Healthy Work Organizations (HWOs) use innovative strategies to improve their performance while simultaneously meeting the needs of their employees. Asynchronous Learning Networks (ALNs) represent an innovative strategy with the potential to help institutions of higher education meet the challenge to reduce instructional costs while enhancing the quality and availability of their instructional offerings. While the benefits of ALNs to the institution are widely touted, the impact of ALNs on faculty is uncertain. This exploratory study examined the relationship between selected ALN characteristics (faculty workload, institutional support, and compensation practices) and the work-related outcomes (global job satisfaction and pay satisfaction) experienced by faculty. Based on an analysis of the survey responses of 145 faculty that teach ALN-based courses, the correlates of global job satisfaction and pay satisfaction were identified. Adequate technical support and policies and practices that promote equity in workload and pay for faculty teaching ALN-based courses were significantly associated with improvements in pay satisfaction and global job satisfaction.
Today’s institutions of higher education increasingly find themselves under pressure to reduce the cost of instructional delivery, enhance quality and service to students, and increase flexibility in meeting the needs of students who have traditionally been denied access because of time or place conflicts. Asynchronous Learning Networks (ALNs) are emerging as the leading high performance work strategy for meeting the competitive challenge in higher education and hold promise for enhancing student learning and instructional productivity. Jaffe (1998: 2) defines ALNs as “...virtual classrooms involving asynchronous interaction and the exchange of information exclusively on-line with no face-to-face interaction or conventional physical classroom arrangements.” Broadly speaking, ALNs may be characterized as a subset of distance education that imposes particularly unique demands on instructors given the exclusively asynchronous nature of interaction involved. ALN-based instruction presents many challenges from learning and applying new and sometimes unfamiliar technologies, to learning to use new modes of asynchronous communication, to establishing new patterns of availability in order to support the asynchronous learner.
While the potential benefits of ALNs are still subject to considerable and sometimes impassioned debate, most existing literature describes the benefits of ALNs accruing to students and institutions of higher education, arguing that ALNs enhance student access and learning outcomes, reduce costs, and provide for academic programs that can adapt quickly to market changes (Graham, 1999; Bourne, 1998; Green & Gilbert, 1995). Less attention has been paid to the impact of ALNs on faculty and the specter has been raised that ALN-based instruction may actually negatively impact faculty (Garson, 1999; Parrott, 1995). Little investigation has been conducted along this line of inquiry and there is, therefore, a need to better understand the impact of ALNs on faculty.
The salience of mutually beneficial outcomes for organizations and their employees is central to the Healthy Work Organizations (HWOs) concept. A Healthy Work Organization is defined as one “which maximizes the integration of worker goals for well-being and company objectives for profitability and productivity” (Sauter, Lim & Murphy, 1996: 250). The extant ALN literature has focused almost exclusively on the benefits to educational institutions. This study will draw on the HWOs concept and expand the literature by examining the impact of ALNs on the work-related outcomes experienced by faculty.
Little is known about the impact of ALNs on faculty. In the absence of such information, educational institutions must still formulate policies and practices relating to ALN-based instruction, some of which may prove significantly deleterious to their faculty. Therefore, the purpose of this study is to examine the impact of ALN characteristics (faculty workload, institutional support, and faculty compensation practices) on work-related faculty outcomes (global job satisfaction and pay satisfaction). An understanding of the impact of ALN characteristics on faculty has practical significance by providing a foundation for developing informed policies and practices that simultaneously benefit both the institution and its faculty.
Job satisfaction is one of the most intensely examined phenomenon in organizational research on employee work outcomes. An employee’s work outcomes (i.e., positive or negative emotional reactions to a job) are strongly influenced by specific characteristics of the job (Griffeth & Hom, 1995). For example, increasing a job’s complexity has been shown to increase job satisfaction (Fried, 1991). In instances where a change in a job’s characteristics produces a negative employee work outcome (e.g., job dissatisfaction), the frequency of employee behavioral problems, such as the withdrawal behaviors of turnover and absenteeism, has been empirically shown to increase (Mobley, 1977; Price, 1977).
Job satisfaction has been operationalized as either the satisfaction with the job in its entirety (i.e., global job satisfaction) or as some combination of satisfaction with discreet aspects of the job (i.e., facet satisfaction) (Tett & Meyer, 1992). It should be noted that the measurement of facet satisfaction involves assessing satisfaction with work-related factors such as supervision, coworkers, working conditions, pay, and opportunities for advancement (e.g., see the Job Descriptive Index, Smith et al., 1969).
Faculty who experience a change in the characteristics of their job are likely to also experience changes in facet and global job satisfaction. Changes in the nature of faculty work wrought by utilization of ALN instructional technologies should, therefore, impact facet and global job satisfaction. Of the elements of facet satisfaction, the authors contend that pay satisfaction is more susceptible to influence than the other factors comprising facet satisfaction in the specific case of faculty. Higher education faculty typically work under little supervision, enjoy collegial relationships with coworkers, experience pleasant working conditions, and have limited opportunities for advancement. Thus, pay satisfaction logically appears the most likely element of facet satisfaction to be effected by changes in job characteristics resulting from ALN-based instruction.
Much of the distance learning literature focuses on issues related to faculty workload, faculty compensation practices, and institutional arrangements for supporting faculty who utilize a variety of distance learning technologies, including ALNs. Consequently, this study includes ALN characteristics related to faculty workload, institutional support, and compensation practices.
A 1997 report by the Government Relations Committee of the American Association of University Professors (AAUP), subsequently published in Academe (1999), focused on three specific distance learning areas (faculty compensation, intellectual property rights, and academic freedom) and the concomitant issues facing institutions of higher education within each. In the area of faculty workload, the AAUP committee’s report acknowledged that faculty engaged in distance learning via the Web have more demands placed on their time in comparison to traditional instruction. The additional time demands result from requisite technological and software training, greater course preparation time, coordination with technical and support staff, and the need to resolve problems unique to distance learning (e.g., student assessment issues). To offset these added time requirements, the report strongly recommended that faculty be awarded credit toward course load.
In contrast to awarding course load credit, the practice of increasing faculty compensation is frequently discussed in the literature. Compensation arrangements include offering extra compensation for developing or learning to develop distance education courses and paying faculty based on student enrollment (e.g., paying part-time instructors at the rate of $125 per student) (Jacobson, 1994; Craig, 1998). At many colleges and universities, academic departments have discretion in fashioning such compensation policies (Harris & DiPaolo, 1999). Flexible policies allow faculty a choice between incentives (i.e., additional compensation versus a reduction in course load).
The above provides examples of literature examining the issues of faculty workload, institutional support, and compensation practices in a distance education/ALN context. However, the extant literature tends to ignore the explicit impact of these issues on faculty, particularly on the work-related outcomes experienced by faculty. Moreover, the descriptive nature of the literature provides a weak foundation for prescriptive decision-making. Therefore, empirically-based research that examines the relationship between ALN characteristics and work-related outcomes is needed.
The three categories of variables under study, with their constituent dimensions and related variables, are summarized in Table 1. The first category, ALN characteristics, consists of: (1) the impact of ALN-based teaching on faculty workloads, (2) the adequacy of institutional support for ALN-based teaching, and (3) institutional practices for compensating ALN-based teaching. The second category, work-related outcomes, consists of the constructs of: (1) the change in global job satisfaction attributed to ALN-based teaching, and (2) the change in pay satisfaction attributed to ALN-based teaching. The third and final category, demographics, consists of items relating to: (1) the respondent’s relevant experience, (2) respondent personal characteristics, and (3) the type of educational institution at which the respondent is employed.
Note that each of the constructs in the second category was operationalized not with respect to the nominal level of global job satisfaction or pay satisfaction experienced by the respondent, but with respect to the perceived change in these constructs owing to ALN-based teaching. The authors assert that this frame of reference is more valid, as there are numerous intervening variables that may impact nominal job satisfaction and pay satisfaction above and beyond the impact that ALN-based teaching may have. Thus, the focus should be on the way in which these constructs have changed as a result of ALN-based instruction.
The following two research propositions, and associated hypotheses, were formulated based on the review of the relevant literature and the rationale offered below.
P1: Increases in global job satisfaction will be positively associated with perceptions that: (a) ALN-based teaching reduces faculty workloads (H1-H3), (b) institutional support for teaching ALN-based courses is adequate (H4-H6), and (c) institutional practices for compensating ALN-based teaching are favorable to faculty (H7-H8).
H1: Increases in global job satisfaction will be positively associated with perceptions that ALN-based courses require less time to deliver than traditional courses.
H2: Increases in global job satisfaction will be positively associated with perceptions that teaching ALN-based courses reduces total workload.
H3: Increases in global job satisfaction will be positively associated with ALN-based courses being counted as part of the regular teaching load.
H4: Increases in global job satisfaction will be positively associated with perceptions that training for teaching ALN-based courses is adequate.
H5: Increases in global job satisfaction will be positively associated with perceptions that technical support for teaching ALN-based courses is adequate.
H6: Increases in global job satisfaction will be positively associated with perceptions that release time for teaching ALN-based courses is adequate.
H7: Increases in global job satisfaction will be positively associated with perceptions that ALN-based courses are compensated favorably in comparison to traditional courses.
H8: Increases in global job satisfaction will be positively associated with ALN-based courses being compensated on a per student basis.
The rationale underpinning the first three hypotheses is that global job satisfaction should be enhanced to the degree that faculty perceive ALN-based teaching as instrumental in reducing their workload by allowing them to work “smarter” rather than harder. Increased efficiencies arising from the use of ALN technologies should facilitate such a change.
With respect to hypotheses four through six, perceptions concerning the adequacy of institutional support for ALN-based teaching should impact global job satisfaction. The authors conjecture that satisfaction with support will enhance overall job satisfaction. The same line of reasoning underpins the last two hypotheses in that the perceived favorability, for faculty, of practices for compensating ALN-based teaching should enhance global job satisfaction.
P2: Increases in pay satisfaction will be positively associated with perceptions that: (a) ALN-based teaching reduces faculty workloads (H9-H11), and (b) institutional practices for compensating ALN-based teaching are favorable to faculty (H12-H13).
H9: Increases in pay satisfaction will be positively associated with perceptions that ALN-based courses require less time to deliver than traditional courses.
H10: Increases in pay satisfaction will be positively associated with perceptions that teaching ALN-based courses reduces total workload.
H11: Increases in pay satisfaction will be positively associated with ALN-based courses being counted as part of the regular teaching load.
H12: Increases in pay satisfaction will be positively associated with perceptions that ALN-based courses are compensated favorably in comparison to traditional courses.
H13: Increases in pay satisfaction will be positively associated with ALN-based courses being compensated on a per student basis.
A commonly accepted notion, in the literature, is that pay satisfaction is determined by not only the level of pay, but by perceptions concerning the level of expenditure of effort as well. Thus, the logic underlying the ninth through eleventh hypotheses is that, ceterus paribus, the perception that ALN-based teaching reduces workload (i.e., the gross expenditure of effort), should positively impact pay satisfaction. Relative to the final two hypotheses, perceptions of favorability, for faculty, of ALN-based compensation practices should increase pay satisfaction.
The sample used in this study consisted of 354 faculty believed to be involved in ALN-based instruction. The sample was collected on a convenience basis by gleaning respondent e-mail addresses from course descriptions found on the Internet. Of the total, 203 e-mail addresses were taken from course listings on the Web site of the Asynchronous Learning Network (www.aln.org). A search engine was utilized to generate the links to the remaining 151 course descriptions and e-mail addresses.
An original twenty-four item survey instrument was designed for purposes of data collection. ALN characteristics and demographics were operationalized with a mixture of five-point Likert scales and nominally scaled items. Each of the two constructs of global job satisfaction and pay satisfaction was operationalized through the use of a multiple item measurement scale, consisting of three five-point Likert scale items. Each item was taken from an existing validated scale, then reworded to reflect the frame of reference (i.e., with respect to the perceived change in the construct) described previously.
To mitigate mono-method bias, one of the three multiple measurement items was reverse scaled and the ordering of the multiple measurement items was randomized throughout the survey. The derived multiple item measurement scales were purified via item-scale correlation and reliability analyses to provide evidence as to their construct validity.
The survey was implemented in the form of an e-mail survey. The e-mail survey began with an operational definition of ALN’s. The participation of the recipient, via an e-mail reply, was requested and a summary of the study findings was promised to participants as an incentive. In the event that the recipient did not teach ALN-based courses, a request was made that the survey be forwarded to a colleague known to teach ALN-based courses.
Respondents were profiled on all demographic variables through the use of frequency distributions (i.e., for nominal items) and descriptive statistics (i.e., for continuous items). Subsequently, ALN characteristics were tested to ascertain whether they differed systematically across the different types of educational institutions studied. The educational institution type variable was utilized (i.e., as a factor) to test for differences in the continuous ALN characteristics via ANOVA. The independence of the nominal ALN characteristics and the educational institution type variable was tested via Chi-square tests of independence.
Finally, the study hypotheses were tested via multiple stepwise regression models, one each for the dependent variables of global job satisfaction and pay satisfaction. The demographic variables served as control variables in these regression models. Collinearity diagnostics were analyzed given the large number of independent variables involved and the resulting desire to protect against the undesirable effects of multicollinearity.
Of the 354 e-mail surveys distributed, thirty-six were returned undeliverable. Of the 318 delivered surveys, 145 usable surveys were returned for a response rate of 45.6 percent. Males comprised 64.5 percent of the sample while females represented 35.5 percent. Faculty at two-year institutions made up 28.7 percent of the sample, 15.5 percent were employed at four-year colleges, and the remaining 55.8 percent taught at universities with graduate programs. Tenure-track faculty made up 62.8 percent of the sample; the remaining 37.2 percent were non-tenure-track.
The respondents had a mean age of 51.4 years, had taught an average of 16.4 years, and had been at their current institution an average of 14.2 years. As a group, the respondents had taught ALN-based courses a minimum of one semester, a maximum of fifteen semesters, and an average of 5.5 semesters.
The nominal ALN characteristics were: (1) compensation for ALN-based teaching on a per-student or fixed basis (PAYBASIS), and (2) ALN-based teaching as part of the regular load or in addition to it (REGLOAD). The independence of these two nominal variables with the type of institution (INSTYPE) was tested via separate Chi-square tests of independence. In the first case, the hypothesis that PAYBASIS and INSTYPE are independent could not be rejected (p=0.28). The basis of pay (i.e., per student versus fixed amount) did not depend on the institution type.
The second test concerning the independence of REGLOAD and INSTYPE was statistically significant (p=0.02). It may be concluded that the practice of making ALN-based courses part of the regular teaching load depends on the type of institution involved. Table 2 summarizes the practices across the different types of institutions.
Post-hoc t-tests, for differences in the proportions shown in Table 2, indicated that the practice at two-year institutions is significantly different from both four-year colleges (p=0.05) and universities with graduate programs (p=0.03), but that there is no significant difference between the practices of four-year colleges and universities with graduate programs (p=0.11). The predominant practice at two-year institutions is to treat ALN-based courses as part of the regular teaching load. There is no dominant practice at four-year colleges or universities with graduate programs because both practices are used with approximately equal frequency.
Next, ANOVA models were constructed using each continuous ALN characteristic as the response variable and INSTYPE as the factor. Equality of variance among the levels of the factor (INSTYPE) is a critical assumption of ANOVA. This assumption was tested and no significant differences were found. This means that the variation in perceptions within each type of institution was equal across the three types of institutions studied; faculty at any one type of institution were neither more nor less consistent in their responses than their peers at other institution types.
Turning to differences in perceptions between institutions, no significant differences in perceptions concerning the adequacy of training (ADTRAIN, p=0.76), technical support (ADTECH, p=0.81), or release time (ADTIME, p=0.65), or in perceptions concerning the relative pay for ALN-based courses (RELPAY, p=0.90) were found among the different types of institutions. The ANOVA models were statistically significant for the relative time required to deliver ALN-based courses (TOTTIME, p=0.00), and for the impact of ALN-based teaching on total workload (TOTLOAD, p=0.01). Table 3 reports the means on these two response variables across institutional types.
Post-hoc multiple comparisons were performed to test for differences between each pair of institutions. Two-year institutions were found to be significantly different from four-year colleges on both TOTTIME (p=0.00) and TOTLOAD (p=0.05). Likewise, two-year institutions were found to be significantly different from universities with graduate programs on both TOTTIME (p=0.00) and TOTLOAD (p=0.01). No significant difference was found between four-year colleges and universities with graduate programs on either TOTTIME (p=0.16) or TOTLOAD (p=0.96).
Again, two-year institutions stand apart. To understand the difference, note that for both scales a value of three implies détente, and lower values reflect the perception that ALN-based courses require more time relative to traditional courses (TOTTIME) and an increased overall workload (TOTLOAD). Thus, at two-year institutions, the perception is that ALN-based courses require much more time relative to traditional courses and greatly increase workload, whereas the perception at four-year colleges and universities with graduate programs is that ALN-based courses require moderately more time to deliver and moderately increase overall workload.
Before analysis could further proceed, it was necessary to purify the multiple item measurement scales. The two sets of three items representing the global job satisfaction and pay satisfaction scales were summed respectively. Item-scale correlations were computed between each of the six items and the two summated scales. Items showed the desired pattern of correlating with their intended scale to a greater degree than the alternative scale, all by a wide margin.
Subsequently, scale reliability coefficients (i.e., coefficient alpha) and item-total correlations were computed. One item on the global job satisfaction scale (i.e., NEGJOB) and one item on the pay satisfaction scale (i.e., PAYSAT) had item-total correlations of less than 0.4. In both cases, the deletion of the suspect item substantively improved scale reliability and the two items were thus deleted. The remaining two items per scale were averaged and the resulting global job satisfaction scale (SATJOB) and pay satisfaction scale (SATPAY) both exhibited good reliability (i.e., alpha=0.86 and alpha=0.72 respectively).
The mean score for the global job satisfaction (SATJOB) scale was computed to be 3.9. Recall that this construct was framed in terms of the change in global job satisfaction arising from ALN-based teaching, that a value of three on the scale represents no change, and that larger values reflect increasing levels of SATJOB. Consequently, on average the respondents perceived a moderate increase in global job satisfaction due to ALN-based teaching. A stepwise multiple regression model was constructed to further explain the variation in SATJOB using all of the ALN characteristics as independent variables and the demographics as control variables.
The final model retained eight independent variables, is highly significant (F=15.2, p=0.00), and explains a sizable fifty-five percent of the variance (r2=0.55) in the change in global job satisfaction. Collinearity diagnostics indicate no particular concerns as each variance inflation factor (VIF) for the retained variables is well below the threshold value of ten. Table 4 summarizes the model output.
Note that years of teaching experience (TEACHEXP) is positively related with increases in global job satisfaction while respondent age (AGE) is negatively related. While a seemingly confusing result, it should be noted that the coefficients for both of these control variables are so small as to render them of no particular practical meaning; their coefficients are roughly one-tenth the size of the other significant independent variables.
As expected, ALN characteristics positively associated with increases in global job satisfaction include ALN-based courses counted as part of the regular load (REGLOAD) and satisfaction with the adequacy of technical support (ADTECH). Contrary to expectations, the perception that ALN-based courses require relatively less time (TOTTIME), satisfaction with the adequacy of training (ADTRAIN), ALN courses compensated on a per-student basis (PAYBASIS), and the perception that ALN-based courses reduce total workload (TOTLOAD) are all negatively associated with increases in global job satisfaction.
The mean score for the pay satisfaction (SATPAY) scale was computed to be 2.4. Given that a value of three on the scale represents no change in pay satisfaction, and that smaller values reflect decreasing levels of SATPAY, on average the respondents perceived a moderate decrease in pay satisfaction due to ALN-based teaching. A stepwise multiple regression model was constructed to further explain the variation in SATPAY using the faculty workload and compensation practices dimensions of the ALN characteristics as independent variables and demographics as control variables.
The final model retained four independent variables, is highly significant (F=43.8, p=0.00), and explains a substantial sixty-one percent of the variance (r2=0.61) in the change in pay satisfaction. Multicollinearity does not appear to be a problem as all VIFs are less than ten. Table 5 summarizes the model output.
The output indicates that the dummy control variable of respondent gender (GENDER) is negatively associated with increases in pay satisfaction. Based on the coefficient and coding of this item, it appears that females reported even larger decreases in pay satisfaction relative to male respondents.
As expected, ALN characteristics positively associated with increases in pay satisfaction include the perception that ALN-based courses are compensated favorably relative to traditional courses (RELPAY), the perception that ALN-based courses reduce total workload (TOTLOAD), and ALN-based courses counted as part of the regular load (REGLOAD). No associations of the significant explanatory variables were contrary to expectations.
The first set of results relates to differences in ALN characteristics among institutions. Two-year institutions more frequently count ALN-based teaching as part of the regular teaching load relative to four-year colleges and universities with graduate programs. Faculty at two-year institutions also perceive that ALN-based courses require more time relative to traditional courses and increase the overall workload to a greater degree than do their peers at four-year colleges and universities with graduate programs. These noted distinctions may indeed be real and valid. There is a possibility, however, that these distinctions were created by differences in the full-time to part-time composition of faculty at two-year institutions relative to the other types of institutions.
A part-time, adjunct faculty member that teaches only one ALN-based course may be predisposed to respond that this course is part of their “regular teaching load;” it is their only teaching load. In the same vein, many adjunct faculty have primary full-time employment outside the academic institution, thus, they may be particularly sensitive to the time demands created by an ALN-based teaching assignment; such an assignment is not, after all, part of their primary employment. Full-time faculty may be less sensitive, seeing the additional time requirement as just another part of their primary employment. A higher proportion of part-time faculty at two-year institutions would consequently bias the results. Future replications of this study should include a part-time/full-time demographic item to control for this possibility.
Support for the hypothesized positive association between increased global job satisfaction and perceptions that ALN-based teaching reduces faculty workload received mixed support. In the case of ALN-based courses being counted as part of the regular load (H3), the hypothesis was confirmed by the data. However, in the case of the first two hypotheses relating to perceptions that ALN-based courses require less time to deliver than traditional courses (H1), and perceptions that teaching ALN-based courses reduces total workload (H2), the results contradicted the hypotheses. To wit, the greater the perception that ALN-based courses require more time to deliver and increase overall workload was positively associated with increased global job satisfaction. A plausible explanation for these results is that the increased challenge and complexity imposed by ALN-based teaching enriches the nature of the work faculty perform, thereby increasing their level of global job satisfaction. Such an explanation is supported by the Job Characteristics Model (Hackman & Oldham, 1980), and this accepted theoretical model has the potential for serving as the foundation for future research in this area.
Support for the hypothesized positive association between increased global job satisfaction and perceptions that institutional support for teaching ALN-based courses is adequate was likewise mixed. Perceptions of the adequacy of technical support for teaching ALN-based courses (H5) was positively associated with increased global job satisfaction, while perceptions concerning the adequacy of release time (H6) was not.
The association between perceptions of the adequacy of training for teaching ALN-based courses (H4) was negatively associated with increases in global job satisfaction, not positively associated as hypothesized. Again, it is plausible that the added responsibility and challenge of self-training would actually enhance global job satisfaction. Such a proposition would also be consistent with the Job Characteristics Model.
Neither of the last two hypotheses concerning a positive association between increases in global job satisfaction and perceptions that institutional practices for compensating ALN-based teaching are favorable to faculty were supported. There was no association between increases in global job satisfaction and perceptions that ALN-based courses are compensated favorably in comparison to traditional courses (H7).
Contrary to the hypothesized positive association, there was a negative association between increases in global job satisfaction and ALN-based courses being compensated on a per student basis (H8). A very likely explanation is that faculty prefer to be protected, via a fixed amount of compensation, against the risk of low compensation resulting from potentially low enrollments in ALN-based courses. A reviewer also suggested that faculty may dislike per student compensation because of conflicts that arise between the desire for additional compensation versus maintaining a manageable number of students.
The hypothesized positive association between increases in pay satisfaction and perceptions that ALN-based teaching reduces faculty workload was confirmed for two of the three hypotheses. Increased pay satisfaction was positively associated with perceptions that teaching ALN-based courses reduces total workload (H10) and with ALN-based courses being counted as part of the regular load (H11). However, perceptions that ALN-based courses require less time to deliver than traditional courses (H9) was not associated with increases in pay satisfaction.
Support for the last two hypotheses concerning a positive association between increases in pay satisfaction and perceptions that institutional practices for compensating ALN-based teaching are favorable to faculty was mixed. Increased pay satisfaction was positively associated with perceptions that ALN-based courses are compensated favorably in comparison to traditional courses (H12), while there was no association between ALN-based courses being compensated on a per student basis and increases in pay satisfaction (H13).
On balance, there is support for the notion that pay satisfaction may be enhanced when faculty perceive that ALN-based teaching reduces the total workload. This perception is likely reinforced when ALN-based courses are counted as part of the regular teaching load. Similarly, the perception that compensation for ALN-based courses compares favorably to traditional courses is associated with increased pay satisfaction.
The results of this study have potential policy implications. First, it should be acknowledged that ALN characteristics indeed appear to be associated with the work-related outcomes experienced by the faculty respondents of this study. Institutions that subscribe to the Healthy Work Organization concept need be concerned with formulating policies and practices that mutually benefit both the institution and its faculty.
Augmenting the recognized benefits of ALNs for educational institutions, this study identified the correlates of improvements in work-related faculty outcomes. Namely, the ALN characteristics associated with improvements in global job satisfaction were: (1) adequate technical support, and (2) the practice of counting ALN-based teaching as part of the regular teaching load. Further, the correlates of enhanced pay satisfaction were: (1) perceptions that ALN-based teaching reduces total workload ostensibly by allowing faculty to work smarter, (2) compensating ALN-based courses favorably in relation to traditional courses, and (3) the practice of counting ALN-based teaching as part of the regular teaching load. Educational institutions would be well advised to develop policies and practices that assure adequate technical support and equitable reward structures that consider both ALN faculty pay and workload in a manner consistent with the study’s results.
Any interpretation of these findings needs to be tempered with an acknowledgment of the limitations of this study. First, this was an exploratory study that utilized a pre-experimental design. The pre-experimental nature of the cross-sectional research design that was used provides inadequate experimental control to support any inferences regarding cause and effect. Moreover, the convenience sample that was used raises external validity concerns regarding the degree to which the findings can be generalized. Replication of the study’s results derived from independent probability samples would help mitigate both of these concerns.
The reader should consider, however, that at the exploratory level of inquiry, pre-experimental designs are the norm and in spite of the above concerns, this study does serve a valid and useful purpose. The study provides the necessary foundation for further more sophisticated inquiry. Oversights have been pointed out, constructs and variables have been operationalized and their associations tested, and a theoretical model that is potentially useful for future inquiry has been identified.
As has been noted, the inclusion of a part-time/full-time demographic variable would reduce the potential for bias in the results concerning differences in ALN characteristics across institution types. A significant enhancement to this line of research would be the use of the Job Characteristics Model. This model provides fertile ground for better understanding the linkages between ALN characteristics, resulting changes in faculty job characteristics, and the impact of those changes on work-related outcomes for faculty engaged in ALN-based teaching.
Table 1-- Definition of Study Variables
|
Category |
Dimensions |
Variables |
|
ALN characteristics |
Faculty workload |
TOTTIME - difference in the total time required to deliver an ALN-based course relative to a traditional course REGLOAD - status of ALN-based course as part of regular teaching load or in addition to regular teaching load TOTLOAD - perceived change, due to ALN-based teaching, in overall workload |
|
Institutional support |
ADTRAIN - satisfaction with adequacy of training for delivering ALN-based courses ADTECH - satisfaction with adequacy of technical support for delivering ALN-based courses ADTIME - satisfaction with adequacy of release time for delivering ALN-based courses |
|
|
Compensation practices |
RELPAY - pay for ALN-based courses relative to traditional courses PAYBASIS - basis of pay for ALN-based courses, either per student or fixed amount |
|
|
Work-related outcomes |
Global job satisfaction
|
OVERSAT - perceived change, due to ALN-based teaching, in overall job satisfaction ENJOYJOB - perceived change, due to ALN-based teaching, in degree to which individual enjoys their work NEGJOB - perceived change, due to ALN-based teaching, in frequency with which individual has negative thoughts about job |
|
Pay satisfaction |
PAYSAT - perceived change, due to ALN-based teaching, in pay satisfaction PAYFAIR - perception that pay for ALN-based courses is fair when compared to pay for traditional courses PAYNEG - perceived change, due to ALN-based teaching, in frequency with which individual has negative thoughts about pay |
|
|
Demographics |
Experience |
TEACHEXP - years of college teaching experience INSTEXP - years of experience at the current institution ALNEXP - semesters of experience teaching ALN-based courses TENURE - tenure status |
|
Personal characteristics |
AGE GENDER |
|
|
Institutional |
INSTYPE - type of educational institution respondent works for |
Table 2 -- Crosstabulation of REGLOAD and INSTYPE
| INSTYPE¯ REGLOAD® |
Part of regular load |
In addition to regular load |
|
Two-year institution |
29 (78%) |
8 (22%) |
|
Four-year college |
12 (60%) |
8 (40%) |
|
University with graduate programs |
37 (51%) |
35 (49%) |
Table 3 -- TOTTIME and TOTLOAD Means by Type of Institution
|
INSTYPE |
TOTTIME Mean |
TOTLOAD Mean |
|
Two-year institution |
1.2 |
1.7 |
|
Four-year college |
2.0 |
2.4 |
|
University with graduate programs |
2.3 |
2.3 |
Table 4 -- SATJOB Regression Model
|
Independent Variable |
Beta Coefficient |
t -statistic |
p-value |
VIF |
|
TEACHEXP |
0.04 |
2.3 |
0.00 |
2.7 |
|
REGLOAD |
0.29 |
1.1 |
0.04 |
1.4 |
|
TOTTIME |
-0.24 |
-1.3 |
0.01 |
2.1 |
|
AGE |
-0.02 |
-1.2 |
0.02 |
2.5 |
|
ADTRAIN |
-0.22 |
-1.9 |
0.00 |
2.0 |
|
PAYBASIS |
-0.30 |
-1.0 |
0.05 |
1.3 |
|
ADTECH |
0.18 |
1.6 |
0.00 |
2.3 |
|
TOTLOAD |
-0.27 |
-1.5 |
0.00 |
2.2 |
Table 5 -- SATPAY Regression Model
|
Independent Variable |
Beta Coefficient |
t -statistic |
p-value |
VIF |
|
RELPAY |
0.44 |
3.2 |
0.00 |
1.3 |
|
TOTLOAD |
0.36 |
3.1 |
0.00 |
1.2 |
|
REGLOAD |
0.45 |
1.7 |
0.00 |
1.4 |
|
GENDER |
-0.42 |
-1.7 |
0.00 |
1.2 |
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