Changes in the Demographics and Motivations of Distance Education Students |
Lori Wallace
VOL. 11, No. 1, 1-31
University distance education students are typically presented as adults, studying part-time, often at a geographic distance from the campus. Evidence suggests, however, that the demographics of distance learners are changing. This study investigated the nature and magnitude of such changes at a Western Canadian university and the reasons why historically atypical students are enrolling in distance education.
Demographic shifts were investigated using enrolment data from the past decade. Results indicate that the independent study population has shifted toward younger students, local residence, and full-time course loads that combine independent study with on-campus courses. These shifts indicate a convergence in characteristics of the independent study and on-campus populations, a trend that also appears to be shared by other western Canadian universities.
A survey instrument based on a conceptual model of "pushes" (responses to barriers) and "pulls" (attractions of independent study) was developed to investigate the reasons why historically atypical students enrol in independent study. Results suggest that the most important barrier pushing students toward registration in independent study is work commitments; the most important attractions relate to control of the time, place, and pace of learning. Factor analysis of the reasons supports the validity of the barriers-attractions model.
Institutional and programmatic implications include needed changes to instructional design, student support services, and policies regarding teaching resources and tuition fee distribution. Implications for the field of distance education include a challenge to the assumptions that distance education students are largely part-time adult learners, and employment is a barrier to study only for adult students.
On présente généralement les étudiants universitaires à distance comme des adultes qui étudient à temps partiel, souvent loin du campus. En réalité, cependant, les facteurs démographiques qui caractérisent les apprenants à distance changent. La présente étude s'est penchée sur la nature et sur l'ampleur de ces changements dans une université de l'Ouest du Canada et sur les raisons motivant des étudiants traditionnellement atypiques à s'inscrire à des cours à distance.
Les facteurs démographiques ont donc été analysés à partir des données sur les inscriptions au cours de la dernière décennie. Selon les résultats, les apprenants autonomes sont maintenant de plus en plus jeunes, résident sur place et suivent des cours à temps complet à la fois de façon indépendante et aussi à l'univesité. Cette évolution témoigne d'une convergence des caractéristiques des apprenants autonomes et des étudiants sur le campus, qui semble se manifester également dans d'autres universités de l'Ouest du Canada.
On a conçu un instrument de sondage fondé sur le concept de « pression » (face aux barrières) et « d'attrait » (pour l'étude indépendante), afin d'étudier les raisons pour lesquelles des étudiants autonomes atypiques s'inscrivaient à de tels programmes d'études. Les résultats obtenus montrent que d'une part, le travail est la principale pression exercée sur les étudiants, en faveur des études indépendantes. D'autre part, le principal attrait est la possibilité de gérer son temps et son rythme d'apprentissage. L'analyse de ces facteurs confirme la validité du modèle inspiré du concept de « pression et d'attrait ».
Entre autres conséquences pour les établissements et les programmes, mentionnons la nécessité de modifier la conception pédagogique, les services de soutien aux étudiants et les politiques en matière de ressources d'enseignement et de répartition des droits de scolarité. Dans le domaine de l'éducation à distance, il faudra revoir les hypothèses selon lesquelles les étudiants à distance sont en grande partie des apprenants adultes à temps partiel, et l'emploi, une pression que vivent uniquement les étudiants adultes.
The Canadian experience with university distance education has its historical roots in faculty outreach activities designed to extend educational opportunities to disadvantaged learners. Typically, those learners have been adult part-time students and those at a geographic distance from the university (Sweet, 1989).
That distance learners are part-time, adult students is a stereotype frequently reinforced in the distance education literature. What has been written about demographic changes in distance education users in Canada has most often been with respect to the influx of adult, lifelong learners into distance education and the particular needs and characteristics they present (Garrison, 1989; Mugridge & Kaufman, 1986).
As in the case of many other Canadian universities, this perception of distance education students has guided the development of distance education courses and student support services at the University of Manitoba. A systematic distance education client analysis, however, had never been carried out at this institution, and after a decade in which enrolments quadrupled, impressionistic evidence suggested that the demographics of the independent study student population were changing and a study was, therefore, undertaken to investigate these assumptions.1
The research problem centred on establishing whether the degree-credit independent study student population has changed from its traditional base, and if so, how and why. The specific research questions addressed in this study are:
Most terms used in this study are familiar to distance educators; two, however, require clarification:
The flexibility that distance education offers in terms of where and when students learn has been particularly advantageous to two groups of students: a) those who live at a geographic distance from the university, and b) those who are fully employed (either at home or in the workplace) and who must pursue a university education on a part-time basis. Because the fully employed tend to be older individuals, distance education has provided access for many adults who are unable to attend scheduled classes on-campus. Hence, enrolment in distance education has traditionally been heavily adult (i.e., older than traditional on-campus students, many of whom have proceeded directly from high school to university and who do not have full-time work commitments).
As a consequence of this history, distance education has become closely associated with adult education, both in practice and in the literature. Moreover, since successful adult education requires a more flexible approach than traditional on-campus programs typically provide, distance education has also come to be identified with greater flexibility, as exemplified, for example, by open universities. These are typically single-mode distance institutions that have no age or academic admissions criteria and that use flexible scheduling, curriculum, and methods of instruction (Leach & Webb, 1993).
Themes drawn from adult education that have also come to dominate the distance education literature include the observations that adult students are different in terms of life circumstances, development, and experience (e.g., they are usually part-time students who assume a multitude of roles, such as full-time worker, spouse, and family caretaker and who are looking for practical implications of new knowledge, particularly for the world of work). These differences between distance students and on-campus students have formed the basis for different institutional responses in terms of policies, learner support, and instructional design.
That students taking courses by distance education are adult learners is a widespread observation in the distance education literature. Moore (1985), for example, comments: “Most distance education is concerned with the education of adults and it seems fairly obvious that our research plans should be informed by the theories and research about learning in adulthood, adult development, program planning, instruction and evaluation in adult education” (p. 36).
The distance education literature confirms this view of distance education students as adult learners (e.g., Bates, 1989; Coldeway, 1986; Courtney, 1992; Hardy & Olcott, 1995; Holmberg, 1995; Thompson, 1989; van Enckevort, 1986). The following quotations are representative:
The principles and rationale of higher distance education are essentially those of adult education. Adults are the primary audience we serve and the methods we have adopted have historically respected the voluntariness of adult learning. (Garrison & Shale, 1990, p. 131)
The data demonstrate significant demographic differences existing between correspondence students and students traditionally served by colleges and universities. Because of the vast differences in age, sex, college classification, marital status, and enrolment status, it would be wrong to treat both populations in similar ways. (Leverenz, 1981, p. 554) The research in this area, however, has distinct limitations and many questions, particularly regarding demographics, remain to be answered, as Coldeway (1986) and Morrison (1986) have noted. Nevertheless, the literature does confirm the long-standing view that distance learners are predominately adults who are pursuing a university education on a part-time basis. This assumption is rarely questioned and, when it is, no hard data are offered (e.g., Holmberg, 1995; Jevons, 1990).
Although gender is not a variable included in the research question for this study, it is worth noting that the review of the literature also confirms that there is widespread agreement that female students outnumber males in distance education. The majority of the sources cited at the beginning of this section (i.e., in the discussion of the view of distance education students as adult students) also indicate that the majority of the students in those programs are female.
There has been considerable distance education research activity regarding a) what happens to students after they enrol in distance education courses (e.g., research on student support, and student satisfaction, dropout or persistence), b) delivery technologies, or c) on the process of distance learning (e.g., Garrison, 1989; Holmberg, 1979; Moore, 1985). Relatively less work has been done to investigate the reasons why students enrol in distance education courses in the first place.
In an attempt to develop a more comprehensive theoretical model of participation for university distance education, it is first useful to note Courtney’s (1992) distinction between “decision-making” models and “origin-of-the-learning-need” models. Decision-making models focus on conditions (social and environmental, as well as psychological) that have an impact on the decision-making process, whereas origin-of-the-learning-need models attempt to account for the origin of the learning need from the psychological standpoint of enduring personality traits and developmental life stages. Both types of model have been used in adult education research. The work of Houle (1961) and Boshier and Collins (1985), on the motivational orientations of adults, provides an example of the origin-of-the- learning-need model, and the work of Cross (1981) and Darkenwald and Merriam (1982) on factors influencing participation, provides an example of the decision-making model.
Although there is clearly some overlap in the two types of models, the decision-making type of model was deemed more appropriate for present purposes because decision models more closely resemble:
. . . independent conceptualizations which break down the conditions governing the act of participation into different elements, some personal and psychological, others social and sociological. Here, the focus is on the decision which leads to the action called participation, rather than on motives as such. Hence, all explanatory theories under this heading pay more attention to the conditions influencing action. (Courtney, 1992, p. 53)
The majority of these decision-making models utilize the notion of “force-field” as originally developed by Lewin (1952). Lewin’s concep-tualizatiosn placed the individual, who seeks equilibrium, within the larger context of psychological and environmental “life space.” Lewin used the term “force” to describe the direction (valence) and strength (vector) of tensions and needs. Forces within individuals and forces outside them interact to direct individuals’ actions in certain ways. There are forces that impel the individual toward a certain action (pulls), and there are forces restraining or exerting pressure against that action (pushes).
Miller (1967) was the first to apply Lewin’s force-field conceptualization to an examination of adult participation in education but, as Courtney (1992) indicates, others have followed his lead. At least six adult education decision-making models owe a conceptual debt to Lewin’s work. These include Cookson (1989), Cross (1981), Darkenwald and Merriam (1982), Groteluschen and Caulley (as cited in Courtney, 1992), and Rubenson (as cited in Courtney, 1992).
Though a useful starting point, these existing models cannot be directly applied to this study for the following reasons: the models have been developed with a focus solely on the adult learner and, therefore, pay attention only to the particular forces and circumstances important to that age group; they make no distinctions between classroom and distance learning; and finally, they have been developed to investigate the question of why individuals engage in educational pursuits in the first place, rather than why they might choose one delivery mode over another. Nevertheless, Lewin’s (1952) notion of a force field has proven valuable in decision-making models, and the conceptualization of factors influencing decisions as “pushes” and “pulls” provides a useful theoretical framework for assessing the reasons why students decide to participate in distance education rather than attend on-campus classes. If one conceives of “pushes” as consisting of barriers that inhibit access to on-campus learning and “pulls” as consisting of attractions to distance learning, a meaningful framework is provided for analyzing previous research on the question.
Much of the previous research has focused on barriers rather than on attractions and Cross’s (1981) work is particularly important. Cross (1981) views barriers as falling into three types: situational (circumstances in the individual’s life such as family and work), institutional (organizational policies and procedures), and dispositional (attitudes toward self and learning). Darkenwald and Merriam’s (1982) research on barriers extended Cross’s model with the addition of another type of barrier-informational- as represented by a lack of information regarding educational opportunities. They also relabelled dispositional barriers, “psychosocial.”
Cross’s conceptualization has been utilized by a number of researchers in distance education (Heinze, 1983; Hezel & Dirr, 1991; Rubenson, 1986; van Enckevort, 1986; Willet, 1984), most of whom focus on situational barriers such as geographic distance and the family and work commitments of adults. Heinze (1983) and van Enckevort (1986), for example, examined the situational barriers affecting adult learners and found that the demands of work and family commitments, which tie learners to particular places and create time conflicts, emerged as the most important of these. Brey and Grigsby (1984), Crane (1985), Rubenson (1986), and Schrader (1987) also reported that situational barriers dominate the reasons why adult learners choose distance education, and Hezel and Dirr (1991) found that time constraints arising from conflicting demands outweighed distance constraints for adult students taking telecourses. Physical disability has also been identified as a situational barrier for some individuals (Perry, 1986) as have role conflicts (Garland, 1993; Heinz, 1983).
The research into gender differences has found that female students are not only more likely to encounter situational barriers than are males, but they are also more likely to experience dispositional barriers (Grace, 1994; Johnstone & Rivera, 1965; Norquay, 1986; von Prummer, 1990). These researchers found that women more often experienced a lack of confidence in their academic abilities and reported fears about being unable to complete the course. Grace (1994) commented that her research suggests that the invisibility of the distance education student is compounded by gender because women have historically been excluded from the processes by which knowledge is constructed. Coulter (1989) further cautions that distance education may promote the “ghettoization” of women. Other studies of dispositional barriers report that these tend to become more formidable with increasing age (Johnstone & Rivera, 1965; Rubenson, 1986).
Less research has been done on informational or institutional barriers, but Rubenson (1986) reports that “red tape” and inflexible policies, inadequate learner support, and inconvenient course times and locations are characteristics of universities that may limit access to on-campus learning.
As noted earlier, research into the reasons why students decide to participate in distance education has focused on barriers that inhibit access to on-campus courses rather than on the attractions of distance learning. Although the two are obviously related, they also pose an important difference in emphasis. Do students participate in distance education primarily for negative reasons (i.e., because of barriers to on-campus learning), or do they also participate for positive reasons (i.e., because of the attractions of distance learning)? As was noted earlier, distance education has come to be identified with greater flexibility and openness than is characteristic of on-campus education, and it seems reasonable to assume that this feature alone would be seen as an important attraction by at least some students.
Attractions have not been entirely ignored, however. Flinck (1978) and Dodds, Lawrence, and Guitton (1984), for example, found that students felt that distance education offered advantages in terms of control over the pace and time of studies. Leach and Webb (1993) found that reasons such as “prefer to study in own time,” “prefer to study at own pace,” and “prefer to study at home” were among the top reasons cited for enrolling in a distance course. Other studies (Ahlm, 1972; Beijer, 1972; Moore, 1985; Thompson & Knox, 1987) suggested that the independence offered by this mode of study extends beyond the choice of “when and where” to preferences for independence in terms of interaction (i.e., the opportunity to work alone with minimal contact with instructors or fellow students). In studies of telecourse students, Brey and Grigsby (1984) and Crane (1985) found that for some students, the opportunity to learn at home or to try a new learning method were important reasons why they became distance learners. Although these authors do not distinguish between barriers and attractions as I have proposed, it does appear that these reasons are expressions of attractions and suggest that individuals may be drawn to distance education courses because such courses better fit their learning style or preference.
The terms learning style and learning preference have been used (often interchangeably) to describe a large range of individual differences with respect to learning, but as Merriam and Caffarella (1991) point out, there is no unified theory upon which the research is based, nor is there even agreement on a common definition of terms such as learning style. This lack of coherence in the large body of learning styles literature creates considerable difficulty in the task of evaluating or classifying the numerous instruments that have been published.
A helpful way to organize the learning styles literature has been proposed by Curry (1983). In Curry’s model the metaphor of an onion is used to illustrate how the different dimensions of an individual’s makeup layer upon each other to create a “learning style.” At the core of the onion are basic characteristics of personality such as introversion/extroversion and impulsivity/reflectivity. The second layer is comprised of cognitive processing characteristics and relates to how the individual organizes and processes incoming information, and the third layer is comprised of social interaction characteristics and relates to how the individual interacts with others. The outer layer, learning preference, grows out of the previous layers and comprises the individual’s preferences with regard to learning methods and environments.
The distinctions between learning style and learning preference made in Curry’s model reflect the earlier work of Rezler and Rezmovic (1981) in which learning style is defined as the manner in which a person perceives and processes information in a learning situation, and learning preference is defined as the choice of one learning situation over another. These distinctions have been subsequently employed by others in the categorization of learning style research and inventories (e.g., Claxton & Murrell, 1987) and are helpful in the present study. As defined, learning preference would appear to be more relevant to a study of the attractions of distance learning than is learning style because the distinguishing characteristics of independent study relate most directly to choices in the learning situation (e.g., time and place, structure, pacing, interaction, and mode of delivery).
There are a number of studies on learning preference reported in the literature (Loesch & Foley, 1988; Ostmoe, Van Hoozer, Scheffel, & Crowell, 1984; Rezler & Rezmovic, 1981), but perhaps the most useful for present purposes is the work of Canfield (1977, 1988). Canfield’s work has been described by Loesch and Foley (1988) and Claxton and Murell (1987) as an inventory which measures learning preference and has also been referred to as such by Canfield himself (Boyland, 1981). The Canfield Inventory measures the attitudinal variables that affect the teaching-learning situation with a 30-item inventory based on three dimensions of learning preference: preferred conditions of learning, preferred content of learning, and preferred mode of learning. Canfield (1977) defines the conditions of learning as “dynamics of the situation in which learning occurs” (p. 24) and includes measures of preference for affiliation with peers and instructor, organization and detailed structure, independence and individual goal-setting, and authority and competition. Preferred content of learning includes measures of preference for learning with numerics, language, objects, and people.
The preferred mode of learning refers to the “general modality in which learning is preferred” (Canfield, 1977, p. 8) and includes measures of preference for listening, reading, visuals, and direct experience. The Canfield Inventory also incorporates a measure of the individual’s accuracy in predicting his or her performance, but this is more specifically related to academic persistence.
The Canfield Inventory has been utilized in distance education research in studies of persistence and dropout (Coggins, 1988; Gibson & Graff, 1992), and it is within that context that it is best suited (Claxton & Murrell, 1987). Nevertheless, it is a useful source of suggestions as to the possible attractions of distance learning over on-campus learning and was utilized in the development of the survey questionnaire.
The population for this component of the study consisted of all students at the University of Manitoba who had been enrolled in a degree-credit independent study course during the Regular Session in any of the years 1983-84 to 1994-95, regardless of whether or not they subsequently withdrew (N = 16,111). The following fields were then extracted from the archived student records: age at time of enrolment, gender, residence (in the city of Winnipeg versus outside), course load, and type of registration (independent study only versus independent study concurrent with on-campus courses).
On-campus enrolment data from the University of Manitoba were compared to the independent study data with respect to total student numbers, age, residence, and course load. Limited data from eight western Canadian universities that offer independent study courses were also obtained with a view to placing the University of Manitoba trends within a larger Canadian context.
Descriptive statistics were used to examine enrolment data for the 11 years of the study (e.g., calculation of means, measures of central tendency, and bivariate analysis of relationships between variables). Tests of statistical significance were unnecessary as the data represented the entire population.
Figure 1 illustrates the shift from residence outside Winnipeg to inside the city, from adult learners to more typical undergraduate students, from part-time students to full-time students, and from exclusively independent study course registration to concurrent registration. Table 1 presents relevant data in tabular form and confirms that the period under study was marked by considerable change. The total number of students enrolled in independent study more than quadrupled, increasing from 497 in 1983-84 to 2152 in 1994-95. The composition of the student body changed with respect to each of the demographic variables identified by the research question. The mean age of independent study students dropped steadily from 32 years of age in 1983-84 to 26 years of age in 1994-95, and the percentage of students under the age of 26 years more than doubled (to 65%). The percentage of independent study students living in the city of Winnipeg almost doubled, growing from 38.5 in 1983-84 to 72.8 in 1994-95. The percentage of students taking an independent study course concurrent with an on-campus course more than doubled, increasing from 29.2 in 1983-84 to 65.9 in 1994-95. Although the mean number of independent study credit hours in which students registered remained almost constant (varying no more than .58 credit hours throughout the period), a substantial upward shift occurred in the mean number of concurrent on-campus credit hours (from 6.2 in 1983-84 to 11.9 in 1994-95), and it is this increase in concurrent on-campus credit hours that accounts for the increase in the mean total number of credit hours enrolled (from 11.8 in 1983-84 to 17.1 in 1994-95).
These figures confirm that there have been dramatic and interrelated shifts in the age, residence, and course load of independent study students. A decade ago, the independent study population was similar to the population described in the distance education literature: adult, part-time students often studying at geographic distance from the university. The profile that emerges in the present study depicts students of typical undergraduate age studying heavier course loads by combining independent study with on-campus study and living in close proximity to the campus.
One question that arises in considering the shift described above is whether it is unique to independent study students or whether it simply reflects similar changes in the general on-campus student population at the University of Manitoba. In order to answer this question, enrolment data for undergraduate on-campus programs were examined for the period 1983-84 to 1993-94 (a revised formula for the calculation of full-time status was employed by the University in 1994-95, rendering data for that year unusable in this study). The specific objective was to determine whether the independent study trend toward younger students and heavier course loads was applicable also to the general on-campus student population.
Analysis of the data showed that total enrolment at the University of Manitoba has increased only marginally in the past decade (4%). The data previously presented on independent study enrolment, however, indicate an increase of over 400% in independent study enrolments, suggesting that the increased demand for independent study courses is not part of an overall increase in demand for university courses. The analysis also demonstrated that the proportion of part-time students on-campus has increased. This, of course, is counter to the trend observed for independent study students, and suggests that the two populations are becoming more alike with respect to course loads.
With respect to age, Table 2 indicates that the overall percentage of on-campus students under the age of 26 has increased by 8.5%. This parallels the trend observed for independent study students but it is much less pronounced. With respect to course load, it appears that the on-campus trend is toward part-time study by younger students. (In 1983-84 students under the age of 26 years comprised 42.5% of part-time learners; in 1993- 94 they comprised 64.9% of that group.) This trend is opposite to the age-course load trend in independent study.
The analysis of the enrolment trends in the independent study and on-campus populations indicates that the two populations do not simply mirror one another. Although both populations are getting younger, the rates of growth are very different as is the direction of growth in terms of course load. Although gender was not identified as a key variable in this study, it is worth noting that the gender proportions within the independent study population and the gender proportions within the on-campus population demonstrated little variation. Females have continued their traditional domination of the independent study population, and the almost equal gender split of the on-campus population has been maintained.
A limited attempt was also made to determine whether the University of Manitoba trends in degree-credit independent study were applicable at other dual-mode western Canadian universities. To this end, eight universities were contacted: University of Victoria, University of British Columbia, Simon Fraser University, University of Alberta, University of Calgary, University of Saskatchewan, University of Regina, and Brandon University. Enrolment trends at the University of Manitoba were described, and the other institutions were invited to respond with impressionistic and, if pos-sible, empirical data as to whether these trends applied to them. Responses were received from six universities and four yielded information that allowed meaningful comparisons. (The University of Calgary indicated that print-based independent study was not offered as part of the distance education program, and the University of Alberta indicated that, as distance education was not centrally coordinated there, no institutional data were available. Neither of these institutions was, therefore, included in the comparisons.)
It is important to recognize the difficulties in making institutional comparisons in that data collection methods and categories frequently vary. Despite these difficulties in effecting meaningful comparisons, the following observations are warranted:
The population in this component of the study consisted of all students who were registered for an independent study course during the Regular Session 1994-95 and who lived in the city of Winnipeg (N = 1566). The purpose of the survey was to investigate the reasons why students living in Winnipeg, where presumably they have on-campus access to two universities, were nevertheless enrolling in independent study courses in rapidly increasing numbers. In other words, the research focused on the reasons why students chose one mode of delivery (independent study) over another (on-campus) for their university courses rather than on their reasons for pursuing a university education per se. The distinction is a crucial one and created some difficulty when previous research and theories were consulted in the development of the survey questionnaire because, as previously noted, most of the literature is devoted to the latter topic.
The theoretical framework of “pushes” (registration in independent study as a response to a barrier to on-campus study) and “pulls” (registration in independent study because of its special appeal) formed the foundation for the development of a research instrument. A structured survey questionnaire was developed to elicit the reasons why local students are choosing to enrol in independent study courses.
As indicated in Table 3, three categories of reasons relating to barriers were developed: situational (work, family, travel, and physical disability), institutional (accessibility and availability of on-campus courses), and psychosocial (lack of academic confidence). Psychosocial (or dispositional) barriers were seen as less relevant to the present study than were situational or institutional barriers because psychosocial barriers refer to attitudes about self that dispose adults against participating in educational programs per se as expressed, for example, in the statement, “I’m too old to begin studying.” Although such perceived barriers might well have an effect on whether or not individuals pursue education, it is less evident how it would affect their choice between on-campus and independent study courses.
Informational barriers were not relevant to the study since information about on-campus courses is at least as available to Winnipeg students as is information about distance education. Moreover, enrolment data indicated that many of the students surveyed were simultaneously enrolled in on-campus and independent study courses.
As noted earlier, previous research provided relatively less guidance with respect to the attractions of distance learning. Learning style inventories were of only limited use, and research on learning preferences (which is more relevant) was insufficiently developed for purposes of the present study. The Canfield (1977, 1988) inventory does, however, provide a basis for developing appropriate questionnaire items relating to the learning preference with respect to conditions and mode of learning. Questionnaire items developed to measure learning preferences based on conditions and mode of learning as they applied to independent study related to studying and learning independently, perceived organization of distance education materials, detailed feedback, learning at own pace, freedom where and when to learn, learning from printed materials, and emphasis on written work.
Canfield’s conceptualization, however, omits students’ preferences regarding ways in which distance learning allows them to better achieve personal or academic goals. Accordingly, another category of attractions, personal and academic goals, was developed. This category included items relating to increased challenge, learning more, better grades, more responsive instructors, convenience, and less interference with leisure time.
Given the cautions in the literature with respect to low survey response rates (Roszkowski & Bean, 1990), and given the experience of the Distance Education Program with student response rates on mail-in course evaluations (which generate less than a 5% response rate), there was concern that the survey might not generate a sufficient sample. The survey questionnaire length was therefore kept as short as possible (15 minute completion time) and other measures were taken to encourage student response as reported in Wallace (1996). The final version of the questionnaire used a single item to measure each reason for enrolling in independent study. Participants were asked to rate the importance of each of the reasons listed on a five-point Likert scale, with five representing the least importance. In addition to measuring reasons for enrolling, the survey elicited demographic information and included an open-ended question that invited participants to add any additional reasons for registering that they felt were missing from the questionnaire.
The survey data were compared to the independent study enrolment data to establish representativeness of the sample with respect to age, gender, and course load. Frequency distributions and means were produced for reasons for enrolling. Frequency distributions and means were also produced (where appropriate) for demographic variables. A factor analysis was conducted to test the conceptualization of reasons into barriers and attractions and the categorizations within barriers and attractions. Responses to the open-ended question (dealing with additional reasons for enrolling) were categorized and discussed in relation to the results of the closed question and the factor analysis.
An acceptable response rate of 63% was obtained. Table 4 reports the results of t-tests conducted on the sample and population means. Because the survey sample was large (986), particularly in comparison to the population (1566), the t-tests indicate statistical differences that are not of substantive significance. The survey data can, therefore, be considered representative of the Winnipeg independent study population with respect to mean age, gender, and number of credit hours enrolled.
The typical respondent in this survey was 23-25 years of age, female, single with no dependent children, working about 20 hours per week in a service sector job. This typical student was a returning university student, having completed at least the equivalent of her first year of course work. She is currently enrolled in three full courses, and there is a 50% chance that the independent study course in which she was registered is not her first. As indicated in Table 5, “work commitments” (V20) was the most frequently cited reason in the survey. This barrier and two others (V10: “on-campus time slot” and V16: “family commitments”) were located in the top third of the ranked reasons. The highest ranked attractions were learning preferences dealing with pace, time or place, and interaction in the learning situation (V19, V22, and V26), followed by attractions dealing with leisure time and reference material (V28 and V18).
The conceptualization of students’ reasons for enrolling in independent study (rather than on-campus) courses as consisting of both barriers and attractions has not been previously utilized. It was important, therefore, to assess statistically its validity via factor analysis.
The process began with the calculation of Pearson product-moment correlation coefficients between all pairs of variables (i.e., reasons for enrolling in independent study courses) with the exception of V17, physical disability. Since this item had the lowest response rate and displayed virtually no variation in response, it was removed from the analysis. The correlation matrix produced 253 coefficients and was simplified by extraction of common factors via principal components analysis. The criteria used for extraction of the factors were the Kaiser rule and the scree-test. Four factors were extracted using these criteria (see Table 6 for eigenvalues).
An orthogonal (Varimax) rotation and Stevens’s (1986) standard cut-off point of .40 (accounting for 17% of the variance in each item) were used to facilitate interpretation of the factors. Factor loadings of .40 or greater are presented in descending order of magnitude in Table 6. The conceptualization used in this study proposed a decision-making model in which reasons for enrolling in independent study could be seen either as attractions of distance learning or as responses to barriers to on-campus learning. The factor analysis appears to support this conceptualization as all of the “attractions” items loaded on Factors 1 and 2 (and only Factors 1 and 2), whereas all of the proposed “barriers” items (save one, V21: academic confidence) loaded on Factors 3 and 4 (and only on those factors).
Since Factors 3 and 4 are the most easily interpreted factors from the principal component analysis, they will be discussed first. Factors 3 and 4 closely fit the barriers component of the decision model, representing the categories of situational barriers and institutional barriers respectively. All of the items proposed in the conceptualization of situational barriers are contained in Factor 3 and none loaded on any other factor. Factor 4 corresponds directly and completely with the institutional barriers category (i.e., with high factor loadings, loadings on that factor only, and no other items loading on that factor).
Factor 1 is the most powerful of the four factors. It contains all but one (V28: leisure) of the items relating to goals, all but one (V22: freedom where and when to learn) of the items relating to learning preference, and the single item relating to psychosocial barriers (V21: lack of academic confidence). Considered in the light of the loadings on Factor 1 (and the extent to which items loaded on both Factors 1 and 2), the separation of attractions into the conceptual categories of learning preference and goals is not supported. These findings suggest that Factors 1 and 2 may represent different dimensions of the same factor and that the two factors should, therefore, be examined together.
Factor 2 contains one item (V28: leisure) from the original concep-tualization of goals. All the other items that loaded on this factor were from the conceptual category of learning preference. For the reasons outlined above with respect to Factor 1, Factor 2 is not interpretable in terms of the original conceptualization. Factor 2 contains items related to leisure time, learning on one’s own, freedom where and when to learn, learning at one’s own pace, and the inclusion of reference material (V28, 26, 22, 19, and 18).
The commonalties within and between each of Factors 1 and 2 suggest that learning preferences are difficult to separate from goals. For example, in Factor 1 the pattern of loadings suggests that preferences for a particular type of learning situation (e.g., V15: learning from print) relate to perceptions of the quality and outcomes of the experience (e.g., V27: learning more). Similarly, in Factor 2, the goal of leisure (V28) is included in a factor containing items relating to a learning preference for independence. The items loading on Factor 2 also suggest that a desire for independence in learning may be situationally, as well as psychologically, influenced. Both factors may be interpreted as measuring learning preference, with Factor 1 measuring preferences relating to learning process and outcomes, and Factor 2 measuring the related dimension of independence. This interpretation of attractions, however, can be offered only as a tentative explanation of relationships among the variables since the instrument itself represents only a first attempt to differentiate between barriers and attractions in the decision to enrol in independent study.
The open-ended question on the questionnaire asked students to specify any additional factors that influenced their decision to enrol in independent study. Less than 5% of students responded, the majority of whom reiterated (or expanded upon) the reasons they had circled in the questionnaire, and overall relatively little new information was provided. The following is a summary of the most frequently noted responses:
The findings presented confirm that the demographic composition of the independent study population has changed in the past 11 years. A shift has occurred from adult, part-time learners living at a geographic distance from the University to younger, Winnipeg residents who are enrolled in heavier, often full-time, course loads. Comparison between independent study enrolment data and on-campus enrolment data revealed that the two populations do not simply mirror one another. Although both groups are getting younger, the rate of growth in independent study far outstrips the growth in on-campus enrolments, and course loads are increasing in independent study but are decreasing in on-campus programs. Comparison of University of Manitoba independent study trends with other dual-mode western Canadian universities suggests that other institutions are also experiencing a trend toward increased enrolments, increased participation by younger students, and increased participation by urban, full-time students.
Given that the young, urban, full-time students who today dominate the independent study population were in a minority in 1983, the question arises as to what has changed to make the barriers and attractions cited by these students more salient today than they were ten years ago. The study does not provide an answer to this question, but it does seem likely that economic changes over the past decade are part of the explanation because both students and universities have been significantly affected by such changes. For students, concerns about unemployment have increased substantially and, with a surplus of available workers, the educational qualifications demanded by employers have risen. Meanwhile, tuition fees have increased between 5% and 10% annually over the past decade, and student financial aid has become more difficult to obtain. For students who are married and/or have families, economic pressures frequently mean that both spouses must work, and consequently time becomes even more limited.
As a result, students appear to be caught in a circumstance in which degree completion is increasingly important in terms of future employment, but where they also cannot afford to continue their studies without employment income. Data on the increasing number of students who work part-time have been gathered by the University of Manitoba, Office of Student Affairs (1996). These data, coupled with the increasing proportions of part-time on-campus students documented in the current study, point to economic circumstances as one explanation of the trends observed in independent study.
Changing economic conditions have also affected the circumstances of the university. Funding to Canadian universities has dropped throughout the past decade, with the result that progressive cuts in on-campus services (e.g., library hours and holdings), larger class sizes, fewer course sections, fewer teaching assistants, and so forth, have translated into restricted access and declining quality. As the survey results suggest, this diminishing availability and quality of on-campus courses has contributed to increasing interest in alternatives such as independent study.
Independent study courses and associated student services have been designed and delivered based on the assumption that the University of Manitoba’s distance education student population is largely drawn from a geographically disadvantaged population of part-time adult learners who have limited opportunity to access higher education. Given that this assumption is no longer completely warranted, there are immediate implications with respect to the Distance Education Program, the University, and the field of distance education generally.
The Distance Education Program is an academic unit charged with responsibility for the design and delivery of distance education courses. The findings of the present study have obvious and immediate impli-cations for the way in which this responsibility is discharged, particularly with respect to policies and practices related to instructional design and student support.
The appropriateness of the instructional design model utilized in the development of independent study courses needs to be re-examined. Currently, instructional designers work with faculty content experts to design independent study courses that incorporate adult education theory. Course designs, for example, take into account the full-time employment, life and career transitions, and motivations of adult learners. The suitability of this paradigm for the current population of independent study students needs to be evaluated. We do not know whether or not current independent study students benefit from the application of adult education principles in course design, nor do we know whether the self-directedness and application of higher-order cognitive skills encouraged in independent study courses might be usefully extended to all courses for younger undergraduates.
Serving a younger, urban student population also opens up possibilities for course designs that allow for face-to-face tutorials at flexible times and locations and a more flexible provision of resources (e.g., computer, print or audiovisual resources could be made available at local libraries). Similarly, the assumption that the independent study students were remote from each other as well as from the campus led to designs that supported independent learning but that also overlooked situations in which opportunities for academic dishonesty could arise.
It is also important, however, not to overlook the needs of students who still do live at a geographic distance from the university and/or are adult learners, even though they are now the minority. Care must be taken to prevent situations where the provision of services appropriate to urban students may disadvantage rural students, or where supports for younger, on-campus students remain unavailable to adult students who work full-time. Possible solutions to these problems may include further specialization of independent study courses so that different course sections are available to urban and rural students and the provision of specialized resources targeted to specific users.
It is apparent that costly learner support services have been directed toward a group of independent study students who may not require them. For example, to compensate for the inaccessibility of the campus library, copyright clearances are obtained, and reprints provided (at no charge to the student), for required reading in independent study courses. As well, a Distance Education Library Service has been established to assist distance education students with term paper research. The Service conducts library searches, mails resource materials, and provides extended loan periods at no charge to students. Other examples include provision of toll-free telephone contact with University departments and independent study instructors and the scheduling of weekly blocks of instructor time for the provision of telephone tutoring.
Some of these support services may not be required by current independent study students, while others may actually present barriers to urban students. For example, independent study students living within Winnipeg city limits are not allowed to use the Distance Education Library Service, but no compensating orientational material for on-campus library use is provided in course manuals. Similarly, independent study instructors are not expected to provide additional office hours for face-to-face (as opposed to telephone) tutoring.
The demographic shift in the independent study population indicates that there is an increasing blurring of the distinctions between on-campus and independent study populations. This convergence has not been the result of a planned or coordinated institutional effort and, as a result, a number of issues arise.
The issue here revolves around services provided (or not provided) by tuition fees and who should pay for these. For example, the majority of independent study students are paying a portion of their fees toward services they do not use (such as the library service, courier services, and long-distance telephone contact) yet, as indicated earlier, they do not have other services targeted specifically for their needs. We do not know to what extent delivery costs for independent study courses have been reduced by the influx of urban students or whether or not such savings should be directed toward (as yet undetermined) services for urban students or toward reduced tuition fees for urban students. The tuition fee situation is further complicated by the fact that students in independent study courses at the University of Manitoba do not pay certain student or faculty fees that are part of on-campus course tuition (and which are forwarded to the student union and faculties). The historic reason for this exemption was that remote learners could not access the services provided by these units and, therefore, should not have to pay for them. Urban students, however, are in a position to take advantage of such services, but we do not know to what extent they do so and to what extent these units should be compensated.
The issue of income distribution has the potential to be a major stumbling block with respect to the co-operation of other academic units with Distance Education. The current budget arrangements at the University of Manitoba direct all independent study tuition income to the self-supporting Distance Education Program. Given the increasing number of urban students, however, other faculties and units may begin to view the tuition paid by urban independent study students as “lost income” which, if directed toward on-campus teaching appointments, would improve the accessibility and quality of on-campus programs. If faculty members perceive that co-operation with the Distance Education Program in the delivery of independent study courses represents a net cost to their on-campus units, an unproductive situation of internal conflict could result.
Continuing budget cuts to on-campus programs will exacerbate the income distribution issue in that the availability and quality of on-campus courses will continue to decline, and demand for independent study courses will continue to increase (with resulting increases in revenue and program expansion). Consequently, a different income distribution formula will likely be necessary to ensure the continued cooperation of on-campus units with the Distance Education Program.
The convergence of on-campus and independent study populations has occurred without any institutional planning and has, in fact, not been previously identified. To use Jevons’s (1990) term, a kind of “black market” has developed with respect to the use of independent study by urban students and, although there is no institutional prohibition against such use, there has been no planned effort to serve this population or to evaluate its needs. Several difficulties arising out of this state of affairs have been noted above. The results of the current study, however, also identify a number of potential benefits in the use of distance education to augment or replace on-campus instruction, particularly in light of the reasons students have provided to explain why they chose independent study courses.
The pedagogical success and cost effectiveness of independent study offer ways to meet the needs of a working student population as well as ways to further develop and better utilize the institution’s teaching resources. If the number of on-campus students who must work while completing university study continues to grow, it would be ill-advised on the part of the University to make investments in expensive new technologies (such as interactive video classrooms) without first giving careful attention to the flexibility in time, place, and pace of study that students in this survey have indicated they require.
In a period of shrinking resources, there may be considerable benefits to be gained by translating course content formerly delivered by face-to-face lecture methods into formats such as independent study. For example, increasing use of independent study offers the potential of different uses of faculty teaching time (e.g., for student tutorials, course development, and delivery), opportunities for joint research and funding, and the sharing of technology. The teaching experience of faculty members with younger students and the experience of distance education staff in instructional design, course delivery methods, and the use of technology (e.g., the World Wide Web) offer excellent opportunities for reciprocal benefits in staff development and enriched blends of course delivery methods.
The most important contributions made by this study to the knowledge base in distance education are that (a) age and geography may no longer define the distance education student and (b) the demands of work may no longer define only the adult student. The widely held assumption, therefore, that distance learners are part-time adult students bears further examination.
As previously noted, the organizational culture of distance education is adult education and, to the extent that distance learners are adults, this is appropriate. If, however, adult students represent an area of diminishing demand relative to younger learners (as the results of this study suggest), the literature upon which current practice is based is inadequate. First, since there have been few institutional data published with respect to independent study student demographics in Canada, we do not know to what extent (and how) these demographics have changed in the past decade. Second, if practice is to be informed by theory and research, we will need to move beyond the current dependence on the field of adult education for direction to incorporate other frames of reference. Relatively few studies have compared either adult distance learners to younger distance learners or younger distance learners to their on-campus counterparts with respect to motivation or learning preferences. Notable exceptions are Harper and Kember (1986), and Leverenz (1981), and the findings of this research suggest that there are indeed important differences to be investigated between these groups. At present, our knowledge of these differences is too limited to allow confident assessment of how the needs and characteristics of a more heterogeneous independent study population might be best served.
This study has generated a number of possible avenues for further research. For example, the extent and magnitude of demographic shifts at other United States and Canadian universities in terms of age, residence, and course loads of independent study students should be investigated. As well, there is a need to determine what changes in course design and student support services would be most beneficial to a young, urban student population and what differences exist between current independent study students and other on-campus learners. Similarly, further work is required to improve the survey instrument (e.g., creating multiple items to measure reasons) and replicate the results. Finally, there is a need to improve the sophistication of the theoretical conceptualization (e.g., the role of psychosocial barriers for younger learners needs to be further developed, as does the possible interaction of psychological and situational influences on learning preference).
Lori Wallace
166 Continuing Education Complex
University of Manitoba
Winnipeg, MB R3T 2N2
E-mail:wallace@cedcampus.Lan1.umanitoba.ca
Phone: (204) 474-8042
Fax: (202) 275-5465
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1. This article presents a summarization of a Ph.D. dissertation completed by the author (Wallace, 1996). Readers are invited to consult the dissertation for further detail regarding the research.
Lori Wallace is currently Senior Instructional Designer for the Distance Education Program at the University of Manitoba, Winnipeg, Manitoba.
ISSN: 0830-0445