Conceptualization and measurement of perceived risk of online education.

Mohamed, Fatma A. ; Hassan, Ahmad M. ; Spencer, Barbara 等

INTRODUCTION

Online education (OE) is coming of age. Over the past few years, a stream of technological innovations, from video streaming to virtual online classrooms, has allowed educational institutions and their faculty members the opportunity to experiment with new teaching methods and to offer new types of degree programs beyond the traditional classroom setting. As a result, students are able to enhance their knowledge and to earn degrees without leaving their jobs and families, and in some cases, without setting foot on a college campus. Today's OE programs can allow students to attain their educational goals in a manner that is flexible, convenient and cost effective (Furst-Bowe & Dittmann, 2001; Anderson, Banks & Leary, 2002). The question is, how do they perceive this opportunity? That is, do students perceive online programs as comparable to on-campus work, or do they perceive such offerings as higher risk alternatives?

Recent trends appear to suggest that perceptions of OE are becoming more positive. In the five year period from 2002-2007, the number of online students more than doubled (Allen & Seaman, 2008). During the fall 2007 term, nearly 3.9 million students, approximately 20-25% of all students in U.S. colleges, took at least one online course. While many of these students are off-campus students with a wide variety of ages, work experience and family circumstances, about half of all online enrollments are estimated to be traditional students seeking online courses for reasons of convenience (Mayadas, Bourne and Bacsich, 2009). Most of these students are at public institutions; more than two-thirds of all higher education institutions in the United States have implemented some form of online offerings (Allen & Seaman, 2007).

Yet, research has shown that the perceptions of people about risk rarely coincide with the actual risk of certain activities (Kaspar, 1979). Moreover, in the context of OE, there is no comprehensive research that measures the way that people assess multiple aspects of risk in relation to their intention to enroll. That is, they may be attracted to this form of education for its convenience, while at the same time, concerned about its effectiveness, their ability to communicate with other students, or their likelihood of success. Understanding these factors is important in the short run, because they may differentially affect students' intention to enroll in online classes at all or their decision to enroll in one program versus another (Campbell and Goodstein, 2001). In the long run, a better understanding of the risks associated with OE may help faculty and administrators to influence the learning process in a positive way. For instance, if social factors constitute an important dimension of the perceived risk associated with OE, then programs can be designed to enhance interaction throughout the learning process using processes that range from old-fashioned team assignments to technologically driven virtual classrooms. Consequently, this study takes the first steps in developing a scale for measuring multiple dimensions of perceived risk in OE programs.

The study is organized as follows: First, it describes the notion of perceived risk in OE and defines the types of perceived risk in the OE context. Second, the study creates the item pool that matches the potential dimensions of perceived risk in the OE context and ensures construct validity by using focus groups and a panel of experts to judge the face validity of the construct. Third, the study relates the dimensions of perceived risk to a variety of student demographics to see how different students view online education.

THE NOTION OF PERCEIVED RISK IN OE

Mitchell (1998) defines risk as "the variation in the distribution of possible outcomes, their likelihood and their subjective values" (Mitchell, 1998). The decision to enroll in an online class involves risk because doing so could lead to unexpected or uncertain consequences, some of which could be negative. Potential online students may wonder if they can learn as well online as in a traditional classroom, whether they will be able to communicate with the teacher or their peers, whether their grades will suffer, whether they can finish their program in a timely manner and so on. Their perceptions of these issues, whether accurate or not, will affect their intention to enroll.

Risk assessment is highly subjective. Research has shown that perceptions of people about risk do not always coincide with what we know to have been the actual risk of certain activities (Kasper, 1979). Introduced by Bauer (1960), the concept of perceived risk has been defined as the unexpected and uncertain consequences associated with a product or service that are likely to be unpleasant. Perceived risk has become a central concept in the marketing literature because it helps to explain the consumer's intention to purchase (Mitchell et al., 1999). Specifically, higher perceived risk reduces the intention to purchase because consumers wish to avoid negative outcomes (Bettman, 1973). In the context of OE, intention to purchase is equivalent to intention to enroll.

Although Bauer's initial work (1960) viewed perceived risk as a two-dimensional construct (i.e., uncertainty and negative consequences), more recent work views it as a multidimensional construct including financial risk, performance risk, physical risk, psychological risk, and social risk (Jacoby & Kaplan, 1972). Several other potential sources of perceived risk include time risk (Roselius, 1971), source credibility risk (McCorkle, 1990) and privacy risk (Elliot, 1995).

A review of these studies reveals that the importance of various perceived risk dimensions varies widely across different situations. Thus, perceived risk appears to be extremely context-dependent (Stone & Gronhaug, 1993). In online education, students interact with their instructors primarily through the internet and other computer networks as opposed to face to face contact in classrooms or faculty offices (Haigh, 2007). Today's increasing acceptance of online education by students, faculty and administrators was not widely anticipated. Over the years, many research studies have pointed to likely disadvantages or limitations of online learning. Taken together, this body of work seems to suggest that several sources of perceived risk are relevant to this context.

Perceived psychological risk reflects concern about the psychological discomfort and tension that may arise because of enrollment in an OE program. Past research has suggested that some online students feel more isolated (Brown, 1996); frustrated, anxious and confused (Hara & Kling, 2000; Piccoli, Ahmad & Ives, 2001) than traditional students. In addition, OE students can experience reduced feelings of belonging to the class (Salisbury et al., 2002), and miss the discussions and participation associated with a traditional classroom (Egan et al., 1992; Salisbury et al., 2002; Furst-Bowe and Dittman, 2001

Finally, some research suggests that online students may fear that they cannot complete their degree work because they lack discipline, writing skills and self-motivation (Golladay, Prybutok & Huff, 2000). Even today, attrition rates for OE students are 10-20% higher than those among students in face-to-face settings (Angelino, Williams & Natvig, 2007).

Perceived performance risk relates to concerns about whether a program will perform as desired or deliver promised benefits. This type of risk has been reflected in research showing that OE students perceived instructors to be less well prepared, to use less appropriate teaching methodologies, and to give heavier workloads than their on-campus counterparts (Clow, 1999; Furst-Bowe & Dittman, 2001). OE students have also reported less satisfaction than their on-campus counterparts with the level of interaction with instructors (Egan et al., 1992; Salisbury et al., 2002; Furst-Bowe & Dittman, 2001); particularly when they failed to grasp the material (Egan et al., 1992, Clow, 1999).

Finally, OE students have reported that their knowledge of the subject material increased less and that the course was of less value than students taking the class in the traditional format (Anderson, Banks & Leary 2002). Furthermore, OE students often experience some type of technical problem during their courses (Furst-Bowe and Dittman, 2001). Indeed, some of the negative assessments of OE may be due the students' difficulty in differentiating between their perceptions of the professor and their perceptions of the delivery system (Silvernail & Johnson, 1992).

Perceived Time-demand risk involves fears about the amount of time and effort that will be required to complete online courses. For many students, a major benefit of online education is the flexibility and convenience of taking such courses from home; however, for those who are employed full time or have family obligations, concerns about the time demands can still arise. In their study of student perceptions of online learning, Smart and Cappel (2006) found that study participants complained about losing previously saved work, the slowness of screen loads and the length of the assignments. Thirty percent of their subjects said that the online units were too long and took too much time to complete. In addition, some OE students have reported frustrations with time spent on carrying out online administrative services such as obtaining textbooks, library access and advising (Furst-Bowe and Dittman, 2001).

Perceived social risk relates to concerns about what others will think about us. In the OE context, students may fear that an online degree may not be well accepted by friends and family, or particularly by employers.

Perceived source risk reflects concern over the credibility of the university offering OE programs. Research shows that when considering whether to enroll in an OE course, students worry about the location of the institution, the reputation of the institution, and whether the program will accept transfer credits earned at other institutions (Furst-Bowe and Dittman, 2001). They also worry that prospective employers may question the value of an OE school or program in comparison to a traditional one.

The next section describes the procedures used to develop a scale to measure these sources of perceived risk.

OVERVIEW OF SCALE DEVELOPMENT AND QUESTIONNAIRE DESIGN

This study followed the scale development paradigm described by Churchill (1979), DeVellis (1991), and Spector (1992) in generating a perceived risk in OE item pool, purifying the scale, and demonstrating the reliability and validity of the scale. The first step in any scale development is to use the definition to generate a number of items designated to capture the conceptual and logical true variance present within the construct (Churchill, 1979; DeVellis, 1991; Spector, 1992). As stated earlier, risk perception is an individual's subjective assessment of the potentially negative outcomes of a situation. According to Jacoby and Kaplan (1972) and Roselius (1971), perceived risk is a multidimensional construct including an array of factors that may be viewed as uncertain or unpleasant.

After examining the literature on perceived risk, we followed DeVellis's advice by holding two focus groups with students who had taken one or more OE courses. The first group consisted of 12 undergraduate students, 5 of whom had enrolled in an online class before, and 7 of whom had not. The second group consisted of 10 graduate students, all of them who had enrolled in online classes. The focus groups allowed for the assessment and exploration of the key variables that would impact the perceived risk of OE.

The first step in the focus groups was to ask open-ended question about the students' problems or concerns about enrolling in on line classes. These questions related to each of the dimensions of risk mentioned in the literature: financial, performance, psychological, social, physical, time demand, source credibility, and privacy.

In each group, students identified concerns associated with five of these dimensions: performance, psychological, social, time demand, and source credibility. Physical risk was not viewed as a factor since OE courses could be taken at home. Privacy was not viewed as an issue either. It was widely agreed among the students that they didn't have any problem with their privacy, since everything in online classes was password protected, and no one could access their work and grade book except the instructor. Regarding the financial risk, they mentioned that having online classes was a source of savings, not risk; they didn't need to commute, they could stay with their children without need of day care or baby sitters, and they could avoid living in a dorm or in any other place away from home.

Therefore, this study considered performance risk, time-demand risk, social risk, psychological risk, and source risk as the types of risks in the context of online education. A separate multi-item scale was developed to assess each of the five dimensions of perceived risk (the main scale) in addition to a subscale to measure students' intention to enroll in online classes (to be used in testing the predictive validity of the main scale). These items were chosen to cover various aspects of each domain. Items had to focus on a single dimension, and not bridge two or more dimensions, a feature important for construct validity. A total of 62 different items were identified from this first step related to the five dimensions of perceived risk. The other 5 items were identified related to the subscale to measuring students' intention to enroll in online classes.

CONTENT VALIDITY

The item pool was developed in an effort to tap each component of the perceived risk dimensions that were derived from a thorough literature review and the focus groups. As noted earlier, the focus groups allowed for the exploration of the key factors related to the perceived risk of OE. They also helped in performing a thorough evaluation of the item wording and eliminating any redundant, ambiguous, or poorly worded items.

Overall, 56 acceptable scale items were generated for the main scale and 5 items for the subscale. These items were submitted to a panel of expert judges in order to assess the content validity. These judges consisted of one education professor, one management professor, one marketing professor, and one doctoral student in management and information systems. They were asked to rate the appropriateness and representativeness on a scale from one (inappropriate and unrepresentative) to five (appropriate and representative) for each of the items included in the various domains of perceived risk.

The items that received a rating of less than four were deleted and other changes were made as recommended. After the elimination of 14 redundant items or "not representative" items, the experts agreed that the scale items of perceived risk of OE adequately represented the construct and that each of the subscale items were representative of the intention to enroll construct. The questions included the revised scale that consists of 44 items for the main scale and the subscale of 3 items. It is also included demographic information such as gender, age, student classification, race, and work experience. A five-point, Likert-type response format was used.

Sample and data collection

The unit of analysis in this study consists of students who have had at least one class online. Data were gathered from 257 students. This sample size exceeds the conventional requirement that five observations per scale item are needed for conducting factor analysis (Hair et al., 1998; Stevens, 1996). About 75% of the respondents were undergraduate and 25% graduate students. The sample consisted of more females (65%) than males. The mean age was 28 years.

Convenience samples are considered valid under two conditions: if the study is exploratory in nature and if the items on the questionnaire are pertinent to the respondents who answer them (Ferber, 1977). This study satisfies both conditions. Since this is one of the first attempts to develop a scale to measure perceived risk in OE, this study can clearly be considered exploratory. Also, since it was a necessary condition to complete the questionnaire from students to enroll in online class(es), the scale items are relevant to the respondents.

Scale Purification

Having generated data using the pools described earlier, the next task was to determine whether any items needed to be eliminated. Items that correlate negatively with one another (after reversing responses to the negatively worded item) or items that did not correlate strongly with the sum of the remaining items were removed. Table 1 provides the correlation matrix among items in the purified scales.

Then exploratory factor analysis was used on the items of each scale. Principal component analysis with varimax rotation "using SPSS" was undertaken for the five dimensions of perceived risk and the subscale that has been created to measure intention to enroll. The different dimensions of scales were analyzed, and the items that didn't satisfy the following criterion were deleted: (1) dominant loadings greater than .40 and (2) cross-loadings less than .25. The latent root criterion was used as a criterion for accepting factors, which specifies an eignevalue greater than 1 to determine the number of factors to be extracted. In addition, the factor loadings are generally high, and factor loadings ranged from 0.85 to 0.41. Table 2 shows the results of the principle components analysis.

Six factors accounted for 61.4 percent of the total variance. Overall, eight items were retained from the performance risk scale, six from the time-demand risk scale, three from the social risk scale, four from the psychological risk scale, four from the source risk scale, and three from the intention to enrollment scale (See Appendix).

Reliability Assessment

The internal consistency of the six scales exceeded the minimum level of .70 as assessed by coefficient alpha. Coefficient alpha had acceptable levels ranging from 0.83 to 0.80 (Nunnally and Bernstein, 1994). The first factor "Perceived Performance Risk" ([alpha] = 0.82) explained 32.7% of the variance. The second factor "Perceived Time-demand Risk" ([alpha] = 0.80) accounted for 9.8% of the variance. The third factor "Perceived Social Risk" ([alpha] = 0.82) explained 6.7% of the variance. The fourth factor "Perceived Psychological Risk" ([alpha] = 0.80) accounted for 5.5% of the variance. The fifth factor "Perceived Source Risk" (a = 0.70) accounted for 5.2% of the variance. The last factor "Intention to Enroll" (a = 0.83) explained 3.9% of the variance. The reliability of the individual items were assessed using the criterion of item-to-total correlations greater than .50 with squared multiple correlations of more than .30 (DeVellis, 1991; Hair et al., 1998).

Predictive Validity

Since students perceived risk relative to OE, this risk should have an effect on student's intention to enroll in online class(es) in the future. This relationship is anticipated to be negative since a higher perceived risk should result in a lower intention to enroll in an OE program. Zero order correlations and multiple regressions were used to assess this predictive validity.

Zero order correlations revealed that enrollment intention significantly and negatively correlated with all the five dimensions of perceived risk for online classes. Table 3 shows the results of the correlation analysis.

Although the correlation analyses generally supported the predictive validity, multiple regression analysis was performed to further analyze the relationships between the independent and dependent variables. The results of the multiple regression analysis appear in Table 4.

These results indicate that four factors of the scale--performance, time-loss, psychological, and source risks--are strongly predictive of OE enrollment intentions.

Variation in Perceived Risk

In addition to its relationship to OE Enrollment, perceived risk varied according to some demographic variables. Using the general linear model, multivariate method (Table 5), shows different effects. For instance, female students perceived more performance risk than male students. Older students experienced more performance risk, psychological risk and source risk than younger students. Graduate students experienced more performance, psychological and source risk than undergraduate students. Students who were working perceived more time risk and psychological risk than the students who were not working. Students with more years of work experience perceived more psychological and source risk than those with less work experience. Students who worked more hours a week perceived more psychological risk when considering OE classes than did those who worked less. While at the same time, students who had taken more online classes perceived more source risk than those who had taken fewer online classes.

Contributions, Limitations and Opportunities for Future Research

This study reviewed the dimensions of perceived risk and identified five dimensions that are relevant to the OE context. These dimensions are: perceived performance risk, perceived time-demand risk, perceived social risk, perceived psychological risk, and perceived source risk. An item pool was developed and content validity achieved by independent judges, who evaluated the appropriateness and representativeness of the items. After deleting inappropriate and unrepresentative items, 26 items remained. For these items, the researchers tested the reliability using coefficient alpha and demonstrated that the results support the reliability of the scale. Moreover, the researchers tested the predictive validity of the scale achieving results showing four dimensions out of five are highly predictive of the intention to enroll in online courses.

The study shows that even though OE is becoming much more common and well accepted, perceived risk still occurs and is associated with the decision of whether or not to enroll in such courses. While this is a good beginning, the availability of a reliable scale allows us to look more in depth at a variety of interesting and important questions concerning online education. For instance, the current study only looks at the intention to enroll in general. It could be very useful, however, to see how these dimensions vary when participants are considering the choice between different programs. It is easy to surmise that source credibility could vary across programs, but so could expected performance outcomes and other potential sources of risk. Even more important would be to find out whether these different risk assessments affected the intention to enroll differently at unique institutions.

If the administrators of online programs better understood potential students' fears and concerns, they could market certain attributes of their programs in a way that might alleviate such fears. For instance, accredited business schools could promote their AACSB credentials in order to reduce the fear of source credibility. They could feature profiles of prior OE students who are now working in well-known organizations with good jobs.

Faculty could also learn how to enhance the online learning process through the use of this scale. It would be very interesting to study the linkage between perceived risk and reported learning outcomes as moderated by different types of course content. For example, students may perceive more psychological risk when considering quantitative classes such as statistics or economics. In such cases, does the perception of risk actually reduce the possibility of success or satisfaction with the course? Do those who perceive more risk perform less well? Or is there an interaction between the type of risk, the content of the class, and the technology used to teach the class? These are complex issues which have yet to be evaluated.

This study has some limitations that also deserve comment. One limitation of the present study was all data were collected through the same questionnaire during the same period of time with cross-sectional research design, common method variance, variance that is attributed to the measurement method rather than the constructs of interest, may cause systematic measurement error and further bias the estimates of the true relationship among theoretical constructs. (Avolio, Yammarino, & Bass, 1991; Bagozzi & Yi, 1990; Crampton, & Wagner, 1994; Doty & Gulick, 1998; Podsakoff, MacKenzie, Lee, & Podsakoff, 2003; Podsakoff & Organ, 1986; Spector, 1994; Williams). Therefore, longitudinal or experimental research is needed to provide a more rigorous test of the validity of such scales. It is also important to know how the assessment of risk changes as students become more experienced in taking classes online. Enrolling in an online class can be described as purchasing a service. Research in the marketing literature has shown that perceived risk is higher when purchasing services vs. products because you must purchase services first and then evaluate them which results in increased uncertainty (Mitchell & Greatorex, 1993). Since different institutions and even different teachers utilize different approaches to OE, the risk may appear high every time.

A second limitation of the study is its use of one sample for purifying and validating the scale. The assessment of reliability and validity should be examined using a new sample in effort to avoid capitalizing on chance. Third, the study has been conducted at one university, and this affects the generalizability of the results. Therefore, more studies are needed using data from several randomly selected universities. Finally, the effect of the perceived social risk on the intention to enroll in online classes needs further investigation.

APPENDIX

Text of Items

Measuring Perceived Risk in Online education

Perceived Performance Risk

I think the instructor will be able to make himself/herself clearly understood. (RC)

I doubt the instructor will be able to make this type of class work for all of the students.

I am concerned about the accessibility of the instructor through phone or fax.

I don't believe the instructor will be very accessible by e-mail.

I'm worried about getting feedback about my performance from the instructor.

I'm concerned that the technology used in OE won't be reliable.

I believe there will be state-of-the-art technology used in OE courses. (RC)

I don't know who will help me if I have problems with the technology used in this course.

Perceived Time-Demand Risk

I'm not sure I'll have the time needed to successfully complete online courses.

I am concerned about the availability of books, required readings, or other resources in a timely basis.

I feel that the library and research facilities at the remote site will be inadequate. (RC)

I'm afraid that OE will take too much time away from my family.

I don't think an online course would interfere with my regular schedule. (RC)

If I take an online course, I'll have less free time.

Perceived Social Risk

I believe potential employers will be more impressed with a degree earned through OE than with one earned the traditional way. (RC)

In general, people who earn their degrees through online programs are held in higher esteem than are traditional students. (RC)

My family will be prouder of me if earn a degree through an online program than they would if I completed a traditional program. (RC)

Perceived Psychological Risk

I am worried about keeping myself motivated in on-line classes.

I have a feeling that online classes are less important than the on-campus classes.

Just the thought of taking an online class causes me to feel stressed.

I think there will be sufficient classroom interaction in an online class. (RC)

I have trouble paying attention to the class materials when I have an online class.

Perceived Source Risk

It is difficult to determine the credibility of some universities offering OE programs.

It is not hard to ascertain the expertise of some universities offering OE programs. (RC)

It's not difficult to learn the reputation of universities offering OE programs. (RC)

I'm concerned about the credibility of some universities offering OE programs.

I think that universities that offer OE programs are just as good as traditional schools. (RC)

I believe that OE is the "wave of the future". (RC)

Criterion variables (intention to enroll)

If the opportunity arises, I'll enroll in a distance course.

I would never even consider enrolling in a distance-learning program. (RC)

There's a very good chance that I'll take a distance-learning course in the future.

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Fatma A. Mohamed, Morehead State University

Ahmad M. Hassan, Morehead State University

Barbara Spencer, Mississippi State University

Table 1

      V1       V2       V3       V4       V6       V8

V1    1
V2    .38      1
V3    .52      .30      1
V4    .30      .33      .24      1
V6    .26      .29      .33      .43      1
V8    .35      .38      .32      .48      .43      1
V11   .38      .36      .35      .38      .31      .41
V12   .39      .17      .38      .22      .15      .26
V13   .30      .32      .30      .39      .27      .46
V14   .26      .23      .26      .36      .36      .35
V17   .30      .27      .26      .37      .33      .41
V18   .34      .29      .26      .34      .32      .31
V23   .32      .22      .26      .28      .32      .25
V24   .29      .11 *    .26      .20      .17      .14
V25   .14      .14      .18      .20      .25      .20
V27   .09      .04      .15      .003     .12 *    .02
V28   .09      .06      .13 *    .07      .17      .003
V29   .06      .13 *    .07      .05      .17      .03
V31   .25      .29      .25      .32      .17      .25
V32   .29      .33      .30      .39      .31      .34
V33   .28      .22      .32      .35      .30      .24
V37   .29      .30      .35      .40      .33      .30
V39   .18      .07      .14      .17      .01      .15
V40   .20      .12 *    .15      .20      .10      .15
V41   .14      .17      .06      .20      .13 *    .17
V42   .36      .22      .33      .24      .23      .22
V45   .40      .26      .43      .30      .23      .18
V46   .23      .13 *    .30      .24      .32      .13
V47   .38      .13 *    .40      .23      .23      .08

      V11      V12      V13      V14      V17      V18

V1
V2
V3
V4
V6
V8
V11   1
V12   .38      1
V13   .38      .19      1
V14   .38      .20      .48      1
V17   .37      .23      .40      .44      1
V18   .35      .28      .43      .42      .52      1
V23   .35      .20      .31      .45      .44      .36
V24   .27      .25      .23      .42      .28      .32
V25   .18      .06      .29      .39      .32      .30
V27   .10      .12      .02      .04      .08      .03
V28   .12 *    .12 *    .02      .20 *    .01      .004
V29   .08      .10      .010     .04      .02      .009
V31   .33      .19      .36      .42      .30      .32
V32   .41      .23      .41      .36      .34      .33
V33   .32      .23      .37      .45      .42      .41
V37   .41      .21      .42      .37      .39      .32
V39   .13 *    .26      .10      .06      .07      .08
V40   .13 *    .25      .14      .07      .11      .12
V41   .26      .14      .20      .23      .24      .25
V42   .30      .27      .30      .32      .32      .29
V45   .36      .40      .39      .34      .35      .34
V46   .26      .19      .40      .34      .32      .26
V47   .27      .27      .35      .30      .27      .28

      V23      V24      V25      V27      V28      V29

V1
V2
V3
V4
V6
V8
V11
V12
V13
V14
V17
V18
V23   1
V24   .36      1
V25   .49      .38      1
V27   .04      .10      .04      1
V28   .07      .09      .05      .69      1
V29   .18      .04      .002     .52      .57      1
V31   .32      .22      .22      .17      .07      .11 *
V32   .36      .24      .27      .21      .16      .12 *
V33   .56      .32      .44      .05      -.06     .03
V37   .37      .26      .27      .14      .04      .05
V39   .02      .10      .03      .21      .21      .13 *
V40   .16      .20      .10      .13 *    .19      .05
V41   .20      .19      .21      .14      .10      .05
V42   .25      .42      .25      .23      .24      .19
V45   .35      .36      .22      .21      .15      .17
V46   .38      .18      .29      .002     -.11 *   .13 *
V47   .31      .36      .21      .10      -.02     .04

      V31       V32       V33       V37       V39     V40

V1
V2
V3
V4
V6
V8
V11
V12
V13
V14
V17
V18
V23
V24
V25
V27
V28
V29
V31   1
V32   .48       1
V33   .43       .44       1
V37   .59       .50       .51       1
V39   .11       .16       .07       .15       1
V40   .16       .19       .10       .18       .53     1
V41   .30       .21       .20       .25       .21     .29
V42   .27       .38       .25       .29       .28     .34
V45   .38       .38       .46       .45       .11 *   .16
V46   .28       .34       .49       .41       .04     .09
V47   .29       .30       .45       .40       .08     .14

      V41      V42     V45     V46     V47

V1
V2
V3
V4
V6
V8
V11
V12
V13
V14
V17
V18
V23
V24
V25
V27
V28
V29
V31
V32
V33
V37
V39
V40
V41   1
V42   .28      1
V45   .17      .46     1
V46   .20      .25     .58     1
V47   .106 *   .36     .70     .61     1

** Correlation is significant at the 0.01 level (2-tailed).

* Correlation is significant at the 0.05 level (2-tailed).

Table 2
Varimax-rotated Matrix of Perceived Risk Items

Components

Variable   Performance   Time-demand   Social   Psychological   Source

VAR1          .617
VAR2          .609
VAR3          .552
VAR4          .623
VAR6          .577
VAR8          .780
VAR11         .625
VAR13         .506
VAR14                       .660
VAR17                       .501
VAR18                       .424
VAR23                       .553
VAR24                       .619
VAR25                       .757
VAR27                                   .817
VAR28                                   .866
VAR29                                   .819
VAR31                                               .736
VAR32                                               .565
VAR33                                               .501
VAR37                                               .726
VAR39                                                            .812
VAR40                                                            .869
VAR41                                                            .448
VAR42                                                            .413

VAR45
VAR46
VAR47

Variable   Enrolment intention

VAR1
VAR2
VAR3
VAR4
VAR6
VAR8
VAR11
VAR13
VAR14
VAR17
VAR18
VAR23
VAR24
VAR25
VAR27
VAR28
VAR29
VAR31
VAR32
VAR33
VAR37
VAR39
VAR40
VAR41
VAR42

VAR45             .784
VAR46             .671
VAR47             .858

Table 3
Zero order correlations

                        Performance        Time         Social
                           Risk         demand Risk      Risk

Performance Risk             1
Time Demand Risk          .671 **            1
Social Risk               .308 **       .207 **           1
Psychological Risk        .699 **       .683 **         .463 **
Source Risk               .537 **       .459 **         .441 **
Enrollment intention     -.534 **      -.535 **        -.281 **

                       Psychological    Source    Enrollment
                           Risk          Risk     intention

Performance Risk
Time Demand Risk
Social Risk
Psychological Risk           1
Source Risk               .562 **         1
Enrollment intention     -.574 **      -.470 **       1

** Correlation is significant at the 0.01 level (2-tailed).

Table 4 Multiple regression analysis results

Independent variables   Beta coefficients     t     Sig.

Performance Risk              .140          2.225   .027
Time Demand Risk              .197          3.215   .001
Social Risk                   .013          .260    .795
Psychological Risk            .245          3.562   .001
Source Risk                   .161          3.047   .002

Dependent Variable: Enrollment intention

Table 5 Perceived Risk Variation according to some Demographic
Variables

Source                Dependent Variables   Mean Square     F     Sig.

Sex                   Performance Risk           1.887    3.844   0.04
                      Time Demand Risk            1.07    2.49    0.116
                      Social Risk                0.159    0.335   0.563
                      Psychological Risk         0.582    0.76    0.384
                      Source Risk                1.026    2.418   0.121

Age                   Performance Risk           0.916    2.199   0.001
                      Time Demand Risk           0.493    1.171   0.253
                      Social Risk                0.611    1.371   0.099
                      Psychological Risk           1.5    2.411   0.001
                      Source Risk                0.752    2.062   0.001

Graduate And          Performance Risk            2.28    4.661   0.032
undergraduate         Time Demand Risk           0.035    0.08    0.777
                      Social Risk                0.871    1.853   0.175
                      Psychological Risk          5.17    6.957   0.009
                      Source Risk                0.979    2.305   0.013

Employed or not       Performance Risk           0.390    0.774   0.380
                      Time Demand Risk           1.919    4.023   0.046
                      Social Risk                1.161    2.343   0.127
                      Psychological Risk         2.795    3.798   0.050
                      Source Risk                0.390    0.774   0.380

Years                 Performance Risk           0.602    1.265   0.162
How many years they   Time Demand Risk           0.561    1.381   0.09
have been working     Social Risk                0.506    1.088   0.351
                      Psychological Risk         1.162    1.703   0.013
                      Source Risk                4.980    4.153   0.042

Hours                 Performance Risk            0.46    0.91    0.623
How many hours        Time Demand Risk           0.431    0.996   0.484
a week?               Social Risk                0.407    0.837   0.736
                      Psychological Risk             1    1.404   0.045
                      Source Risk                0.377    0.861   0.701

OE Experience         Performance Risk           1.458    2.956   0.087
                      Time Demand Risk            0.25    0.577   0.448
                      Social Risk                0.101    0.213   0.645
                      Psychological Risk         0.088    0.115   0.735
                      Source Risk                1.986    4.731   0.031