Does Policy Make a Difference? An Exploration into Policies for Distance Education


Dr. Katrina A. Meyer
Assistant Professor of Educational Leadership (Higher Education Program)
University of North Dakota
P.O. Box 7189
Grand Forks, ND 58202
(701) 777-3452
katrina_meyer@und.nodak.edu
 
 

ABSTRACT

The study focuses on the impact of various policies (e.g., faculty compensation, workload, intellectual property, geographic service areas) on distance education enrollment growth. Five cases were developed based on data submitted in response to a survey sent to institutions that are members of the Western Cooperative for Educational Telecommunications. The cases provide greater appreciation for the complex role played by funding, the marketplace, and policies. The discussion presents a framework for understanding why policies may, or may not, influence faculty behavior as well as alternatives institutions may wish to consider when contemplating changing these policies.

INTRODUCTION

Distance Education and Policy

This research project explores the role played by policy in distance education. Is there evidence that different policies impact the growth of distance education, or put more simply, does policy make a difference in the distance education effort?

By all evidence, the growth in distance education courses and enrollments has been phenomenal. For instance, the National Center for Education Statistics (1999) found that from Fall 1995 to academic year 1997-98, the number of courses and degree or certificate programs doubled, from 25,730 to 52,270 courses and from 860 to 1,520 programs. Student enrollments also doubled in the same timeframe, from 753,640 to 1.6 million enrollments. However, teasing out the role policy may play in this growth is very difficult, since it is clear there are strong market forces at work in this phenomenon. For example, students are encouraged for a number of economic reasons to pursue additional education through distance technologies and institutions are influenced to provide distance education in order to serve the students in their perceived market and to reap the increased state funding that results from serving greater numbers of FTE students.

To be honest, the motivation behind much policy-making is to avoid lawsuits resulting from not having policy or to lay the groundwork for a successful defense based on having, and following, an adopted policy. And yet it is very common to hear from a number of policy bodies Ė from legislatures to state boards of higher education Ė that policy on a particular matter is needed. The belief seems to be that policy will help clarify the situation, provide a guide for future behavior, or change the behavior of individuals in a manner deemed more appropriate or beneficial.

Policy and Faculty Behavior

Certainly, the evidence is very mixed that policy affects human behavior. Koljatic and Kuh (2001), in a study of three practices deemed "good" for undergraduate education, found that despite several much-publicized policy reports on the importance of and ways to improve the education of undergraduates, the three practices did not markedly increase in frequency. What is more typical in studies of faculty behavior is Dooley and Murphrey (2001), who reviewed the attitudes of administrators and faculty toward distance education and, having found them to be similar, still concluded that revised policies on rewards for faculty were needed.

Even though the literature on policies affecting behavior is limited, there are an ample number of studies on current practices for faculty compensation and workload in distance education. Johnson and DeSpain (2001) surveyed deans of colleges of education and found that 42% provided monetary or other consideration (e.g., release time) for faculty teaching distance education courses (deans also indicated that only 40% had a formal intellectual property policy on ownership of distance education courses). The National Education Association (2000) survey of members found 63% of respondents did not receive additional compensation and 84% received no reduction in courseload. Edwards and Minich (1998) found that 44% of faculty surveyed teaching an interactive video course taught the course "in load" (without additional compensation) and 51 of 64 respondents felt there was no recognition for their distance education efforts. As for policies on intellectual property, or ownership of distance education courses, 45% indicated the institution owned the rights, 11% indicated the faculty had the rights, and 24% indicated those rights were shared (20% indicated "other," which was not explained). What is interesting in this last finding is the frequency of rights being shared between faculty and institution, a position supported by Bates (2000), who also supports teaching distance education "in load," which recognizes that distance education ought to replace something else in the facultyís workload rather than being added to existing responsibilities.

What is perhaps most intriguing about policy and faculty behavior is how counterintuitive it sometimes appears. In studies of faculty involvement with distance education, Wolcott (1997) found that many institutions did not reward faculty for their online teaching, nor were promotion and tenure decisions influenced positively by a faculty personís developing web-based courses. And yet distance education continues to grow, largely through the efforts of faculty. In a subsequent study, Wolcott (2001) investigated faculty beliefs on compensation and workload issues and uncovered three factors: return on and equity of investment, intrinsic motives, and commitment. In other words, faculty appear to be motivated by intrinsic factors to the greatest extent, the commitment of the department or college to a lesser extent, and least of all by recognition or credit in performance evaluations. This latter finding may be due to the continuing lack of recognition for these activities at many institutions.

In a study of faculty compensation, Schifter (2001) found that institutions were more likely to pay faculty for delivering a course than developing one, although considerable variability in policies were found. Hezelís (2001) survey of 30 institutions found that only 12 had workload and/or compensation policies; seven additional institutions were in the process of discussing policy in these areas. Most frequently, institutions apply existing policies to distance education and do not pay instructors for updating courses but support faculty training by paying conference fees or granting release time to do so. These studies indicate that the world of policy regarding faculty compensation and workload is in considerable flux, although most institutions seem to have decided to handle these issues no differently than other efforts on campus.

In a factor analysis of motivators and inhibitors for teaching online, Schifter (2000, 2002) surveyed faculty and administrators and found four scales (in order of loading): intrinsic motives (e.g., challenge, improve teaching), personal needs (e.g., release time, monetary reward), inhibitors (e.g., lack of release time, lack of support), and extrinsic motives (e.g., requirement of department, support of administrators). For faculty, responses were also split between those who had participated in distance education and those who had not; those who had taught online were more likely to name intrinsic motives while those who had not named more extrinsic motives. Administrators were more likely to name personal needs and extrinsic motivators as influencing whether faculty participate in distance learning. Fredericksen, Pickett, Shea, Pelz, and Swan (2000) had similar results, finding that faculty motivated to try online teaching were interested in the Internet or online teaching and rated the experience more satisfying than faculty whose motivation was a fear of being left behind.

Betts (1998) also looked at the motivation for involvement with distance education and found that faculty were (again) motivated by intrinsic factors (e.g., intellectual challenge), inhibited by lack of release time and technical support. Extrinsic factors (e.g., credit toward promotion, merit pay) did not affect their involvement. Deans thought the top motivating factors for faculty were money, credit toward tenure, and release time. In another study of incentives, Rockwell, Schauer, Fritz, and Marx (1999) also found that faculty were motivated by such incentives as providing innovative instruction and using new teaching techniques; monetary awards were neither an incentive nor an obstacle. The biggest obstacles were time and training. These studies present a consistent picture of the intrinsic motivators that push faculty into getting involved in online learning, and that administrators overestimate the importance of extrinsic motivations. On the other hand, these studies also seem to imply that to involve the faculty who are not motivated by the same factors, it may well take money, time, and rewards.

While the emphasis on intrinsic rewards is interesting, what is more interesting is how impervious faculty have been to negative rewards (or the lack of extrinsic rewards). This is an interesting quandary, where policy discourages a behavior that some faculty pursue anyway while other faculty avoid the activity due to the lack of extrinsic rewards. Although there are probably multiple answers to this issue, reward and tenure policies aligned to support online learning may encourage some of the more reluctant faculty to pursue online teaching. On the other hand, a favorable policy may not be sufficient to change faculty behavior; it is not necessary, but it does enable faculty involvement for those so motivated.

Clearly, one should recognize that faculty are not only very different in their personal characteristics, but they are differently motivated in different situations. They are imbedded in multi-layered environments, influenced to a greater or lesser extent by their personal views and values, departmental and college goals, university ambitions, system or state values, and even regional or national trends. So it is not a simple notion to ascribe faculty motivations to one thing or another, let alone to the existence of a specific policy adopted by one layer of this complex environment.

And yet it is an intriguing task to ask the question about the impact of policy, and to attempt to tease out its role in what is happening to higher education. It is not likely that a clear, definite answer will result, but perhaps some interesting relationships will be uncovered and will be worth investigating further.

METHODOLOGY

What follows is an example of policy analysis, as described by Gill and Saunders (1992). Such analysis partakes, at different times, of rational and intuitive methods, drawing upon both traditional data collection as well as an understanding of the interconnectedness of complex systems. Crucial to this process is explicating the variables and relationships proposed to exist in the system as well as the human factors that affect decisions and actions within the system. Analysis is "strongly grounded in the analystís judgment and intuition of the problem, for solution of nonquantifiable problems demands a role for subjective human judgment" (p. 7). That should not mean that the judgments can not be explained, rationalized, and supported and made understandable so that others can judge for themselves the quality of the analysis. Policy analysis is, by its very nature, a messy process, but it is not chaotic.

During Fall 2001, a survey was sent as an attachment to an email to the membership of the Western Cooperative for Educational Telecommunications (WCET). The membership includes over 150 institutions that pay dues to participate in WCET and are thus a group that is largely aligned with the pro-distance education values of the organization. Seven institutions submitted data to the investigator, and only five of these were deemed usable for the analysis (two institutions had only begun delivering distance education so had a short track record to evaluate in terms of the impact of various policies).

The outcome measure of interest was distance education enrollments, and two types of policies were investigated: faculty-related policies and institutional/state policies. The institutional survey included questions on the number of distance education enrollments (by headcount or FTE) per academic year and the number of fully distance courses offered by academic year. The three policy areas of interest to faculty were: 1) faculty compensation (whether faculty were paid for course development), 2) faculty workload (whether faculty taught distance education courses in load or as overload), and 3) intellectual property (whether the policy allocated ownership of distance education courses to the institution, the faculty, or both). In addition, institutions indicated whether specific funding for distance education was available from the state, whether a state plan for distance education was in place, whether distance education appeared in the institutionís mission statement, and whether geographic service areas delineating where institutions could offer distance education were in place. The additional data on funding, strategic plans for distance education, mission statements, and service areas were specifically asked to determine whether these policies would influence distance education growth as much or more than the policies that more directly impact faculty.

Based on the input of the five institutions that provided information, the investigator developed five institutional profiles, labeled case A through E (Table 1). The seven policy questions were:

The five institutions are located in the west, the midwest, and the south. They include one community college, two regional four-year institutions, and two research institutions, and thus institutional enrollments are varied, but range from over 2,000 to 20,500 total headcount students in the most recent year. Distance education headcount enrollments ranged from over 1,000 to over 7,000 students in the most recent year. Because not all institutions are experiencing the same conditions (be they economic state-level politics), it is difficult to compare experiences or overly generalize from these cases, but only to comment on the unique experiences of the five institutions.

FINDINGS

This section will review the five cases based on institutional data and discuss various policy conditions that may inform our understanding of each case.

Case A received state funding in its early years of offering distance education courses and programs, but its largest enrollment increases were in later years, when there was no state funding. Faculty policies (compensation, workload, intellectual property) were supportive of faculty, including compensation for developing courses, distance education taught in or out of load as the faculty person chose, and an intellectual property policy that shared with faculty the rights to and benefits from of a distance education course. In terms of state policies, service areas had been eliminated, and a state plan for distance education was in place. Distance education was not specifically mentioned in the institutionís mission statement.

Case B had not received state funding for its distance education program in its first year, but in each year thereafter. Growth in enrollments was higher in the first and last years. Faculty policies were supportive of faculty, including compensation for developing and delivering online courses and distance education courses taught in load. Despite its long history with distance education, the institution had just begun to develop an intellectual property policy for online courses. State policies were also supportive, including the elimination of service areas, a state plan for distance education, but no mention of distance education in the institutionís mission statement.

Case C had never received directed state funding for its distance education effort, although it also saw high enrollment growth tied to high growth in the number of new courses added to its offerings. Faculty policies were supportive of faculty, including compensation for developing and delivering online courses, distance education courses taught in load, and an intellectual property policy that shared with faculty the rights to and benefits from of a distance education course. Other policies were not so supportive, including the existence of service areas, no state plan for distance education, and no mention of distance education in the institutionís mission statement.

Case D had received state funding every year of its distance education program, but had not added new courses in year 3 and had increased its new courses by 80% in year 4. Largest increases in enrollment were in the first and fourth years of distance education offerings. Faculty policies were supportive of faculty, including compensation for developing online courses, distance education courses taught in load, and an intellectual property policy that shared with faculty the rights to and benefits from of a distance education course. State policies were also supportive, including the elimination of service areas, a distance education plan, and a specific mention of distance education in the institutionís mission statement.

Case E had received state funding in only its last year of operation. Faculty policies were supportive of faculty, including compensation for developing online courses, distance education courses taught in load, and an intellectual property policy that gave faculty the right to own and benefit from their distance education courses. State policies were mixed; service areas had been eliminated but no state plan for distance education had been developed. Distance education was not mentioned in the institutionís mission statement.
 

Table 1. Profile of 5 Institutions
 
5 Institutions CASE A CASE B CASE C CASE D CASE E
Growth Rates(a): 

Year 1-2(g) 

Year 2-3 

Year 3-4 

Year 4-5 

Year 5-6 

Year 6-7 

11.06% (b) 

7.98% (b) 

11.49% (b) 

29.72% 

24.22% 

41.69% 

37.00% (b) 

32.04% (b) 

18.87% (b) 

23.10% (b) 

43.50% (b) 

3.75% (c) 

96.38% (f) 

118.78% (f) 

61.56% (e) 

73.44% (d) 

22.91% 

115.10% (b) 

24.8% (b) 

8.22% (b,c) 

107.20%(b,f) 

65.88% 

17.82% (d) 

38.87% 

25.49% (b,e) 

Faculty Compensation Yes Yes Yes Yes Yes
Faculty Workload  Yes Yes Yes Yes Yes
Intellectual Policy Shared Under development Shared Shared Faculty
Service Areas No No Yes No No
State Plan Yes Yes No Yes No
In Mission No No Yes Yes No
NOTES:
  • All enrollments duplicated headcount.
  • Received state funding for distance education in these years.
  • No new courses offered.
  • Increased number of courses offered 35-59%.
  • Increased number of courses offered 60-75%.
  • Increased number of courses offered 76%-100%.
  • Beginning year is not the same for the five cases.


IMPLICATIONS

From the Cases

There are perhaps four conclusions one can draw from the diverse experiences of these five institutions, as described in the case profiles in Table 1. First, it is logical that funding is certainly helps to build a distance education program, state funding appears to have no consistent, marked effect on enrollment growth (see Cases A, D, and E). Without funding, Case A continued to experience 25%-30% annual growth, more than when the effort was funded. And for Cases D and E, growth was healthy prior to receiving funding.

There may be one proviso to this insight. Certainly, having additional resources is important to developing new courses and programs, and there appears to be a relationship between the number of courses and programs offered and the subsequent impact on enrollments (as in Cases C and E where high growth in enrollments seems tied to a growing number of courses). It may be that funding eases the development of the distance education enterprise by putting in place basic people and organizational support services or by funding the development of new courses, but it does not guarantee enrollments nor enrollment growth.

Second, it appears that enrollment growth occurs in sporadic leaps and jumps, but usually follows a consistent upwards trend despite having no state funding (Case C and E) and only modest growth in the number of courses offered (see Cases C and D). What may be happening in all of this growth is the simple influence of the marketplace, where the pent-up demand of students continues to drive enrollment growth despite the number or variety of courses being offered or how an institution is funding its distance education effort.

Third, all five cases have policies supportive of faculty (compensation, workload and intellectual property), which may be the result of these institutionsí longer experience with distance education programs. In any case, it does not appear that one can differentiate among these institutions based on the nature of their faculty policies.

Lastly, it may be that the march of the market is more powerful than our policies, and certainly these five cases seem to imply that our policies are less influential than we might want to think they are. In Case B, despite long-term growth in enrollments, only recently has the institution initiated a review of its intellectual property policy. A reference to distance education in the institutionís mission statement did not seem to distinguish among the institutions, since the cases with such a statement (C and D) had seven and four yearsí of experience, as did the Cases (A, B, and E) who were not included in the mission of the institution. State policies on service areas were largely supportive, and in Case C where service areas still were in place, this did not seem to affect its enrollment growth. And whether a state had a plan for distance education did not seem to impact enrollment growth since Case C and E had no plan and yet had seven and four yearsí of healthy enrollment growth, respectively. (The realization that state policies and plans may be uncorrelated with distance education enrollments is an especially humbling insight for a former state policy-maker.)

That does not mean that policies do not have an influence, only that they appear to have a modest one at best. Why that may be so will be taken up in the next section.

A Characterization of Policy and Faculty

The question is how can we make sense of these situations? And there may be answers in understanding some basic qualities of the policy environment as well as faculty faced with novel or innovative situations such as involvement in distance education.

First, we can characterize the policy environment as existing on a continuum from policy-free to policy-restricted, with several points in between. For this analysis, let us focus on the two extremes. The policy-free environment is characterized by having no policy in place and decisions likely made on a case-by-case basis. The policy-restricted environment would be characterized by having policies for all eventualities and decision-making that is based on those policies. (The case of a situation where policies conflict, neither providing freedom to operate nor a clear set of policies to implement is particularly troublesome and commonplace in the real world.)

Second, we can characterize faculty by using Rogersí (1995) theory of the diffusion of innovation as it places individuals into five categories based on their comfort, and interest, in innovation: Innovators, Early Adopters, Early Majority, Late Majority, and Laggards. Hagner and Schneebeck (2001) modify Rogersí typology somewhat, and group faculty into four "waves:" the "entrepreneurs," the "reward seekers," the "risk aversives," and the "reluctants." Innovators and Early Adopters probably comprise the entrepreneurs, the early and late majorities are found in the risk-averse and reward-seeking category, and the laggards and even some of the late majority would comprise the reluctants. Combining these two approaches draws upon some useful language and concepts in describing faculty behavior.

Figure 1. Framework of Policy Extremes and Categories of Faculty
 

Policy Extremes Entrepreneurs Risk-Aversives & Reward-Seekers Reluctants
Policy-free      
Policy-restricted      
Figure 1 provides a visual framework for discussing the faculty categories as they relate to our two policy extremes. For the entrepreneurs, a policy-free environment is probably ideal, offering them maximum freedom to operate as they will. However, the entrepreneur in the policy-restricted environment may operate in the same manner, ignoring discouraging policy and suffering more difficulties as a result. Whether policy could stop the entrepreneur is an interesting question; for now, let us assume that the strength of motivation for the entrepreneur is stronger than policy.

For this analysis, let us group together the risk-averse and reward-seeking faculty, due to their common characteristic of being affected by external factors, either positive (rewards) or negatives (risks). For these faculty, the condition of having no policy might be especially troublesome, as it provides them with few indications of where risks are located and what activities might produce a reward. Living in a policy-restricted environment may be more comfortable for these individuals, offering them clear clues as to what to avoid and what to pursue. And given the strength of their need to avoid risk and gain rewards, one would expect them to respond differently to different policies. For example, to these individuals, a positive policy Ė one setting policy on rewards for teaching online courses Ė would encourage them to try out this new activity (other things being equal, such as demands on time, etc.). On the other hand, a lack of policy (or a policy that did not reward this behavior) would be a barrier, largely preventing these individuals from pursuing teaching online.

For the reluctants, it is likely that having no policy is frightening or a confirmation that the activity is a dangerous endeavor, which would be reason enough not to pursue it. The policy-restricted environment may feel more reassuring to these individuals, although one suspects that for truly reluctant individuals, there may be no policy good enough to encourage a change in behavior.

This construct explains a number of behaviors already captured in the review of literature and the five cases. First, the faculty who have, so far, taught distance education courses may be heavily drawn from the entrepreneurs, who revel in policy-less environments and ignore policies that might discourage their involvement in distance education. If there is no extra compensation or no adjustment to their workload, they teach online anyway. The lack of explicit rewards or clear intellectual property policy may be troublesome, but it does not stop them doing what they want to do. These may be the majority of faculty types included in the research by Schifter (2000, 2002), Wolcott (1997, 2001), and Betts (1998), faculty who are intrinsically motivated to teach online.

However, for the risk-averse and reward-seeking faculty, the lack of policy on rewards and compensation keep them away from teaching online courses. For these individuals, the creation of positive, supportive policy may be important to encourage them to consider online teaching. If these faculty types are the early majority and late majority of Rogersí terminology, they are the largest number of faculty and therefore, the most predominant type in institutions of higher education. It is probably because of these faculty that we hear the constant urging to revise policy to make distance education more attractive.

An Institutionís Policy Alternatives

Does this mean each institution should initiate a policy initiative immediately? Not without considering four alternatives. However, before considering these alternatives, an institution needs to understand at least three issues. First, it must have a grasp of how its faculty are distributed across the entrepreneurial and other categories and how a policy discussion (or its absence) will be interpreted. Second, it must have a clear vision of what involvement in distance education or online learning will do for them, or not, as the case may be. Third, it must have an understanding of the severity of its other challenges and whether this is an appropriate or necessary time to undertake change.

The first policy alternative is to do nothing. Although often pursued by default, it is a legitimate and honorable policy alternative, if chosen based on understanding the institution and its faculty, its direction and challenges. For example, if distance education is not deemed to be a useful direction for the institution, or the faculty too risk-averse or suspicious of othersí motives to discuss new policy, then an institution may be well-advised to stay its course and/or spend its valuable time and energy meeting its other challenges.

The second alternative is to revise current policies to be more supportive of distance education. If this alternative is chosen, one assumes that the institution believes this is a good time to initiate a policy discussion, that the majority faculty may not undertake this effort without appropriate policy being in place, and that this is a good direction for the institution.

The third alternative, and another popular policy alternative, is to study the issue. This might be an appropriate alternative for institutions where timing may currently not be propitious for change (but may be in the future), where the study process may be designed to help educate more individuals on campus, or that the direction of the institution (and its various challenges) require some thoughtful preparation.

The last alternative may be to deliberately avoid policy development for now, but use incentives available to the institution to encourage involvement in distance education, such as targeted funding. This may be an appropriate response for an institution with ample resources and greater faith in incentives than in having supportive policies in place or one with more faculty who are reward seekers than risk aversives (who may avoid the temporary monetary gain to ensure tenure and promotion).

There is no one right answer to these policy choices, only answers that will be better or more appropriate for one institution at a point in time. These alternatives can be combined consecutively (first you study and then you revise policy) or pursued concurrently (do nothing but also study the issue). However, these policy choices will help, or not, based on the institutionís knowledge of its strengths and weaknesses, its environment and the market in which it must compete for resources, be they students, faculty, funding, or public regard.

In any case, undertaking a change in policy is not for the faint of heart. It is one of the most difficult and time-consuming activities any administrator can pursue and it generates all types of suspicions and responses from faculty and others who may have something to lose or gain by the change, or only think they do. And most likely, the new policy will not solve as many problems as originally thought. It will likely be unknown by some or ignored by others in the institution and this is an important caution should someone believe a new policy will change behavior overnight or even over time. However, if the policy environment surrounding distance education needs changing, it is best to go forward with a thorough understanding of what distance education needs, the complexities of each institution and the needs of its faculty, and a generous sense of humor for the vagaries of human behavior, including your own.


Biographical Note

Dr. Meyer is currently assistant professor of educational leadership at the University of North Dakota specializing in online learning and higher education. For over three years, she was Director of Distance Learning and Technology for the University and Community College System of Nevada. Prior to this, she served 8 years as Associate Director of Academic Affairs for the Higher Education Coordinating Board in the state of Washington and was responsible for technology planning and online learning issues.


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Online Journal of Distance Learning Administration, Volume V, NumberIV, Winter 2002
State University of West Georgia, Distance Education Center
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