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Perception Differences About Participating in Distance Education

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Catherine Schifter,
Associate Professor,
College of Education,
Temple University,
Philadelphia, PA. 
catherine.schifter@temple.edu

Abstract

 

Non-traditional distance education is increasingly common in higher education.  While many distance programs are separated into continuing education or adult education programs, infusion of distance education courses as options for traditional higher education students is beginning to take hold. (U.S. Department of Education, 1999, HERI, 1999)  For this to be successful, faculty of the institution need to be part of the process, specifically in developing and teaching the courses.

 

The pedagogy of the faculty member in a distance education course changes from a teacher-centered approach to being student-centered (Strain, 1987; Beaudoin, 1990; 1998; Berge, 1998).  In addition, "unbundling" of the faculty role is more and more recommended for distance education. (Paulson, 2002), but this is difficult for many faculty who are concerned about who then owns the course or copyright.  Carnevale (2001) notes in a report in the Chronicle of Higher Education a recent AFT report that indicates concern over the practice of "unbundling" the traditional role of the professor by online courses creators.  Unfortunately, research has indicated many faculty are not enthusiastic about participating in distance education (Olcott and Wright, 1995).  Issues that have been noted as barriers to faculty participation include insufficient training, lack of applicability toward promotion and tenure, lack of release time, insufficient instructional and administrative support, minimal monetary compensation, and an expanded teaching load (Clark, 1993; Dillon and Walsh, 1992; Koontz, 1989; Olcott, 1991; 1992; 1993; Wagner and Elms, 1993; and Wolcott, 1993).  Bower (2001) notes that for some faculty who teach distance courses the lack of direct interpersonal contact and feedback from students is a problem, given the fact that most faculty learn to teach face-to-face, or "hand-to-hand." (p. 2)  Do these factors remain?

 

Taylor and White (1987), McKenzie (2000), and Seay, Rudolph and Chamberlain (2001) reported faculty preferred conventional face-to-face courses over distance teaching due to the degree of interpersonal contact available in each mode.  Less interaction with the students led to less interest on the part of faculty to participate.  Clark (1993) showed through a national survey that faculty support for distance courses was tempered by concern for quality of interaction, administrative support, and rewards.  Betts (1998) demonstrated that the strongest motivating factors for faculty who participate in distance education are different from perceptions held by non-participating faculty and administrators of motivating factors for faculty participating.  One question that does not seem to have received attention is whether there are differences in faculty attitudes by gender, age, faculty rank, and tenure status.

 

Faculty (distance education participators and non-participators) and administrators at a research extensive, state-related university were surveyed about (1) faculty use of technology in teaching, (2) motivating and inhibiting factors for participating in distance education, and (3) understanding of policies on distance education.  This paper presents a factor analysis of the 46 motivating and inhibiting factors for distance education participation and an analysis of interaction between responses and level of participation in distance education, gender, age, faculty rank and tenure status.

 

 

Methods

With permission from the author (Betts, 1998), this study used a modified version of a survey developed to identify factors that influence faculty participation in distance education (Betts, 1998).  Minor modifications were made to address the institution for this study.  The survey was distributed in to all full-time faculty and twenty-five senior administrators, including all deans.  After accounting for faculty on leave (paid or unpaid) from the university, the target faculty population totaled 1312.  A total of 263 completed and usable surveys were returned for a response rate of 20%, which could limit the external validity of the results.  A total of eleven administrators returned the survey for a 44% response rate; however, only nine completed the sections on motivating and inhibiting factors.

 

The data was analyzed using the SPSS Statistical Package.  First, the 29 motivating (Table 1) and 17 inhibiting (Table 2) factors were ranked according to mean scores and a factor analysis was used on all 46 factors to see how they grouped.  An analysis of variance (ANOVA) was conducted on mean factor scores to determine significant differences by level of participation, gender, age range, faculty rank and tenure status.  Four independent Chi-square analyses were run to test the null hypothesis that there was no relationship between level of participation and gender, age range, faculty rank or tenure status.

 

Table 1: Motivating Factor List

 

1                 Personal motivation to use technology

2                 Graduate training received

3                 Opportunity for scholarly pursuit

4                 Reduced teaching load

5                 Opportunity to use personal research as a teaching tool

6                 Requirement by department

7                 Support and encouragement from dean or chair

8                 Working conditions (e.g., hours, location)

9                 Job security

10              Monetary support for participation (e.g., stipend, overload)

11              Expectation by university that faculty participate

12              Opportunity to develop new ideas

13              Visibility for jobs at other institutions/organizations

14              Professional prestige and status

15              Grants for materials/expenses

16              Support and encouragement from departmental colleagues

17              Intellectual challenge

18              Overall job satisfaction

19              Technical support provided by the institution

20              Career exploration

21              Credit toward promotion and tenure

22              Release time

23              Distance education training provided by the institution

24              Merit pay

25              Greater course flexibility for students

26              Opportunity to diversify program offerings

27              Ability to reach new audiences that cannot attend classes on campus

28              Opportunity to improve my teaching

29              Support and encouragement from institutional administrators

 

 

Table 2: Inhibiting Factor List

 

1                 Concern about faculty workload

2                 Negative comments made by colleagues about distance education teaching experiences

3                 Lack of distance education training provided by the institution

4                 Lack of support and encouragement from departmental colleagues

5                 Lack of release time

6                 Lack of professional prestige

7                 Lack of technical background

8                 Lack of support and encouragement from dean or chair

9                 Lack of grants for materials/expenses

10              Concern about quality of courses

11              Lack of technical support provided by the institution

12              Lack of merit pay

13              Lack of support and encouragement from institution administrators

14              Lack of monetary support for participation (e.g., stipend, overload)

15              Concern about quality of students

16              Lack of salary increase

17              Lack of credit toward promotion and tenure

 

 

Results

 Table 3 presents the demographic data about the respondents.  While the survey was sent to full-time faculty, two respondents were part-time faculty and one person did not answer this item. Thirty-eight (14.4%) faculty indicated they participated in distance education.  For the purpose of this study, this group is called “participators” and those who did not indicated participating in distance education are called “non-participators.”

 

Table 3: Demographic information

 

A total of eleven administrators returned the self-study survey:  six deans, two vice presidents, one vice provost, one associate dean, and one acting assistant dean.  Of the eleven, nine completed all the sections, including those on motivating and inhibiting factors.

Faculty and administrators were asked to rate from 5 to 1 (5 = strongly agree; 1 = strongly disagree) to what extent they believed 29 factors had motivated, or would motivate, faculty to participate in distance education and 17 factors had inhibited, or would inhibit, faculty from participating in distance education. A factor analysis of all 46 factors (motivating and inhibiting) rendered four scales, showing distinct factor relationship patterns.  In addition, an overall "motivation" scale was calculated for the 29 motivating factors, and an overall "inhibiting" scale was calculated for the 17 inhibiting factors.  These six scales were used in further analysis of the response.

Scale 1 was labeled “Intrinsic motives” and had an Alpha coefficient of .9123.  The following factors grouped into this scale:

·       Intellectual challenge

·       Opportunity to diversify program offerings

·       Opportunity to develop new ideas

·       Overall job satisfaction

·       Opportunity to improve my teaching

·       Greater course flexibility for students

·       Personal motivation to use technology

·       Ability to reach new audiences that cannot attend classes on campus

·       Opportunity for scholarly pursuit

·       Opportunity to use personal research as a teaching tool

 

Scale 2 is labeled "Personal needs" and has an Alpha coefficient of .8956.  The following items grouped into "personal needs":

·       Release time

·       Credit toward promotion and tenure

·       Merit pay

·       Monetary support for participation (e.g., stipend, overload)

·       Visibility for jobs at other institutions/organizations

·       Lack of credit toward tenure and promotion

·       Grants for materials/expenses

·       Reduced teaching load

·       Working conditions (e.g., hours, location)

·       Professional prestige and status

·       Job security

·       Career exploration

·       Graduate training received

 

Scale 3 is labeled "Inhibitors" and has an Alpha coefficient of .8878.  The following items grouped into "inhibitors":

·       Lack of release time

·       Lack of support and encouragement from institution's administrators

·       Lack of merit pay

·       Lack of support and encouragement from departmental colleagues

·       Lack of monetary support for participation (e.g., stipend, overload)

·       Lack of support and encouragement from dean or chair

·       Lack of grants for materials/expenses

·       Lack of technical support provided by the institution

·       Lack of salary increase

·       Lack of distance education training provided by the institution

·       Lack of professional prestige

·       Concern about faculty workload

·       Negative comments made by colleagues about distance education teaching experiences

·       Concern about quality of courses

·       Concern about quality of students

Scale 4 is labeled "Extrinsic motives" and has an Alpha coefficient of .8440.  The following items grouped into "extrinsic motives":

·       Expectation by university that faculty participate

·       Requirement by department

·       Support and encouragement from dean or chair

·       Support and encouragement from departmental colleagues

·       Distance education training provided by the institution

·       Support and encouragement from institution's administrators

·       Technical support provided by the institution

·       Lack of technical background

 

 

The means of each the four scales and each individual factor (motivating and inhibiting) were analyzed using an ANOVA to test significant differences between level of faculty participation in distance education (participate, not participate).  Significant differences were found for nine motivating (M) factors and one inhibiting (I) factor.  The results are found in Table 3.  Overall, distance education participating faculty rated intrinsic motives higher (M1 and M26), while non-participating faculty rated higher personal needs (M4, M10, and M22), inhibitors (I3), and extrinsic motives (M19 and M23).

 

Table 4.  ANOVA calculated significant differences found between DE participation and motivating or inhibiting factors

 

The same analysis was conducted including administrators' means.  Significant differences were found for twelve motivating factors, two inhibiting factors, and Scale 2 (Personal needs).  The results are found in Table 4.

 

Table 5. ANOVA calculated significant differences found between administrators and DE participation with motivating or inhibiting factors and the four scales

 

Very significant differences (p < .001) were found between faculty (participators and non-participators) and administrators on "reduced teaching load" (M4) and "monetary support for participation" (M10).  The administrators rated these factors much higher than either faculty group, and the non-participators rated both higher than the participator group.  It is of interest to note the differences between groups on issues of "personal motivation to use technology" (M1), "credit toward promotion and tenure" (M21), "release time" (M22), and "distance education training provided by the institution" (M23).  Personal motivation was rated higher by participating faculty than non-participants, while the other three factors were rated higher by non-participating faculty.  The data shows administrators rate these factors significantly differently than faculty, whether participators in distance education or not; however, there were only 9 administrators who completed this section of the survey.

 

Using the mean scores for faculty, an ANOVA was calculated for differences in individual factors (motivating = M, inhibiting = I) or in the 4 scales by gender.  Significant differences were found in 18 motivating factors, nine inhibiting factors, and four scales.  Results are found in Table 5.

 

Table 6: ANOVA calculated significant differences found for gender of respondent and motivating or inhibiting factors

 

Overall, the female respondents rated each one of these factors higher.  There were very significant differences (p < .000 level) for "distance education training provided by the institution" (M23), lack of technological background (I7), and "extrinsic motives" (Scale Four).  A Chi-square test was used to test the null hypothesis that there was no relationship between gender and the level of faculty participation in distance education.  The Chi-square analysis indicated that gender had no significant effect on the level of faculty participation (p < .617); therefore, the hypothesis was not rejected.

 

The percentage of males and females participating and not participating in distance education did not deviate significantly from the group percentages (participators = 14.5%, non-participators = 85.5%).  The percentage of male faculty respondents participating in distance education was 13.7%, while the percentage for those not participating was 86.3%.  The percentage for female faculty respondents participating in distance education was 16%, while the percentage for those not participating was 84%.  This indicates that, of the faculty who responded to the survey, males and females were participating at the same level when compared to the overall distribution of male and female respondents.  There was no relationship found between gender and level of faculty participation in distance education.

 

Using only the mean scores for faculty, an ANOVA was calculated to test differences in individual factors (motivating = M, inhibiting = I) or in the 4 scales by age ranges.  Significant differences were found in 3 motivating factors and four inhibiting factors.  Results are found in Table 6.

 

Table 7: ANOVA calculated significant differences found regarding age of respondent and motivating or inhibiting factors

 

Overall, faculty who are under 30 years of age were more concerned about these factors than older faculty, except for " lack of grants for materials/expenses" (I9), "lack of monetary support for participation" (I14), and "lack of salary increase" (I16) where faculty over 60 years of age were more concerned.  The other factors listed refer to "visibility for jobs" (M13), "career exploration" (M20), and "credit or lack of credit toward promotion and tenure" (M21 and I17) for participation in distance education.  A Chi-square test was used to test the null hypothesis that there was no relationship between age and the level of faculty participation in distance education.  The Chi-square analysis indicated that age had no significant effect on the level of faculty participation (p < .674); therefore, the hypothesis was not rejected.

 

The percentage of faculty within each age range, participating and not participating in distance education, did not deviate significantly from the group percentages (participators = 14.1%, non-participators = 85.9%), except for the under 30 years of age group (5%).  The percentage of faculty respondents within the 30-45-age range participating in distance education was 15.4%, while the percentage for those not participating was 84.6%.  The percentage for faculty respondents within the 45-60-age range participating in distance education was 14.4%, while the percentage for those not participating was 85.6%.  The percentage for faculty respondents within the 60+-age range was 14.3%, while the percentage for those not participating was 85.7%.  This indicates that, in spite of age group, the faculty who responded to the survey were participating at the same level when compared to the overall distribution of respondents' ages.  There was no relationship found between age and level of faculty participation in distance education.

 

Using only the mean scores for faculty, an ANOVA was calculated to see if there were differences in individual factors (motivating = M, inhibiting = I) or in the 4 scales by position level.  Significant differences were found in nine motivating factors, one inhibiting factors, and two scales.  Results are found in Table 7.

 

Table 8: ANOVA calculated for differences by position level of respondents

 

Overall, faculty who were Assistant Professors or Instructors were more likely to be either motivated or inhibited by these factors, with very significant differences (p < .001 level) for "job security" (M9) and "career exploration" (M20), and highly significant differences (p < .000 level) for "graduate training received" (M2), "visibility for jobs" (M13), "credit or lack of credit toward promotion and tenure" (M21 and I17), and "personal needs" (Scale 2).  A Chi-square test was used to test the null hypothesis that there was no relationship between faculty position and the level of faculty participation in distance education.  The Chi-square analysis indicated that faculty position had no significant effect on the level of faculty participation (p < .395); therefore, the hypothesis was not rejected.

 

The percentage of faculty within faculty position level participating and not participating in distance education did not deviate significantly from the group percentages (participators = 14.4%, non-participators = 85.6%), except for Instructors where only 1 out of 16 participated in distance education.  The percentage of faculty respondents who were full professors participating in distance education was 11.9%, while the percentage for those not participating was 88.1%.  The percentage for faculty respondents who were associate professors participating in distance education was 18.9%, while the percentage for those not participating was 81.1%.  The percentage for faculty respondents who were assistant professors participating in distance education was 17.0%, while the percentage for those not participating was 83.0%.  This indicates that, in spite of faculty position level, the faculty who responded to the survey were participating at the same level when compared to the overall distribution of position levels.  There was no relationship found between faculty position level and level of faculty participation in distance education.

 

Using only the mean scores for faculty, an ANOVA was calculated to see if there were differences in individual factors (motivating = M, inhibiting = I) or in the 4 scales by tenure status.  Significant differences were found in ten motivating factors, two inhibiting factors, and one scale.  Results are found in Table 8.

 

Table 9: ANOVA calculated for differences by tenure status of respondents

 

Overall, the non-tenured faculty rated these issues higher than tenured faculty.  There were highly significant differences (.001 or .000 levels) between tenured and non-tenured faculty on "graduate training received" (M2), "opportunity for scholarly pursuit" (M3), "job security" (M9), "visibility of jobs" (M13), "career exploration" (M20), "credit or lack of credit toward tenure and promotion" (M21 and I17), and the "personal needs" scale (Scale Two).  A Chi-square test was used to test the null hypothesis that there was no relationship between tenure status and the level of faculty participation in distance education.  The Chi-square analysis indicated that tenure status had no significant effect on the level of faculty participation (p < .854); therefore, the hypothesis was not rejected.

 

The percentage of tenured and non-tenured participating and not participating in distance education did not deviate significantly from the group percentages (participators = 14.2%, non-participators = 85.8%).  The percentage of tenured faculty respondents participating in distance education was 14.0%, while the percentage for those not participating was 86.0%.  The percentage for non-tenured faculty respondents participating in distance education was 14.9%, while the percentage for those not participating was 85.1%.  This indicates that, of the faculty who responded to the survey, tenured and non-tenured faculty were participating at the same level when compared to the overall distribution of respondents.  There was no relationship found between tenure status and level of faculty participation in distance education

 

Discussion

 While there no statistically significant differences were found for faculty gender, age range, rank or tenure status in DE participation, differences were found between faculty and administrators perceptions of what motivates faculty DE participation.  Faculty participants in distance education appear to be more highly motivated by intrinsic issues of Scale 1 (e.g., intellectual challenge, and overall job satisfaction) than non-participating faculty.  Along those same lines, non-participating faculty seem to be more effected by personal needs of Scale 2 (e.g., release time, credit toward promotion and tenure, and merit pay), inhibitors of Scale 3 (e.g., lack of release time, lack of merit pay, lack of monetary support for participation), and extrinsic motives of Scale 4 (e.g., expectation by university, requirement by department, lack of technical background).

 

This finding may be due to the fact that faculty participating in distance education have already responded to personal needs and external pressures, feel comfortable with their technical skills and are ready to move forward in developing programs and supporting students through distance education.  They know what works for them and what does not, while non-participating faculty may be caught up in the personal technical concerns, preventing them from concentrating on pedagogical issues.

 

Administrators rated factors associated with personal needs of Scale 2 higher than either DE participating or non-participating faculty.  Clearly, the administrators who responded to this survey considered issues of financial support and release time/reduced teaching load to be very important to faculty when deciding whether to participate in dist