Sociology of Education

Haywood & Mac an Ghaill (1996) believe that masculinities are not singularly based on roles, but can be defined in terms of relationships. This, along with Frank’s dynamic nature of masculinity, creates a view of it that is well within the social arena. That masculinity is defined socially accounts for the complexity of roles that are socially constructed as masculine in that it allows what is defined as masculinity to vary within the frame of culture, class, race, behavior and so on. However, the idea of masculinity assumes a certain hegemonic quality when it refers to “forms of masculinity that are culturally dominant in a given setting . . . signifying a position of cultural authority and leadership, not total dominance,” (Connell, 1996: 209). This sort of hegemonic masculinity can be seen at work, for example, in the stereotype of the male sports hero or the male warrior. We contend that a similar hegemonic stereotype has arisen in the arena of technology.

Technology as a Masculine Construct

Technology has been historically and culturally viewed as masculine (Henwood, 2000), and as a male domain (Fredman, 1992; Lage, 1991). Additionally, computers and technology are perceived as belonging to the world of science, which has traditionally been viewed as a male domain (Inkpen et al., 1994). People who participate more readily in technology, at least initially as “early adopters” are usually male (Young, 2000), as evidenced by the commonly held perception that “hackers” and “computer geeks” are typically male (Morahan-Martin, 1998). Given all of this, it is not surprising that research has shown that females hold more negative views about technology than do males (Schumacher & Morahan-Martin, 2001). It is unclear why many females seem to hold negative these attitudes toward technology. Certainly these attitudes do not spring entirely from gender stereotyping. Some negative attitudes have been linked to other perceptions related to gender. These perceptions all align along a central theme supported by various interacting mechanisms: using technology is not a woman’s role. Professions that rely heavily on using computers and technology are typically seen as male domains. Some even suggest that increasing the number of women in such professions could be seen as a threat to the gender order in general and the masculinity of men specifically (Henwood, 2000). The imbalance is maintained in several ways. Fewer computer instructors in secondary and higher education institutes are female (Young, 2000), and there are fewer women students enrolled in computer science programs across the country. Additionally, the portrayal of computer professionals in the mass media (Knupfer, 1998) contributes to negative attitudes held by females. And, the imbalance starts early. Computer games and software, are primarily made for and marketed to males (Deborah Butler, 2000); Henwood, 2000; Knupfer, 1998). Through this avenue, boys get more opportunities to use technology as part of their play activities than girls; the technology itself becomes more obviously identified with boys, adding to the perception that women belong outside the arena of technology.

Spotts & Bowman (1995) break technology down into three categories, old technologies, new technologies and tool technologies. New technologies include distance learning, email, presentation software, and computer conferencing. Old technologies include audio, film and video. Tool technologies include word processing, spreadsheet and statistical analysis programs. Instructional technology, however, is more than the mechanical technologies implied in Spotts and Bowman’s definition. Instructional technology can be defined as “the systemic and systematic application of strategies and techniques derived from behavior and physical sciences concepts and other knowledge to the solution of instructional problems,” (Gentry, 1995). For the purpose of this paper, we confine our examination of instructional technology to the application of such strategies and techniques that involve computer technologies as well. Faculty members are progressing in their use of such instructional technology (Groves & Zemel, 2000), but for a number of reasons, faculty in higher education have adapted to the use of instructional technology more slowly than other professionals have incorporated technology into their jobs (Dusick, 1998). However, while faculty are slowing adopting instructional technologies, many university and distance education administrators are calling for a faster pace, including more web-based courses. Faculty members are not immediately responding to the call to create these courses, even though they are using more instructional technologies than ever before. Hannon (1999) calls on faculty to, “. . . realize that technology—in particular, the Internet—is now integrally related to scholarship; it is not simply an external resource for students to consult when doing their assignments” (p.B8). This apparent lack of understanding of the growing importance of technology in scholarship is not the only factor preventing large numbers of faculty from embracing web-based instruction. Various studies have determined that there are at least four primary universal barriers affecting higher education faculty adoption of technology: lack of institutional support, lack of financial support, lack of time, and lack of knowledge (Betts, 1999; D. Butler & Sellbom, 2002; Chizmar & Williams, 2001; Groves & Zemel, 2000;).

Current Trends in the Use of Technology

Evidence that females more commonly hold negative views toward technology than males notwithstanding, the use of technology by females, particularly Internet-based technologies, seems to be steadily increasing. In the mid 1990s, Currid (1996) claimed that one third of Internet users were female and two-thirds male. Data from one year later told a different story. Two studies between 1989-90 and 1997 showed that there was a significant increase in computer use for both males and female over the time period (Schumacher & Morahan-Martin, 2001). In fact, by 1997, 89 percent of males said they used the Internet, as did 76 percent of females. There was still a gender difference, but the gender gap in Internet use was not as large as Currid had claimed. Further still, more current data showed that not only is the difference in the numbers of males and females diminishing, but also in some instances females are outnumbering their male counterparts in the use of technology. Despite these apparent trends, many contend that negative attitudes of females toward technology persist. In a recent report, for example, Jackson, Ervin, Gardner, & Schmitt (2001) found that females used e-mail more than did males, males used the Web more than did females, and females reported more computer anxiety, less computer self-efficacy, and less favorable computer attitudes.

Technology in Tertiary Educational Settings

In academe, there are well-established gender differences among faculty. Research has shown that women are less likely than men to hold full professor rank (Hagedorn, 1996; Park, 1996), receive smaller salaries than men of the same rank (Bellas, 1997; Benjamin, 1999), publish less (Schneider, 1998), and spend a larger proportion of time on teaching activities (Park, 1996; Stecklein & Lorenz, 1986). Gendered trends have also been found in relation to technology use. Spotts, Bowman, & Mertz, (1997) found that male faculty rated their own knowledge and expertise higher in some technologies than women did. For example, men self-reported a superior knowledge of and experience with the Internet. Interestingly, the researchers found no significant difference between male and female faculty in the frequency of technology use. Their study focused more on what Clark (1994) has termed “delivery technologies,” rather than on “instructional design technologies.” Clark defines delivery technologies as those that dispense instruction to the student—for example a computer program, while instructional technologies focus on pedagogy. Clark sees the distinction as between fitting the content into technology and using technology to enhance the content. The former focuses on the technology, or delivery, while the latter focuses on the educational concept, or pedagogy.

Many faculty view instructional technologies as simply the delivery systems like those Clark (1994) discusses, such as computer hardware and software employed in the course of instruction. Clark asserts that most research into faculty technology beliefs and practices has focused on these aspects and this is why no large gender differences among faculty in terms of instructional technology beliefs and practices have been found. Campbell (2000) believes that gender creates differences in education and argues that there is a great gender difference in regard to technology, not only in the practices of those who use it, but more fundamentally, in language and in socialization of those who use it:

In short, educational computing is a man’s world where females are not welcome; males take over, push females out of the way, and brag about their “superior” knowledge; and demean female knowledge. The culture is alien and separate; the language is exclusive. As females may have differing cognitive abilities in regards to spatial abilities, and in the ability to develop autonomy and intimacy, they are often disempowered by contexts in which procedural, linear thinking, competition, and autonomous knowing are incompatible with their socialized female values (2000, no page number).

We hypothesized that that an examination of delivery technologies as well as beliefs and practices of instructional design technologies would uncover a significant gender difference.

Method

The study was conducted at a large research university in the southeast United States. The university has a full-time faculty of approximately 775 in twelve colleges and schools and serves approximately 19,300 undergraduate, professional, and graduate students. It is the flagship university of the state and offers 215 degree programs and almost 20 distance education degree programs, both web-based and video-based. Faculty in this study were of all ranks and represented all colleges.

The study consisted of two parts. Part A was designed to ascertain actual faculty instructional field practices, while Part B was designed to determine specific beliefs held by faculty about the use of instructional technology, and to discover how faculty self-report their actual practices. The major distinction between practices in Part A and Part B was that in part A, the faculty use of instructional technologies was directly observed by the researchers, while in part B, the use of instructional technologies was self reported by the faculty participants.

In Part A, data were collected from a total of 174 WebCT courses through a grounded theory approach, which permitted the field data to define the conceptual categories. Fifty-four female and 41 male faculty members taught the 174 courses examined. However, 50% of the courses had male instructors, while 49% female instructors—there was one female-male team—which meant that more men than women had multiple courses. In order to determine actual practices, the instructional technology tools in each of the six WebCT modules were examined for content modification and applied use. The researchers initially observed basic patterns of use, which were afterward more closely evaluated to determine whether these patterns were actual or artificial. The patterns initially pointed to a correlation between faculty rank, tenure status and gender of faculty member and type of instructional technology used.

Part B, designed to measure self-reported beliefs and practices, was conducted via a web survey. All full-time faculty were emailed and asked to take the survey, which was accessible by clicking on a link and launching a web browser. The return rate was roughly 18%, with 54% of the respondents being male, and 46% female. A majority of the males were full professors (52%), while the majority of females were assistant professors (39%). Seventy-three percent of the males were tenured, while 51% of the females were tenured. Demographics of part B are summarized in table 1.

Table 1. Demographics of Part B.
	Female		Male		Total
	Number	%	Number	%	Number	%
Instructor	10	15%	2	3%	12	8%
Assistant Professor	26	39%	17	21%	43	30%
Associate Professor	18	27%	19	24%	37	25%
Full Professor	13	19%	41	52%	54	37%
total	67	100%	79	100%	146	100%

Received Tenure	34	51%	58	74%	92	63%
Not received tenure	17	25%	16	20%	33	23%
N/A	16*	24%	5	6%	21	14%
total	67	100%	79	100%	146	100%

The survey was divided into three sections, each designed for specific measurements: demographic information, beliefs regarding instructional technology, and use of instructional technology. Four broad categories of questions assessed beliefs: beliefs regarding teaching and learning styles, beliefs regarding value of instructional technology, beliefs regarding time required to use instructional technology, and beliefs regarding skills required to use instructional technology. The survey asked respondents to rate their level of agreement or disagreement with positive and negative statements about technology and its use in education via a Likert-type response scale. The final section asked respondents to report on frequency and amount of use of a variety of technological tools.

The data for both parts of the study were analyzed for frequencies and cross-tabulated using Pearson’s Chi-square to test for significance in differences of responses based on gender, rank and tenure status, and those tabulations generating significant differences were identified. An alpha level (level of significance) of .05 was used throughout data analysis.

Limitations of Part B

The most obvious limitation of part B of the study was the small sample size due to the low survey return rate of 18 percent of the sampling frame. Technical difficulties caused the follow-up email to not reach the faculty, so this return rate represents initial respondents only. However, based on prior survey response percentages, these researchers believe that this response rate is typical for this University and the follow-up email would not have resulted in a large increase in survey responses. In addition to the small sample size, potential for measurement error may have been introduced because the survey was distributed by the University’s Faculty Resource Center (FRC). It is conceivable that this avenue of dissemination may have influenced participant response either positively or negatively. For example, faculty who have no knowledge of the FRC or who do not envision needing their services may not have been inclined to respond. Conversely, those faculty who have used services at the faculty resource center may have been more likely to respond to the call for participation.

Results and Discussion

For this study, we gathered information in three areas: observed instructional technology practices (delivery practices), self-reported instructional technology practices, and self-reported instructional technology beliefs. We expected to find a gender difference in all three areas. We anticipated that there would be a difference in the way female and male faculty view technology and what they believe about its intrinsic value and that these differences would manifest themselves as differences in observed instructional technology practices. We did find a significant difference in observed practices: females differed from males in the actual use of particular kinds of instructional technologies. However, we did not find a significant gender difference in self-reported beliefs and practices of instructional technologies.

Part A and B of the study revealed no significant differences in terms of faculty rank and tenure status. However, in terms of gender, part A revealed there were two significant differences in the use of two of the tools, the content module and the quizzes/tests feature. Female faculty used both more than male faculty. The content module showed a Chi-Square value of 4.794 at the .029 level. The quiz module also demonstrated a significant gender difference in use. The Pearson Chi-Square value was 6.441, which is significant at the .011 level.

Part B of the study yielded no significant differences in responses when gender was cross-tabulated against beliefs regarding instructional technology and against actual self-reported behavioral practices in using instructional technology. Interestingly, however, while statistical analysis of the Part B survey data revealed no significant relationship between gender and self reported beliefs and self-reported practices, the gender distribution within the sampling frame (all University faculty) was 31.2% female, 68.8% male, but the gender breakdown of the respondents was 46.3% female, 53.7% male. Females were disproportionately represented in the sample. The demographic breakdown of the sample itself compared to the sampling frame does could itself be viewed as significant. The fact that we observed a difference is consistent with research reporting that women and men use technology differently. Research has shown that males use the internet and the world wide web primarily for the gathering of information (Gefen & Straub, 1997), while women use them primarily for communication. We observed that female faculty members responded to an email requesting them to fill out a web survey about technology use in education in significantly greater numbers than did their male counterparts. To the extent that this use of technology represents communication, this observation is consistent with the research.

One clear question emerged from the study: in terms of instructional technology, why is there a difference between what female faculty members say they are doing, and what they are actually doing? Hand in hand is this question: why is there no similar difference among male faculty? It is not at all clear what motivations and rationale faculty members employ when deciding what to do and how their beliefs coincide with self-reported practices and observed practices in regard to instructional technology. In our opinion, characterizing and understanding these factors is critical to understanding the role of gender in faculty use of technology. Possible explanations of our results suggest three potential theoretical frameworks to guide future research.

The first theoretical framework offers that women have traditionally faced a challenge breaking into male dominated fields, namely loss of status due to the feminization of the field (Borsoo, 1996, Henwood, 2000). In order to combat this loss of status, women in newly opened fields tend to adopt the accepted gendered behavior of the men already in the field (Chliwniak, 1997). This phenomenon, known as systemic paternalism, may also be occurring in the field of instructional technology. The field of instructional technology is relatively new to both genders. However, to the extent that the field has been masculated through its connection to the masculine nature of technology itself, female faculty may try to compensate for being female in a masculine field by adopting male-gendered behavior when selecting and implementing teaching methods and tools. This explanation is certainly supported by the findings of Part A, where female faculty used technology outside of the typically-gendered manner of other females. It is possible that these female faculty were using technology in a way which they believed would be viewed by their male colleagues as legitimate; in essence, they did not want their use of instructional technology to be seen as feminine and therefore devalued (Cockburn, 1983). Such views may also be at work in part B of the study as well in that female faculty members may have self-reported beliefs and practices consistent with similarly legitimized beliefs and practices.

Another theoretical framework that may explain the unexpected results of the current study suggests that women may be adapting to, instead of challenging, existing educational methods and standards that were created by and primarily for men (Griffin, 1997). The traditional informational style of teaching represented by the lecture format of teaching present in most university classrooms today is a style that many sociologists and educators believe is more suited for masculine learning styles. The common uses of current forms of instructional technology may discourage some of the more feminine learning styles. In using instruction technology, then, it may be that rather than adapting the technology, female faculty members are instead changing their teaching to support more masculine learning styles.

A third theoretical framework considers the newness of the field of instructional technology and the implications of this newness on teaching, teaching styles and pedagogies. Unlike email and the Internet, which have been widely available to the general public since around 1995, using technology in teaching is still in its infancy. Therefore, teaching styles have not yet been personalized, nor has a sound pedagogy been explored (Earle, 2002). The pedagogy of instructional technology use cannot be expected to be as polished and established as the pedagogy of the traditional classroom. In fact, not all faculty members agree on just exactly how to define ‘instructional technology’. Because of these factors, a faculty member may do one thing, but self-report another. However, in this framework, it is not clear why we would observe a significant difference in self-reported beliefs and practices and observed practices only for female faculty but not for male faculty.

This study provides evidence that there is a gender difference in how instructional technology is used in tertiary education. While we are not able to determine the cause behind the gender difference, it is clear that this difference has serious potential effects on student learning and needs to be further examined. To best serve the interests of all of those we educate, we must be critically aware of the choices we make and why we make them.

References

Bellas, M. L. (1997). Disciplinary Differences in Faculty Salaries: Does Gender

Bias Play a Role? Journal of Higher Education, 68(3), 299-321.

Benjamin, E. (1999). Disparities in the salaries and appointments of academic women and men. ACADEME, 85(1), 60-62.

Betts, K. (1999). Perception vs. reality: top 10 motivators and inhibitors for participating in distance education as view by faculty and deans at a research II institution. Retrieved December 15, 2002, from http://www.geteducated.com/vug/archives/vug0499.htm#chalk

Borsoo, Paulina (1996). The memoir of a token: an aging Berkeley feminist examines wired. Wired Women: Gender and New Realities in Cyberspace. Ed. Lynn Cherny and Elizabeth Reba Weisse. Seattle: Seal Press, p 24-42.

Butler, D. (2000). Gender, Girls, and Computer Technology: What's the Status Now? Clearing House, 73(4), 225.

Butler, D., & Sellbom, M. (2002). Barriers to adopting technology for teaching and learning. Educause Quartely, 25(2), 22-28.

Campbell, K. (2000). Gender and educational technologies: Relational frameworks for learning design. Journal of Educational Multimedia and Hypermedia, 92, 131-150.

Chizmar, J. F., & Williams, D. B., 2001, 18-24. (2001). What do faculty want? Educause Quarterly, 24(1), 18-24.

Chliwniak, Luba (1997). Higher Education Leadership: Analyzing the Gender Gap (Ahse-Eric Higher Education Reports) New Jersey: John Wiley & Sons.

Clark, R. E. (1994). Media will never influence learning. Educational Technology Research and Development, 42(2), 21-29.

Cockburn, Cynthia (1983). Brothers: male dominance and technological change. London: Pluto Press.

Currid, C. (1996). Bridging the gender gap. InformationWeek(573), 114.

Dusick, D. M. (1998). What social cognitive factors influence faculty members’ use of computers for teaching? A literature review. Journal of Research on Computing in Education, 31(2), 123.

Earle, Rodney S. (2002). The integration of instructional technology into public education: promises and challenges. Educational Technology, 42(1), 5-13.

Fredman, A. (1992). Yes, I can. Action projects to resolve equity issues in educational computing. Eugene, OR: International Society for Technology in Education.

Gefen, D., & Straub, D. W. (1997). Gender differences in the perception and use of e-mail: An extension to the technology acceptance model. MIS Quarterly, 21(4), 389.

Gentry, C. G. (1995). Educational Technology: A Question of Meaning. In G. J. Anglin (Ed.), Instructional Technology: Past, Present and Future (2nd ed.). Englewood, CO: Libraries Unlimited, Inc.

Griffin, Glenda (1997). Teaching as a gendered experience. Journal of Teacher Education, 48(1), 7-18.

Groves, M. M., & Zemel, P. C. (2000). Instructional technology adoption in higher education: An action research case study. International Journal of Instructional Media, 27(1), 57.

Hagedorn, L. S. (1996). Wage equity and female job satisfaction: The role of wage differentials in a job satisfaction cause model. Research on Higher Education, 37(5), 569-598.

Henwood, F. (2000). From the woman question in technology to the technology question in feminism: rethinking gender equality in IT education. The European Journal of Women’s Studies, 7, 209-227.

Hurrell, G. (1999). The Interplay Between Constructions of Masculinity and Constructions of Subject English in One Coeducational Year 8 English Class. Unpublished Honours Thesis, Flinders University.

Inkpen, K., Upitis, R., Klawe, M., Lawry, J., Anderson, A., Ndunda, M., et al. (1994). We Have Never Forgetful Flowers in Our Garden": Girls' Responses to Electronic Games. Journal of Computers in Math and Science Teaching, 13(4), 383-403.

Jackson, L. A., Ervin, K. S., Gardner, P. D., & Schmitt, N. (2001). Gender and the Internet: Women Communicating and Men Searching. Sex Roles, 44(5), 363.

Knupfer, N. N. (1998). Gender divisions across technology advertisements and the WWW: Implications for educational equity. Theory Into Practice, 37(1), 54.

Lage, E. (1991). Boys, Girls, and microcomputing. European Journal of Psychology in Education, 6(1), 29-44.

Morahan-Martin, J. (1998). Males, females and the internet. In J. Gackenback (Ed.), Psychology and the internet: imtrapersonal, interpersonal and transpersonal applications (pp. 169-197). San Diego: Academic Press.

Park, S. M. (1996). Research, Teaching, and Service: Why Shouldn't Women's Work Count? The Journal of Higher Education, 67(1), 46-84.

Schneider, A. (1998, September 11, 1998). Why don’t women publish as much as men? The Chronicle of Higher Education, 45, A14.

Schumacher, P., & Morahan-Martin, J. (2001). Gender, internet and computer attitudes and experiences. Computers in Human Behavior, 17(1), 95-110.

Spotts, T. H., & Bowman, M. A. (1995). Faculty use of instructional technologies in higher education. Educational Technology, 35(2), 56-64.

Spotts, T. H., Bowman, M. A., & Mertz, C. (1997). Gender and use of instructional technologies: A study of university faculty. Higher Education, 34(4), 421.

Stecklein, J. E., & Lorenz, G. E. (1986). Academic women: Twenty-four years of progress? Liberal Education, 72(1), 63-71.

Young, B. J. (2000). Gender Differences in Student Attitudes toward Computers. Journal of Research on Computing in Education, 33(2), 204.

Back to Course Work