. Although statistical testing was not attempted with such a small follow-up sample, the researcher believes that because there were so few differences between the telephone information and the interview data, especially on the obstacles and course preferences information, the instrument and the interviewers were quite reliable. Coolican (1974) noted that no coefficients of interviewer reliability were established among the various interviewers mentioned in her report. Subsequent research should endeavor to determine actual interviewer reliability. Invariably, one learning project could be added with intensive probing or in some cases one mentioned in the initial interview was not recalled over the  telephone. Despite his intensive efforts, Tough also determined that "interviewers felt they failed to uncover all of the learning projects in some interviews and that perhaps self-planned learning is even more common than . . . figures indicate” (Tough, 1971, p. 89).

 

6. Statistically the following was accomplished: The total sample was split randomly into two groups. The groups were then compared by chi-square on the total number of expressive and the total number of instrumental course selection. No significant differences were found as shown below:

 

Group Number

Instrumental Preferences

Expressive Preferences

One

629

402

Two

615

439

Totals

1244

841

χ2 = 1.42; a non-significant difference

 

Validity

 

Several efforts were made to ensure initially that a valid interview schedule was available and after the collection of the data to assess the instrument’s validity:

 

1. In the initial development of the instrument a review of the literature aided, from a content validity view, the inclusion of obstacles and courses.

 

2. A panel of judges assisted in the construct validity effort by categorizing the courses chosen as instrumental or expressive. An original pool of 75 course titles was obtained from the literature and from the course catalogs of agencies offering courses to the older person. Each panel member (a teacher in gerontology, an administrator or of gerontology program, and an adult education/Cooperative

Extension researcher) was given the list of 75 courses and a definition of the two terms. Where there was unanimous agreement from all three (each working independent of the other) that a course title was instrumental or expressive, it was included on the instrument. To keep even numbers, sixteen in each category were inc1uded (there were actually 29 "expressive" agreements). Respondents were not told anything about the instrumental or expressive categorizations.

 

3. Observations made during the pilot-testing by the researcher suggested that the instrument was actually measuring indications of learning inhibitors, course preferences, and learning activity.

 

4. Concurrent validation involved the comparison of course preferences with information reported on section 4 of the schedule after the actual learning activities were categorized by the researcher and the research assistant working independently. The information is shown below:

 

Type of Course Preference

Total Number of Course Preferences

Actual Learning Projects

Instrumental

1244

421

Expressive

841

271

Totals

2085

692

χ2 = .30; a non-significant difference

 

Individual respondent correlations comparing the number of course preferences to the number of actual learning projects were as follows:  rinstrumental = .2541

instrumental rexpressive = .3474

 

Although both correlation coefficients are relatively small, they are significant at the .001 level and beyond.

 

Population for the Study

  

The population consisted of 256 adults, 55 and older, residing in the State of Nebraska. Age 55 was chosen because that is now the age being considered by many as the time to begin retirement. Havighurst (1967) refers to it as the beginning point for maintaining one’s position and for looking ahead. Financial limitations precluded the choice of study individuals who resided outside the State of Nebraska.

 

The following describes their location and how they were selected:

 

1. Urban (Lincoln) Group –

 

a. 114 people were chosen randomly from voter registration cards and divided up among three interviewers. City hall officials made the voter registration cards available. A pool of randomly selected individuals was obtained with names, addresses, and ages. Interviewers were given a list of names and they contacted people on the list until between 35 or 40 interviews per interviewer were completed.

 

b. 31 people were chosen randomly from the rolls of two residential complexes built especially for the elderly and interviewed by one person.

 

2. Rural Group – 38 people were chosen randomly from voter registration cards or rural townships in Nebraska (eighteen townships and two communities were represented near Lincoln and Omaha, Nebraska) and interviewed by one person.

 

3. Small Town Group –

 

a. 45 people were chosen randomly from the voter registration cards in three small Nebraska communities (under 4,000 population) and interviewed primarily by one person (one person noted above interviewed four people in this group).

 

b. 28 people were chosen randomly from the rolls of a Mexican-American community center in a middle-sized Western Nebraska town (15,000) and interviewed by a Spanish speaking person.

 

The refusal rate was very low (only 17 people refused to be interviewed). However, two interviewers exhausted their pool of names because of not being able to find people at home and thus reduced the number of potential respondents. In addition, several interviewees determined that the interview was taking too much time and were unable or unwilling to finish answering all the questions on the instrument.

 

Data Analysis

 

Tables with frequencies, percentages, and means are utilized to describe much of the data throughout Chapters 3 and 4. In addition, a crossbreak analysis is used wherever it was determined that comparisons could be explained better, where the significance of any differences revealed through exploratory computations could be shown, and when testing some of the study's hypotheses. The t-test for significant differences between means was utilized for examining the fourth hypothesis.

 

The crossbreak analysis was utilized when two nominal (actual or researcher manipulated) variables were being compared. The term “variable” in this study refers to the various demographic characteristics, the obstacle selections, the course preferences, and the learning projects information. A major purpose of the crossbreak technique in examining relationships among variables is as follows:

 

. . . to facilitate the study and analysis of relations. Crossbreaks,  by conveniently juxtaposing research variables, enable the researcher to determine the nature of the relations between the variables. (Kerlinger, 1967, p. 243)

 

The "Statistical Package for the Social Sciences" (a computer package available through the University of Nebraska's Computer Center—also available now as desktop or laptop software) contains a crossbreak analysis program that includes computation of the chi-square statistic. Fisher's exact test is applied in SPSS when there are fewer than 21 cases and Yate's corrected chi-square is applied to all other comparisons when the tables are 2 X 2 tables (Nie, et al.). Significance found at the .05 level and beyond is included in this report. Because directions are predicted for hypotheses 2 and 3, the one tailed test of significance was utilized (Siegel, 1956; Tuckman, 1972).

 

The t-test of significance was employed to explore the relations between nominalized (actual or researcher manipulated) variables (questions on the instrument) and interval scales (the number of learning projects and the number of hours) in an examination of the fourth hypothesis. The assumption of equal-intervals was made for the two scaled variables so that the t-test could be used:

 

 . . . if we  use ordinal measures as though they were interval or ratio measures, we can err seriously in interpreting data and the relations inferred from data, though the danger is probably not as grave as it has been made out to be . . . On the other hand, if we abide strictly by the rules, we cut off powerful modes of measurement and analyses and we are left with tools inadequate to cope with the problems we want to solve. (Kerlinger, 1967, p. 427)

 

In addition to an assumption about equal intervals, the researcher made the assumption that two populations, i.e., natural or manipulated groupings, might or might not have the same variance. The SPSS computer package automatically computes an F test of sample variance so that a decision on pooled variance probability estimate versus separate variance probability estimate can be determined at the .05 level of confidence:

 . . . the null hypothesis H0 : s2/1 = s2/2  with alternative H1 : s2/1s2/2  and a significance level αl is chosen . . . From the sample variances, F is computed.

 

F = larger S2/smaller S2.

 

If the probability for F is greater than αl, H0 is accepted; t based on the pooled-variance estimate . . . should be issued.

 

If the probability for F is less than or equal to αl, H0 is rejected; t based on the separate variance estimate . . . should be used. Nie, et al., p. 270)

 

Thus, the researcher examined each t value in light of the above and significant values reported in the next chapter were determined accordingly.

 

The Respondents

 

General Information

 

Table 3 displays a variety of demographic data pertaining to the respondents. In summary of those data the subjects were approximately sixty percent female, mostly white American, and mainly from the middle class strata. Most of the interviewees lived in a house, were married, and were at least a high school graduate. A wide variety of occupations were represented, but with only a fairly small percentage falling in semi-skilled or unskilled categories.

 

Table 3. Various Demographic Characteristics for the Study’s Respondents.

 

Characteristic

Response Frequency

Percent

Accumulative Percent

Gender:

 

 

 

Male

105

041.0

041.0

Female

151

059.0

100.0

Race:

 

 

 

White American

227

088.7

088.7

Black American

001

000.4

089.1

Mexican American

028

010.9

100.0

Social Classa:

 

 

 

Lower

015

005.9

005.9

Middle-Blue Collar

116

045.3

051.2

Middle-White Collar

109

042.5

093.7

Upper

016

006.3

100.0

Living Arrangement:

 

 

 

Apartment

032

012.5

012.5

House

193

075.4

087.9

Other

031

012.1

100.0

Marital Status:

 

 

 

Married

162

063.3

063.3

Widowed

065

025.4

088.7

Single

021

008.2

096.9

Divorced/Separated

008

003.1

100.0

Years of Education:

 

 

 

Less than 8th Grade

024

009.4

009.4

8th – 11th Grade

062

024.3

033.7

High School Graduate

083

032.2

065.9

Some College

037

014.5

080.4

College Graduate

025

009.8

090.2

Graduate Training

025

009.8

100.0

Professional/Occupation:b

 

 

 

Higher Executive/Professional

011

004.3

004.3

Lower Executive

046

018.0

022.3

Administrative Personnel

016

006.3

028.6

Homemaker

079

030.6

059.2

Clerical/Technician

039

015.3

074.5

Skilled

041

016.1

090.6

Semi-Skilled

016

006.3

096.9

Unskilled

008

003.1

100.0

Age:c

 

 

 

55-64

101

039.5

039.5

65 and older

155

060.5

100.0

Location:d

 

 

 

Urban

145

056.6

056.6

Rural

111

043.4

100.0

aDetermined by the interviewer based on answers to other questions and personal observations. This particular category was also discussed during the interviewers’ training session.

bDetermined by the interviewer based on answers to other questions or to direct questions about occupation. This particular category was also discussed during the interviewers’ training session.

cThe oldest person was 98 years of age; the average age was 68.11 years; the median age was 67.10 years.

dUrban subjects included only those residing in Lincoln. All others were classified as rural.

 

The age distribution showed a fairly large number in each group, although sixty percent of the interviewees were over 64. The range of age was from 55 to 98 with the average age at slightly more than 68 years. Slightly more than thirty-five percent were 70 years of age or older.

 

Interviewers also asked questions seeking to ascertain if the older persons had received training outside the formal education structure. It was reported that 108 people had received or participated in specialized training. The following outlines the main categories reported:

 

Vocational/technical training  - 15 people

On the job training  -  41 people 

Correspondence study - 8 people 

Business school - 18 people

Miscellaneous training -  26 people

 

This particular question was not pursued in-depth by the interviewers. Subsequent research would need to delve deeper into the topic if it is considered an important variable.

 

Hypothesis Testing

 

The first hypothesis stated in the null form there will be no differences between demographic data for the study sample and 1970 Census data for Nebraska. Table 4 shows the comparative data for selected variables. On the demographic characteristics of age, gender, marital status, and occupation, the study sample was representative of the total state population, 55 years of age and older. However the hypothesis received only partial support. The study sample included more non-whites, higher educated people, and more urban residents than would be expected in a truly representative sample. The fact that a fairly large proportion of the individuals resided in Lincoln accounted for much of the difference.

 

Table 4. Crossbreak Comparisons of Selected Study Demographic Variables with the 1970 U. S. Census Data for Nebraskans (55 Years of Age and Older).

 

Comparison Variables

Study Data

Number

Study Data

Percent

Census Data

Number

Census Data

Percent

Gender:

 

 

 

 

Female

151

059.0

177,593

055.2

Male

105

041.0

144,591

044.8

Totalsa

χ2 = 1.51; Sig. = N.S.

256

100.0

322,184

100.0

Race:

 

 

 

 

White American

227

088.7

316,300

098.2

Other

029

011.3

005,884

001.8

Totals

χ2 = 128.73; Sig. = < .001

256

100.0

322,184

100.0

Marital Status:

 

 

 

 

Married

162

063.3

201,307

061.8

Widowed

065

025.4

028,125

008.7

Single

021

008.2

078,875

024.2

Divorced/Separated

008

003.1

017,259

005.3

Totals

χ2 = 2.57; Sig. = N.S.

256

100.0

325,566b

100.0

Years of Education:

 

 

 

 

Less than 8th Grade

024

009.4

045,950

016.3

8th – 11th Grade

062

024.3

134,206

047.5

High School Graduate

083

032.2

058,825

020.8

Some College

037

014.5

025,408

009.0

College Graduate

025

009.8

010,592

003.8

Graduate Training

025

009.8

007,453

002.6

Totals

χ2 = 135.13; Sig. = < .001

256

100.0

282,434c

100.0

Occupation:d

 

 

 

 

White Collar

112

063.3

320,482

063.3

Blue Collar

065

036.7

185,676

036.7

Totals

χ2 = 0.00; Sig. = N.S.

177

100.0

506,158

100.0

Age:c

 

 

 

 

55-64

101

039.5

138,658

043.1

65 and older

155

060.5

183,526

056.9

Totals

χ2 = 1.39; Sig. = N.S.

 

 

 

 

Location:e

 

 

 

 

Urban

145

056.6

162,454

050.4

Rural

111

043.4

159,730

049.6

Totals

χ2 = 3.96; Sig. = < .05

 

 

 

 

aExpected frequencies within each category were obtained for the chi-square test by multiplying the corresponding Census data percentage times the study number total.

bBased on sampling projects so that the totals are different than the actual universe total.

cBased on sample projects of those individuals with an income so that the totals are different than the actual universe total.

dBased on sample projections of employed individuals, 16 years of age and older, so that the totals represent the entire Nebraskan adult population. White collar includes professional, technical, managerial, sales, clerical, and farm owners classifications. Blue collar includes craftsmen, operatives, and laborer classifications. Housewives/homemakers, service workers, and private household workers are not included in either group. Homemakers also are not included in the study population for the chi-square computation.

eUrban included only Lincoln residents. Rural included all other individuals.

 

CHAPTER 4

FINDINGS

 

Introduction

 

The purpose of this chapter will be to present as concisely as possible the major findings of the study. There are three major sub-divisions in the chapter. The first section is a brief description of responses to the obstacles that prevent older people from participating in formal learning activities. The second section presents information on course preferences. The section includes some comparisons according to the instrumental and expressive categories and a testing of hypotheses 2 and 3. The final section describes the learning projects information, makes several comparisons, and tests hypothesis 4.

 

Obstacles to Learning

 

Interviewers asked each respondent the following questions: “Many things stop people from taking a course of study, learning a skill, or following a topic of interest. Which of the following do you feel are important in keeping you from learning what you want to learn?” Then a list of 25 obstacles was read and interviewees selected as many as they wanted from the list as obstacles to learning activities.

 

Table 5 shows the ranked responses from all the people interviewed. Not wanting to go out at night was indicated as an obstacle by almost half of the respondents. Perhaps this finding indicates that adult education is perceived of as only an evening activity and, if such a conclusion is true, then the non-traditional efforts of educational institutions will need considerable promotion.

 

Table 5. Obstacles to Learning Activity Ranked by the Numbers Indicating Yes.

 

Obstacle Description

No. Saying Yes

Percenta

Rank

Don’t like to go out at night

116

45.3

01.0

Not enough time

100

39.1

02.0

Costs

078

30.5

03.0

Home responsibilities

077

30.1

04.0

Job responsibilities

073

28.6

05.0

Don’t have enough energy or stamina

072

28.1

06.0

Don’t know what I’d like to learn

069

28.0

07.0

I’m too old to begin learning

067

26.3

08.5

My health is bad

067

26.3

08.5

Time required to complete programs

053

21.8

10.0

Don’t enjoy studying

047

18.7

11.0

Too much red tape in enrolling

045

18.9

12.0

Courses not scheduled when I can attend

043

18.5

13.0

Strict attendance requirements

038

16.0

14.0

No transportation available

037

14.5

15.0

Courses often aren’t interesting

032

13.7

16.0

Tired of school and classrooms

031

12.4

17.5

Not confident of my ability

031

12.4

17.5

No information about where I can get

what I want

030

12.3

19.0

Courses don’t seem to be available

024

10.4

20.0

I don’t meet requirements to begin

021

08.9

21.0

Friends and family don’t like idea

020

07.9

22.0

Low grades in past

009

03.6

23.0

No way to get credit for a degree

007

03.0

24.5

No place to study or practice

007

03.0

24.5

aPercentages based on total number of responses per item. There were occasional non-responses for an item.

 

A further examination of the table reveals that perceptions of personal problems, time constraints, and health-related obstacles are ranked quite high. Obstacles related primarily to administrative decision-making areas perhaps are the next highest marked areas. Family-related constraints, attitudes about personal abilities, and course-related problems were obstacles receiving only a few “yes” responses.

 

Hopefully, the information related to perceived obstacles can be utilized by program administrators to make learning opportunities more available. In addition, subsequent research should focus more intently on this issue of obstacles and determine some means whereby they can be overcome.

 

Instrumental and Expressive Learning

 

Interviewers also made the following statement about potential enrollment in adult education activities: "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?" The respondents were then read the list of 32 courses and asked to indicate their interest with a "yes” or “no” reply. Table 6 details those responses.

 

Table 6. Course Selection Preferences Ranked by the Numbers Indicating Yes.

 

Course Title

No. Saying Yes

Percenta

Rank

Stretching Your Retirement Dollar (I)b

138

53.9

01.0

Tax Benefits for Older Americans (I)

129

50.4

02.0

Outdoor Flora

107

41.8

03.0

Medical Care in the Retirement Years (I)

103

40.2

04.0

Laws Affecting the Aged (I)

100

39.1

05.0

Tourism and Your Travel Dollar (I)

097

37.9

06.0

Music Appreciation

090

35.2

07.0

Wills and Estate Planning (I)

088

34.4

08.0

New Opportunities in Retirement (I)

085

33.3

09.5

Physical Fitness with Fun (I)

085

33.3

09.5

Nutrition and the Aging Process (I)

083

32.5

11.0

Leisure Activities for Retirement Years (I)

082

32.2

12.0

Modern Religions

078

30.5

13.0

Fundamentals of Investing (I)

073

28.5

14.0

Reading Efficiency (I)

068

26.7

15.0

Art Appreciation

064

25.0

17.0

Introduction to Crafts

064

25.0

17.0

Mid-Western Birds

064

25.0

17.0

Films and Photography

055

21.6

19.0

The Nature of Prejudice

050

19.6

20.0

Conversational Spanish

045

17.6

21.0

The Archaeology of Mexico

043

16.8

22.5

Beginning Painting

043

16.8

22.5

Financial Aspects of Retirement Counseling (I)

042

16.4

24.0

Rock Collecting

036

14.1

25.5

Foot Problems and Care (I)

036

14.1

25.5

Nature Photography

035

13.7

27.0

Three Black Authors

026

10.2

28.0

Astronomy: From Myth to Science

023

09.0

29.0

Mushroom Hunting

018

07.1

30.5

Basics of Lipreading (I)

018

07.1

30.5

The High Cost of Dying (I)

017

06.6

32.0

aPercentages based on total number of responses per item. There were occasional non-responses for an item.

bThe letter in parentheses signifies an instrumental course. All others were classified as expressive in nature.

 

Many of the instrumental selections were ranked highly by the respondents. Fifty percent or more of the individuals said they would enroll in two of the five money-related courses and four of the five were ranked in the top half of course selections. Health related topics were another area of high interest. Music appreciation. art appreciation. outdoor flora. and modern religions were the only expressive courses ranked in the top half.

 

Perhaps not too surprising, the topic “The high cost of dying" was ranked at the bottom. Art, crafts, and outdoor-related courses also were infrequently se1ected by respondents. Hopefully, the information on course selection will be helpful in future course planning by educators.

 

The second hypothesis predicted a greater preference for instrumental courses. As Table 7 shows, a significant preference for instrumental types of learning was found and the null hypothesis of no difference according to instrumental or expressive categories can be rejected. Note, too, that the figures in parentheses reveal that actual learning involvement was in the direction of instrumental activities at a significant level. The third hypothesis called for an examination of any preference differences according to instrumental or expressive categories based on various demographic characteristics. Predicted directions were as follows based on an earlier study by the researcher (Hiemstra, 1973):

 

  1. The oldest individuals would show more preference toward instrumental.
  2. Males would show more preference toward instrumental.
  3. Blue collar workers would show more preference toward instrumental than would white collar workers.
  4. Rural residents would show more preference toward instrumental than would urban residents.
  5. Less than college graduates would show more preference toward instrumental than would college graduates.

 

Table 8 shows the results related to the hypothesis and includes data for comparisons according to the variables "race," "social class," "living arrangement," and "marital status" for which no directions were predicted. (Additional related tables can be found in Appendix B.)

 

Table 8. Crossbreak Comparisons of Various Demographic Variables with Instrumental or Expressive Learning Preferencesa.

 

Comparison Variables

Instrumental

Number

Instrumental

Percent

Expressive

Number

Expressive

Percent

Age:

 

 

 

 

55-64

067

73.6

024

26.4

65 and older

091

67.4

044

32.6

χ2 = 0.73; Sig. = N.S.

 

 

 

 

Gender:

 

 

 

 

Female

083

63.4

048

36.6

Male

075

78.9

020

21.1

χ2 = 5.64; Sig. = < .01

 

 

 

 

Occupation:b

 

 

 

 

Blue Collar

085

70.2

036

29.8

White Collar

072

69.2

032

30.8

χ2 = 0.00; Sig. = N.S.

 

 

 

 

Location:c

 

 

 

 

Urban

082

62.6

049

37.4

Rural

076

80.0

019

20.0

χ2 = 7.12; Sig. = < .005

 

 

 

 

Education:d

 

 

 

 

Less than College Grad.

129

72.1

050

27.9

College Graduate

028

60.9

018

39.1

χ2 = 1.68; Sig. = N.S.

 

 

 

 

Race:

 

 

 

 

White American

133

66.8

066

33.2

Othere

025

92.6

002

07.4

χ2 = 6.32; Sig. = < .02f

 

 

 

 

Social Class:g

 

 

 

 

Upper

006

42.9

008

51.1

Upper Middle

069

68.3

032

31.7

Lower Middle

077

77.0

023

23.0

Lower

006

54.5

005

45.5

χ2 = 0.03; Sig. = N.S.

 

 

 

 

Living Arrangement:

 

 

 

 

Home/House

121

71.6

048

28.4

Apartment

022

73.3

008

26.7

Institution

010

52.6

009

47.4

Otherh

005

62.5

003

37.5

χ2 = 0.35; Sig. = N.S.

 

 

 

 

Marital Status:

 

 

 

 

Married

107

75.4

035

24.6

Widowed

038

66.7

019

33.3

Single

008

42.1

011

57.9

Divorced/Separated

005

62.5

003

37.5

χ2 = 9.48; Sig. = < .05

 

 

 

 

aInstrumental or expressive preferences were determined by tabulating an individual's total number of selections or projects in each category. If the individual's total for instrumental was larger than the total for expressive, the label of instrumental preferences was given (vice versa for expressive preferences). Thirty people had chosen an equal number of instrumental and expressive courses and were not included in the computations for this table. Totals are not always equal to 226 because of non-responses.

bHomemakers were included within the blue collar grouping. Appendix B shows an expanded version of the occupational classification.

cSee Table 4, Chapter 3, for a description of the location classification.

dAppendix B shows an expanded version of the educational classification.

eOther included one Black American and 25 Mexican Americans.

fA two tailed test for significance table was utilized for this and the next three variables.

gSee Table 3, Chapter 3, for a discussion of this variable.

hOther” included people living with relatives, living at a residence only temporarily, in the process of moving, or living in a convent.

 

The directions suggested were generally supported, although only for two variables were there significant differences. In addition, younger individuals tended to prefer instrumental courses at a greater rate than older respondents. Consequently, rejection of the null hypothesis can only be partial. Note, too, that the “race” and “marital status” characteristics showed significant differences in the comparisons and should provide some directional suggestions for future hypotheses and research.

 

The learning activities to be described more fully in the next section were also analyzed according to the instrumental and expressive categories. (For 20 of the projects it was impossible to determine if the classification should be instrumental or expressive. Consequently, only a base of 692 instead of 714 could be used.) In a comparison of the learning projects and the various demographic characteristics, some similar and a few differences were observed relative to the information presented above for the third hypothesis. Table 19 in Appendix B contains these findings. The primary differences was in the “race” comparison where a non-significant difference was found.

 

Table 20 in Appendix B contains a comparison table to Table 8 above, except that those cases where the number of instrumental preferences equaled the number of expressive preferences are included. The only difference in relation to Table 19 was the fact that a non-significant chi-square value existed for marital status.

 

The same information on actual learning projects was also analyzed by T-test according to the total number of projects per year. As Table 9 shows, there was only one significant difference in the test of means. White collar workers carried out more learning projects in a year than did blue collar workers. As will be seen in a later table, this can be accounted for in part by the fact that the white collar worker was more involved with professional or vocational improvement type of projects.

 

Table 9. T-test Comparisons of Various Demographic Variables with the Number of Instrumental or Expressive Learning Projects.

 

Comparison Variables

Instrumental

Numbera

Instrumental

Mean

Instrumental

St. Dev.

Expressive

Number

Expressive

Mean

Expressive

St. Dev

Age:

 

 

 

 

 

 

55-64

085

2.41

1.66

055

1.89

1.03

65 and older

105

2.06

1.11

088

1.90

1.10

 

T value = 1.76

Sig. = N.S.

 

T Value = -0.04

Sig. = N.S.

 

Gender:

 

 

 

 

 

 

Female

112

2.13

1.29

095

1.95

1.13

Male

078

2.35

1.52

048

1.79

0.94

 

T value = -1.05

Sig. = N.S.

 

T value = 0.87

Sig. = N.S.

 

Occupation:b

 

 

 

 

 

 

Blue Collar

103

2.01

1.23

075

1.83

1.03

White Collar

086

2.47

1.54

067

1.96

1.12

 

T value = -2.26

Sig. = < .05

 

T value = -0.71

Sig. = N.S.

 

Location:

 

 

 

 

 

 

Urban

106

2.25

1.43

090

1.95

1.09

Rural

084

2.18

1.34

053

1.79

1.04

 

T value = 0.33

Sig. = N. S.

 

T value = 0.89

Sig. = N.S.

 

Living Arrangement:

 

 

 

 

 

 

Apartment/House/Home

167

2.25

1.40

122

1.88

1.07

Institution/Other

023

2.00

1.28

021

2.00

1.14

 

T value = 0.85

Sig. = N.S.

 

T value = -0.46

Sig. = N.S.

 

Education:

 

 

 

 

 

 

College Graduate

044

2.43

1.76

035

2.06

0.91

Less than Coll. Grad.

146

2.15

1.26

107

1.84

1.13

 

T value = 1.18

Sig. = N.S.

 

T value = 1.15

Sig. = N.S.

 

Race:

 

 

 

 

 

 

White American

161

2.20

1.42

123

190

1.08

Other

029

2.31

1.23

020

1.85

1.04

 

T value = -0.44

Sig. = N.S.

 

T value = 0.21

Sig. = N.S.

 

Marital Status:

 

 

 

 

 

 

Married

129

2.34

1.49

086

1.79

0.98

Not Marriedc

061

1.95

1.10

057

2.05

1.19

 

T value = 1.82

Sig. = N.S.

 

T value = 1.38

Sig. = N.S.

 

Social Class:

 

 

 

 

 

 

Upper/Upper Middle

101

2.30

1.40

083

2.00

1.12

Lower/Lower Middle

089

2.12

1.38

060

1.75

1.00

 

T value = 0.86

Sig. = N.S.

 

T value = 1.40

Sig. = N.S.

 

aThe figures represent the number of cases, not projects; individuals with zero projects have been excluded.

bHomemakers were included within the blue collar classification.

cSingle respondents were never married, widowed, divorced, or separated.

 

Although the information in Table 9 is not presented here necessarily in support of hypothesis 2 or 3, the findings should provide useful information for future researchers and program planners. In essence, the data trends suggest that younger people, white collar workers, males, urban residents, people living in homes or apartments, college graduates, non-whites, married people, and upper/upper middle class people are more likely to be engaged in instrumental activities. Females , urban residents, white collar workers, college graduates, non-married individuals, and upper/upper middle class people are more likely to be engaged in expressive forms of learning. Table 21 in Appendix B contains some supplemental data.

 

Learning Projects

 

Interviewers asked a variety of probing questions to help respondents recall the number of different learning projects and number of hours spent with each project. As Table 10 shows, the older people interviewed are spending a considerable amount of time each year in learning endeavors. It should be noted that 42 people choose not to or were unable to supply information relative to learning projects because of fatigue or unwillingness. Most of these individuals fell in the older and/or lower class groupings. Consequently, a base of 214 people will be utilized throughout this section.

 

Table 10. Older Adults’ Learning Projects: General Descriptive Informationa.

 

Informational Descriptionb

Hoursc

Projectsd

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

55-64

17,900,000

04.5

65 & Over

18,600,000

01.6

aBased on 214 individuals with one or more learning projects.

bSee Coolican (1973, p. 12) for comparable data.

cTotal number of hours = 69,456.

dTotal number of projects = 712.

 

In addition to actual learning activity, the interviewers all noted that most people spent many hours each week of their life watching television programs of an entertainment nature as opposed to an educational nature. One obvious conclusion from this information is the fact that the typical older person in Nebraska keeps active or busy in a variety of ways.

 

Tables 11 and 12 outline the number of different projects and number of hours spent in learning. Although the majority of the respondents carried out fewer than four projects and spent fewer than 300 hours in 1earning, many people are engaged in considerable learning each year. To give you a flavor of the learning activity, three examples are given:

 

n      One 86 year old gentleman in Lincoln spent nearly 600 hours last year learning how to grow an organic garden. His activities included attending meetings, reading books, watching ETV programs on gardening, attending gardening meetings, and talking with other gardeners.

n      An 81 year old Lincoln woman spent nearly 1200 hours last year researching for her autobiography. She remarked that she doesn't really care if it is ever published; she just wants to write it.

n      A semi-retired 69 year old factory worker devoted over 2000 hours to research for several magazine articles he is writing. He has had several things published over the years.

 

Table 11. Number of Learning Projects Conducted In A Year.

 

Number of Projectsa

Number of People

Percent of Peopleb

Accumulative Percent

0

41

--

--

1

46

21.4

021.4

2

43

20.0

041.4

3

34

15.8

057.2

4

38

17.7

074.9

5

26

12.1

087.0

6

14

06.5

093.5

7

05

02.3

095.8

8

06

02.8

098.6

9

03

01.4

100.0

aSee Tough (1971, p. 17) for comparable data.

bBased on 214 individuals.

 

Table 12. Number of Hours Spent in Learning In A Year.

 

Number of Hoursa

Number of People

Percent of People

Accumulative Percent

12-99

37

17.29

017.29

100-199

51

23.83

041.12

200-299

38

17.76

58.88

300-399

39

12.55

72.43

400-499

19

08.88

81.31

500-599

12

05.61

86.92

600-699

09

04.21

91.13

700-799

03

01.40

92.53

800-899

05

02.34

94.87

900-999

06

02.80

97.67

1000-1499

03

01.40

99.07

1500-1999

01

00.47

99.54

2000-2300

01

00.47

100.01b

aSee Tough (1971, p. 18) for comparable data.

bRounding error.

 

The information on learning projects was compared with various demographic variables to ascertain a better picture of the learning activities. Table 13 contains this information. If a composite picture is possible, the active older learner in Nebraska more often than not is 55-64 years of age, rural/non-town, white American, upper class, living in an apartment, not married, and highly educated. No discernible trends were obvious for the characteristics of “gender” and “occupation” because of similar percentages or small numbers in the various categories.

 

Table 13. Comparisons of Learning Projects Information With Various Demographic Variables.

 

Comparison Variables

No. of People

Average No.

of Projects

Range of

Projects

Average No.

of  Hours

Range of

Hours

Age:

 

 

 

 

 

55-64

091

3.43

1-9

336.74

12-1675

65 and older

123

3.26

1-9

315.54

20-2300

Community:

 

 

 

 

 

Urban

126

3.44

1-9

352.11

12-1675

Rural/Non-Town

036

3.75

1-8

388.44

20-2300

Rural/Small Town

052

2.72

1-6

211.30

12-1675

Gender

 

 

 

 

 

Male

089

3.19

1-9

327.65

20-2300

Female

125

3.43

1-9

322.35

12-1675

Race:

 

 

 

 

 

White American

185

3.29

1-9

333.52

12-2300

Black American

001

3.00

3

350.00

1050

Mexican American

028

3.64

1-6

239.71

20-668

Social Class:

 

 

 

 

 

Lower

014

2.93

1-6

256.29

50-990

Lower Middle

085

2.96

1-9

293.59

20-2300

Upper Middle

101

3.48

1-9

307.18

12-1296

Upper

014

4.64

2-7

590.86

212-1675

Living Arrangement:

 

 

 

 

 

Apartment

028

3.71

1-9

413.39

26-999

Home/House

159

3.21

1-9

310.40

12-2300

Institution

018

3.73

1-9

232.44

75-450

Other

009

3.56

2-8

302.67

50-668

Marital Status:

 

 

 

 

 

Married

140

3.30

1-9

302.51

12-2300

Widowed

051

3.18

1-7

357.83

35-1675

Single

016

4.32

1-9

307.19

30-910

Divorced/Separated

007

2.85

1-5

337.86

26-955

Education:

 

 

 

 

 

Under 8th Grade

022

3.22

1-6

250.55

50-668

8 – 11th Grade

045

2.40

1-7

222.22

20-999

H.S. Graduate

065

3.26

1-8

304.66

12-1675

Some College

034

3.76

1-8

443.50

25-2300

College Graduate

024

3.75

1-9

276.38

30-815

Graduate Training

024

4.25

1-9

452.92

20-1296

Occupation:

 

 

 

 

 

Highest Professional

009

4.32

1-6

354.33

136-659

Lower Professional

045

3.51

1-9

370.11

20-1296

Admin. Personnel

014

4.57

1-9

388.14

45-945

Homemaker

066

3.21

1-8

302.03

20-1675

Clerical/Sales/Technician

029

3.48

1-8

273.62

12-700

Skilled Manual

031

2.81

1-9

242.59

20-990

Semi-skilled/Operative

014

2.58

1-8

358.00

20-2300

Unskilled

005

3.01

1-4

283.00

100-580

aSee Tough (1971, pp. 20-21) and Coolican (1973, p. 12) for comparable data.

 

Respondents were also asked to make judgements about each project they reported. They were asked about the current status of the project at the time of the interview, the reason for doing the project, the primary planner of the learning activity, the subject matter area studied, and the source of the subject matter. The resulting data are contained in Table 14.

 

Table 14. Learning Projects: Supportive Informationa.

 

Informational Description

No. of Projectsb

Percent of Projects

Current Status of Projects:

 

 

Inactive

176

24.79

Active

534

75.21

Reason for Doing Project:

 

 

To Obtain 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/Non-Human Resource

028

03.95

The Learner Him or Herself

391

55.15

Mixed (No Dominant Type of Planner)

072

10.16

Subject Matter Area:c

 

 

Occupational/Vocational

115

16.17

Personal/Family

144

20.25

Social/Civic

067

09.42

Self-Fulfillment

385

54.15

Source of Subject Matter:

 

 

Group/Group Instructor

086

12.11

Expert

032

04.51

Books, Pamphlets, Newspapers

222

31.27

Programmed Materials

020

02.82

TV/Radio/Recordings

066

09.30

Displays/Exhibits/Museums/Galleries

008

01.13

Friend/Relative/Neighbor

053

07.47

Mixed Sources

223

31.41

aSee Tough (1971, pp. 86-88) and Coolican (1973, p. 12-13) for comparable data.

bProject totals for each major category are not always equal because of occasional non-responses.

cSee the definitions in Chapter 1.

 

Only about one-quarter of the projects were inactive, perhaps reflecting the role learning continuously plays in fulfilling needs and in satisfying interests. Nearly 70% of all the primary reasons given for undertaking a project were of a purely enjoyment nature. It also turns out that the learner himself or herself plans most of the projects, or an average of 2.14 of all projects (see Table 15). 

 

Table 15. Frequency of Type of Primary Planners of Learning Projects.

 

Primary Planner of Project

No. With At Least one Project

Average No.

With Planner

A Group or its Leader/Instructor

086

1.69

One Person in One-to-One Situation

048

1.52

Material/Non-Human Resource

022

1.27

The Learner Him or Herself

022

1.27

Mixed (No Dominant Type)

046

1.57

 

The subject matter areas studied were varied, although more than half of the projects were reported as self-fulfillment in nature (see the definitions in Chapter 1). Some comparisons of the subject matter areas with various demographic variables are shown in a later table. Table 14 also contained information as to the primary source of the subject matter information reported by respondents. Books, pamphlets, and newspapers served as the biggest single source of information. Unfortunately from the researcher’s point of view in terms of a community’s educational potential, the community and its resources were little utilized for learning needs (Hiemstra, 1972b).

 

Table 16 contains some comparison information on the choice of subject matter area according to various demographic characteristics. As can be seen, there was considerable difference in choice according to the various sub-categories. Younger educated people, clerical/sales/technician employees, skilled manual workers, unskilled people, and homemakers were more likely to report self fulfillment projects. The data in Table 16 were also analyzed by chi-square according to the collapsed categories utilized earlier. Every comparison was significant at the .05 level or beyond. Certainly these findings should suggest several subsequent research ideas. 

 

Table 16. Comparison of Subject Matter Area By Various Demographic Variablesa.

 

Comparison Variables

Occupational/

Vocational No.

Occupational/

Vocational

%

Personal/

Family No.

Personal/

Family %

Social/

Civic No.

Social/

Civic %

Self-Fulfillment

No.

Self-Fulfillment %

Age:

 

 

 

 

 

 

 

 

55-64

085

27.33

072

23.15

023

07.40

131

42.12

65 and older

030

07.50

072

18.00

044

11.00

254

63.50

χ2 = 62.01; Sig. = < .001

 

 

 

 

 

 

 

 

Community:

 

 

 

 

 

 

 

 

Lincoln

080

18.48

095

21.94

047

10.85

211

48.73

Rural/Non-Town

022

16.42

025

18.66

008

05.97

079

58.96

Rural/Small Town

013

09.03

024

16.67

012

08.33

095

65.97

χ2 = 13.60; Sig. = < .01

 

 

 

 

 

 

 

 

Gender:

 

 

 

 

 

 

 

 

Male

076

26.86

050

17.67

020

07.07

137

48.41

Female

039

09.11

094

21.96

047

10.98

248

57.94

χ2 = 40.34; Sig. = < .01

 

 

 

 

 

 

 

 

Race:

 

 

 

 

 

 

 

 

White American

110

18.12

109

17.96

064

10.54

324

53.38

Black American

000

00.00

003

100.00

000

00.00

000

00.00

Mexican American

005

04.95

032

31.68

003

02.97

061

60.40

χ2 = 26.52; Sig. = < .001

 

 

 

 

 

 

 

 

Social Class:

 

 

 

 

 

 

 

 

Lower

004

10.53

008

21.06

000

00.00

026

68.42

Lower Middle

032

12.90

061

24.60

021

08.47

134

54.03

Upper Middle

062

17.82

061

17.53

030

08.62

195

56.03

Upper

017

22.08

014

18.18

016

20.78

030

38.96

χ2 = 9.93; Sig. = < .05

 

 

 

 

 

 

 

 

Living Arrangement:

 

 

 

 

 

 

 

 

Apartment

023

12.07

022

19.82

017

15.32

049

44.14

Home

087

11.76

104

21.05

036

07.29

267

54.05

Institution

000

00.00

008

11.10

014

19.18

051

69.86

Other

005

15.15

010

30.30

000

00.00

018

54.55

χ2 = 14.70; Sig. = < .01

 

 

 

 

 

 

 

 

Marriage Status:

 

 

 

 

 

 

 

 

Married

085

18.44

087

18.87

026

05.64

263

57.05

Widowed

015

08.98

043

25.75

025

14.97

084

50.30

Single

007

10.94

008

12.50

013

20.31

036

56.25

Divorced/Separated

008

42.11

006

31.58

003

15.79

002

10.53

χ2 = 11.64; Sig. = < .01

 

 

 

 

 

 

 

 

Education:

 

 

 

 

 

 

 

 

Less than 8th Grade

002

02.90

021

30.43

001

01.45

045

65.22

8-11th Grade

011

10.00

020

18.18

013

11.82

066

60.00

High School Grad.

026

12.68

043

20.98

022

10.73

114

55.61

Some College

024

17.65

023

16.91

011

08.09

078

56.35

College Graduate

016

17.98

019

21.35

012

13.48

042

47.19

Graduate Training

036

35.64

018

17.82

008

07.92

039

38.61

χ2 = 26.59; Sig. = < .001

 

 

 

 

 

 

 

 

Occupation:

 

 

 

 

 

 

 

 

Highest Professional

013

27.08

006

12.50

006

12.50

023

47.92

Lower Professional

040

26.14

029

18.95

012

07.84

072

47.06

Administrative Pers.

024

37.50

012

18.75

004

06.25

024

37.50

Homemaker

009

04.23

051

23.94

022

10.33

131

61.50

Clerical/Sales/Tech.

010

10.53

024

25.26

003

03.16

058

61.05

Skilled Manual

009

27.27

014

16.28

011

12.79

052

60.47

Semi-Skilled/Operative

009

27.27

044

12.12

003

09.09

017

51.52

Unskilled

001

07.69

004

30.77

000

00.00

008

61.54

χ2 = 34.33; Sig. = < .001

 

 

 

 

 

 

 

 

aChi-square values are based on the collapsed categories as displayed in Table 9. Percentages are based on comparison variable sub-category totals.

 

 

The fourth hypothesis suggested that no significant differences would be found in the average number of learning projects or hours spent in learning according to various demographic characteristics. As Tables 17 and 18 show, the null hypothesis is supported almost totally. There are no significant differences in the number of hours spent by the population in a pursuit of learning. When the number of learning projects was examined, three significant differences emerged: The two combined upper class groups carried out more projects than the two combined lower groups; college graduates carried out more projects than non-college graduates; white collar workers carried out more learning projects than did blue collar workers.

 

Table 17. T-test Comparisons of Various Demographic Variables with the Number of Hours Spent Annually in Learning.

 

Comparison Variables

No. in

Group

No. of Hours

Mean

No. of Hours

St. Dev.

Age:

 

 

 

55-64

091

336.74

315.81

65 and older

123

315.54

304.91

T value = 0.49; Sig. = N.S.

 

 

 

Community:

 

 

 

Urban

126

352.11

310.95

Rural

088

285.10

303.68

T value = 1.57; Sig. = N.S.

 

 

 

Gender:

 

 

 

Female

125

322.35

296.68

Male

089

327.65

327.29

T value = 1.12; Sig. = N.S.

 

 

 

Race:

 

 

 

White American

185

333.52

320.40

Other

029

267.34

219.02

T value = 1.07; Sig. = N.S.

 

 

 

Social Class:

 

 

 

Lower/Lower Middle

099

287.21

314.00

Upper Middle/Upper

115

356.70

302.38

T value = -1.64; Sig. = N.S.

 

 

 

Living Arrangement:

 

 

 

Institution/Other

027

255.85

145.30

Apartment/Home/House

187

334.48

325.01

T value = -1.24; Sig. = N.S.

 

 

 

Marital Status:

 

 

 

Married/Widowed

191

318.18

295.77

Not Married

023

377.48

407.23

T value = -0.87; Sig. = N.S.

 

 

 

Education:

 

 

 

College Graduate

048

366.73

298.73

Non-College Graduate

165

312.74

312.68

T value = 1.09; Sig. = N.S.