Gender, Faculty and Teaching with the World Wide Web: A Study of WebCT Module Use

Susan Lucas
The University of Alabama

Abstract

Men and women use technology differently. Specifically, the web is used differently. Research has shown that males use the web primarily for the gathering of information, while women use it primarily for communication. The objective of this study was to see whether these tendencies where also found in higher education. Does gender influence web use in higher education? As higher education has begun to shift from the traditional classroom to the technological web, more and more online course have become a part of the curriculum. The potential benefit of understanding how gender fits effects teaching in an online course is enormous.

A study of 174 online courses was conducted using six separate factors to test whether male and female faculty would choose different modules to teach a course in an online educational environment. The expectation that a correlation existed with the literature and that male faculty would use tools to disseminate information and females would use tools to enhance communication. However, the results of the study showed that while male and female faculty do use the tools differently, the difference was found in unexpected areas.

Background

Gender

Gender has traditionally been a grammatical category that distinguishes male, female and neuter nouns. The term is no longer used solely to differentiate inanimate and non-human animate nouns; the term is now used to differentiate humans. Humans are said to have both a gender and a sex. The confusion surrounding this word exists because gender and sex are not synonymous . Gender is socially constructed, while sex is biologically determined. Gender refers to culturally defined roles, and the relationships that exist between the two sexes because of these roles. Gender roles may or may not be biological or have a biological basis. Regardless, they have become a standard of classification in our society. No area of society escapes gender stereotyping, not even something as seemingly neutral and unbiased as technology.

Since technology has been historically and culturally viewed as masculine, the people who use technology are assumed to be masculine, the “hacker” and “geek” cultures around technology are viewed as masculine, and even the hardware and machines associated with technology are seen as masculine (Butler, 2000; Henwood, 2000; Schumacher & Morahan-Martin, 2001, Young, 2000). This gender stereotyping of technology has implications for users in that it does not address the feminine.

Humans respond to various stimuli based on gender. Males and females may respond differently to phenomena. It follows that men and women respond differently to different aspects of technology, including computers, the Internet, email and the world wide web (web). This gender-based response needs to be accounted for and tailored to education. How does it factor into learning with technology, specifically into web-based instruction?

There are multiple web-based course management systems such as WebCT and Blackboard available for faculty to design and teach web-based courses. These management systems, or online educational environments, make available various instructional modules which help faculty meet their educational goals and objectives. The methods chosen to achieve these goals and objectives are influenced by the gender of the faculty member. Male faculty may choose one type of module to reach their objective and females another. Are faculty members making the appropriate decisions and choosing modules that will enhance learning for all students? This paper will review the literature which examines gender differences in attitudes toward technology and gender differences in the use of technology, and will discuss possible consequences for web-based instruction.

Gender and Attitudes Toward Technology

Females have more negative views toward technology than do males. The view of technology as masculine is one cause of females having these negative attitudes about technology. This fact is intriguing since women have been involved in the evolution of computer technology from its inception. One of the early computer programming languages Ada was named after programmer Augusta Ada Lovelace; Adele Goldstine wrote the first programs for ENIAC, and Grace Hopper helped develop COBOL (Butler, 2000). Despite the fact that women have been an integral part of technology development, and that girls have had positive role models in technology, research has shown that while males view technology generally positively, females view technology more negatively (Butler, 2000; Schumacher & Morahan-Martin, 2000; Jackson, Ervin, Gardner & Schmitt, 2001; Young, 2000).

These negative attitudes are not simply the result of gender stereotyping. Rather, they stem from several sources. The professions around computers are seen as male domains. 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. Stereotypes also play an important role in the negative attitudes females hold. Computer users are seen as “nerds,” “geeks,” or “techies.” These social categories, while respected for boys, are unacceptable for girls. This is evidenced by one of the richest and most respected men in America, yet one of the most famous “geeks,” Bill Gates. Additionally, the portrayal of computer professionals in the mass media (Knupfer, 1998), contributes to negative attitudes. Computer games and software are primarily made for and marketed to males. (Butler, 2000; Henwood, 2000; Knupfer, 1998). Computer games allow users to start to become comfortable with computers at a very young age. Since most games involve guns and violence, few girls are interested in them, and this gives boys more experience with computers. Thus, the lack of experience (Butler, 2000) contributes to girls’ negative feelings about computers. However, as females become more experienced with computers, their attitudes about them change (Arbaugh, 2000). This attitude has driven the change in use of technology for females over the past few years.

Gender and Technology Use

Margaret Wylie asked in 1995 to, “Make no mistake about it; the Internet is male territory. Considering its roots are sunk deep in academic and the military-industrial complex, that’s hardly surprising” (in Campbell, 2000). In 1996, Currid claimed that one third of Internet users were female and two-thirds male. Data from one year later told a different story. Schumacher & Morahan-Martin (2001) compared the use of computers in two groups of college freshmen, one group in 1989-90, the other in 1997. What they found was that there was a significant increase in computer use for both males and female over the time period between the two studies. In fact, 89 percent of males said they used the Internet, and 76 percent of females said the same. This shows that there was still a gender difference in the use of the Internet, email and the web, but that the gender gap in Internet use was not as large as Currid claimed. Additionally, Schumacher & Morahan-Martin found that there was a difference in skill, namely that males self-reported more skill than females in the use of the Internet and the web. However, there was no gender difference in use of email (2001). Data from 2001 showed that 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 and less stereotypic computer attitudes (Jackson, Ervin, Gardner & Schmitt, 363).

This shows that the gender gap began to close by 1997, but still had a considerable way to go.

Women are now using one form of technology more than men, a form that allows women to focus on what gender stereotypes claim to be fundamental to women, communication and relationships. This form of technology is email. Women are now said to outnumber men online (Van Slambrouck, 2000), but their primary reason for being online is still for email. As Wilson (2000) says, “Communication, particularly e-mail, is by far the most important feature of the Internet to women.” America Online (AOL) is currently running a commercial for their internet service. In the commercial, various men and women give reasons for why they like to use AOL in an attempt to get other users to sign up for the service. The women predominantly cite reasons such as email, keeping in touch with family, and sharing news and personal events among friends. The men say they are using the internet to find facts or to consult their stock portfolios. Gefen & Straub attribute this use of email to the fact that men focus on independence and hierarchy, and women focus on intimacy and solidarity (1997). Email is an important tool for women, since it allows them to be are more interpersonally oriented, where men are more information/task oriented (Jackson, Ervin, Gardner & Schmitt, 2001), and would be interested in other uses of the internet.

Some (Wilson, 2000; Van Slambrouch, 2000) believe that the web will become more like email in that it will become the domain of females. Wilson claims that the Internet is now more feminine than masculine, but he perhaps means that there are more female than male users of the web (2000). It is clear that more and more females are using the web, and using it for a variety of reasons, but they still seem to be primarily interested in communication rather than information. Arbaugh points out that,

This research suggests that men also communicate via the medium in a competitive mode, either elevating their own status or lowering that of others. On the other hand, it has been suggested that women see cyberspace as a means to develop increased collaboration and support networks for increasing learning and communication of the entire group (2000, 504)

We must, however, consider the fact that many email clients are now web-based, and thus the use of email via a browser could be affecting the numbers of women using the web. Nonetheless, the important point to remember is that females and males use technology differently, and these gender differences are important to education.

(See table 1 for a gender comparison of use and ability over the various years).

Faculty and Technology

Instructional technology is, simply, any technology involved in instruction. However, in recent years, the term has come to mean primarily those technologies associated with computers and education. Video and audio are no longer viewed as instructional technologies. Further still, some faculty and others view instructional technology as synonymous with web-based instruction and do not equate other computer technologies with instructional 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 would be word processing, spreadsheets and statistical programs (1995). For this paper, instructional technologies will be defined as any computer technology involved in instruction.

For a number of reasons, faculty have adapted to the use of technology in instruction somewhat more slowly than other professionals have incorporated technology into their jobs (Dusick, 1998). Many motivational factors have influenced this slow adoption, including lack of time, lack of money, and lack of understanding of how technology can benefit instruction. Nevertheless, faculty are progressing in their use of technology in instruction. Two very important studies have been conducted, one by Spotts & Bowman in 1995, and the other by Groves & Zemel in 2000. These studies researched faculty attitudes toward and the use of various instructional technologies. The later study used an instrument that was adopted directly from the Spotts & Bowman instrument. This gives a very accurate gauge of change over the five years between the studies. Spotts & Bowman found, in 1995, that only 38 percent of faculty believed technology to be very or critically important in teaching. By 2000, that percentage had increased to 46 percent (Groves & Zemel). Both studies found use of word processing to be quite high, but one of the largest increases came from the use of email. Spotts & Bowman found that only 32 percent of the faculty used email, whereas Groves & Zemel found that number to be 62 percent, or almost double the amount. Another large jump came from distance education, or web-based technologies. In 1995, only 9 percent of the faculty surveyed used distance education, or web-based instruction, in their teaching. By 2000, that number had grown to 14 percent, an increase of over fifty percent.

While university and distance education administrators are calling for more web-based courses, it seems as if faculty members are not immediately responding to the call to create these courses. 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). Lack of understanding of the benefits of web-based courses is not the only factor preventing large numbers of faculty from embracing web-based instruction. According to Betts, (1999) the top four inhibiting factors to faculty participation in web-based or distance education courses are: 1) workload; 2) lack of technical support; 3) lack of release time; 4) concern about course quality. The fourth highest factor actually deals with the educational value of these courses. Faculty are primarily concerned with work-condition issues rather than educational ones, and this is chiefly preventing them from implementing web-based courses.

Faculty, Technology and Gender

While there have been studies on gender-based use of technology among the general population, there has not been extensive study of gender and technology use among university faculty. Two questions remain: Is the way faculty use technology different from the way the population at large, and if so, what are the implications for web-based instruction? It seems that faculty would follow the norms for male and female use of technology, and that the reasons for the use would be the same as those for the population in general. If males use technology for information and females for communication, does this also hold for use by post-secondary faculty? Spotts, Bowman & Mertz (1997) found that male faculty rated their knowledge and expertise higher in some technologies than did women. Men reported a superior knowledge of and experience with the Internet. There was no significant difference between the genders in reported knowledge and experience with email, word processing and presentation software. As far as use, the researchers found no significant difference in the frequency of use between male and female faculty. However, they do believe that there are gender differences in technology use by faculty and these differences need to be addressed.

Campbell agrees that gender creates differences in education and argues that there is a great gender difference in technology, not only in use, but in language and in socialization.

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).

Faculty, Gender and the Web

While there have been a few studies on faculty, technology and gender, there have been fewer still on faculty, gender and the use of the web. There seems to be little difference in frequency of use, knowledge and experience of web-based technologies between male and female faculty, but there may be a difference in the way the two groups use the web. Evidence has shown that women use the web more for communication and men more for information, so male and female faculty may be using web-based technology differently.

Expectations of the Study

Based on current research, a gender difference in the way male and female faculty use the web to teach should exist. Applying the research conclusion that males gather information and females communicate, given the same choices, male and female faculty would differ in the tools they choose and in the way they use tools. Males would choose “information” tools and try to disseminate information while females would choose “communication” tools and be more concerned with communication in the learning process. The goal of the study was to determine whether gender influenced faculty in their choice of web tools, or modules, for delivery of online courses via WebCT.

The study was conducted during the spring of 2002 at the University of Alabama. The University is a doctoral/research university-extensive (Carnegie classification) and has 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. It has a faculty of approximately 800, and of those, roughly one-forth have attended some sort of technology training over the past three years. This includes the almost fifteen percent who have had training specifically in WebCT.

WebCT, along with its competitor BlackBoard, is sometimes referred to as a course management system. A more fitting term, however, would be an online educational environment. As an online educational environment, WebCT offers faculty the opportunity to incorporate more technical kinds of learning techniques into their web-based courses without needing any special technological knowledge. Before the advent of these environments, faculty who wished to use tools such as bulletin boards or chat, or even email either needed to buy the programs, use a third-party’s or create the program themselves. None of these options was optimal. WebCT has, in essence, kept faculty from having to “reinvent the wheel” every time they wished to use a new technology in their teaching and allowed faculty to focus on their discipline rather than on the technology.

I manually examined all WebCT courses at the University of Alabama existing at the beginning of the spring term, 2002, which amounted to a total of 240 WebCT courses. Female faculty owned (this word will be used for lack of a better one; faculty have the courses created and are responsible for them, but do not necessarily build nor teach them) 117 (49%) courses, male faculty owned 121 (50%), one course owned by a male-female faculty team. The course owned by the male-female team was not used. In the final analysis, there were 53 female faculty members who own courses and 41 male faculty members. Many faculty owned multiple courses. In fact, one male faculty member owned 25 courses. The highest number owned by a single female faculty member was seven. Because the male faculty member had only modified one of the 25 courses, 24 of them were discarded and not used in the analysis. Additionally, of the 240, forty (17%) had never been modified and were therefore excluded from the final analysis. Modification means that the faculty member or faculty member’s appointee had gone into the course and changed at least one aspect of it. Overall, 174 courses were analyzed, 97 (56%) owned by female faculty and 77 (44%) owned by male faculty.

The rank of the faculty encompassed adjunct, temporary faculty to full professors, and they represented eleven different colleges and schools at the university. The highest percentage of courses owned came from the College of Human Environmental Sciences, at 22%. The next highest came from the College of Nursing with 16%. Arts and Sciences, the largest college at the university had 15%, and faculty from the College of Communication and Information Sciences owned 14%. Additionally, faculty from Business, Education, Library Sciences, Health Sciences, Engineering, and Social Work all owned courses.

Of the approximately fourteen modules available in WebCT for course delivery and augmentation, six were examined for evidence of modification. The modules were calendar, quiz, content, chat, discussions, and syllabus. Four of the modules were information modules: calendar, external syllabus, content and quiz, where two were communication modules, chat and discussions. The calendar module is represented by a table where assignments and events can be added to inform the class of assignments and important dates. The quiz module can be used as an online test center or as a survey instrument. Results from either are automatically entered into the student database. Lectures and class notes are most commonly placed in the content module. This module distributes the content in a strictly linear fashion where the students complete once section before moving on to the next, much the same way as classroom lectures are delivered, meaning one session is built upon the previous. Chat is a synchronous tool where students interact with each other and with the professor in real time. Responses are immediate. Conversely, Discussions are asynchronous, where students have time to formulate answers and/or questions. The syllabus replicates a traditional course outline and policy statement. For these reasons, chat and discussions were used as communication determiners, where the calendar, content and quiz were used as information determiners. The syllabus was viewed as neither a communication determiner nor an information determiner.

As males and females tend to self-rate their computer competency skills and comfort levels differently, the goal was to determine if this holds true for faculty; consequently, the syllabus was used to determine technology competency. WebCT has two options for using a syllabus, the built-in tool and external syllabus. In order to use the external syllabus, faculty needed to know, at the very least, how to convert their existing syllabus from a word processing program into html, upload the file into WebCT and then add the file as their syllabus. This somewhat complicated process is much more difficult than using the built-in syllabus tool. For this reason, the external syllabus was used to roughly gauge competency and to determine if there was a gender difference in actual technological ability.

Each of the 174 courses was manually accessed via a generic user id. Each module in each course was examined for evidence of modification. Except for the chat module, it was visibly clear when all modules had been modified. Chat is synchronous, and therefore to really know if it is being used one must be electronically present at time of use. However, WebCT has the ability to record transcriptions from the chat rooms. These transcripts were examined to see if the rooms had been used. If there was an entry, chat was recorded as used.

The resulting data of the manual count were analyzed using the SPSS program. In order to assess gender differences, crosstabs and the chi-square statistics were used for the dichotomous (yes/no) variable after the manual count. An alpha level (level of significance) of .05 was used throughout data analyses.

Results

Communication determiners

The first module used to determine whether there was a gender difference in the use of communication tools was the chat function. Chat proved to be the second least popular module of those examined, second only to the quiz module. Only 30 female-owned courses (31% of total courses owned by females) and 27 male-owned (35%) used this synchronous communication tool. There was no significant gender difference in the use of this tool. Like chat, there was no significant gender difference in the use of the discussions communications module. Thirty-nine female-owned courses (40%) had this module available for student use, while 30 male-owned courses (39%) did the same.

Information determiners

Like both communication determiners, there was no significant gender difference in the use of the calendar module. Of the female-owned courses, 47 or 48% utilized the calendar tool, while 29 male-owned courses (38%) used this tool. However, two information other tools did show a significant gender difference in use.

The content module, which delivers information in a linear manner, showed a Chi-Square value of 4.794 at the .029 level. Of the female-owned courses, 59 (61%) used the content module. Of the male-owned, 34 (44%) used the module. Female faculty were more likely to use this module than were male faculty. Similarly, the quiz module also demonstrated a significant gender difference in use, although this module proved to be the least popular of all the modules examined. Female faculty members were more likely than their male colleagues to use the quiz; 36 female-owned (37%) tested online, while few (15 or 19%) male-owned incorporated this function. The Pearson Chi-Square value was 6.441, which is significant at the .011 level.

The remaining module, the external syllabus demonstrated that a significant gender difference in technology ability did not exist; meaning gender did not factor into ability. Fifty-three female-owned (55%) and 45 male-owned (58%) courses had an external syllabus.Totals for male and female faculty using specific WebCT modules:

The results showed that there is a significant gender difference in some modules used to teach via WebCT. However, the results were the opposite of what had originally been expected since female faculty are using more information modules than are their male colleagues. Female and male faculty are using communication tools similarly and with no significant gender difference, which is quite different from what the research studies of the general population have shown. Several hypotheses may explain the results, but no clear answer can be found until a follow-up qualitative study is done which examines and analyzes specific motivations.

Implications for Future Research

While it is impossible to know the motivations and rationale that faculty have and use when choosing an appropriate module to meet their educational goals, the results open several potential theoretical frameworks for guiding future research.

The first theoretical framework and avenue to explore may deal with the recurring problem women have had breaking into male-dominated fields and the behaviors women adopt once in the field. An example of this can be illustrated by looking at the history of women in management positions. Traditionally, in government, business, medicine, military, religious organizations, and almost every work segment, men have been in charge. The Baby-Boomer generation was the first to offer women managers in numbers of consequence. These women had few, if any, feminine models of management style. Rather, these female managers relied on traditional management styles, which were developed by and for males. They also had to deal with validity and being taken seriously by their superiors, peers and employees. Consequently, some of these new female managers appeared markedly masculine in their styles and at times used a more “masculine” style than the males. They tended to over-compensate for being women and assumed that adopting perceived masculine management techniques would make them effective managers. The next group of female managers, those from Generation X, had a model to use, albeit a flawed one. These women realized that they could use more “feminine” management techniques and still be effective managers.

The same phenomenon may be occurring with faculty using web-based technology tools for teaching. The results of the study showed that female faculty are more likely to use information modules than male faculty. Perhaps this is a form of over-compensation as well. Female faculty want to be viewed as legitimate and respected scholars, researches and teachers, and may be hesitant to adopt techniques that are perceived as “feminine” and therefore devalued.

Another theoretical framework that needs to be explored and which may explain the unexpected results is that women may be adapting, instead of challenging, existing educational methods and standards that were created by and primarily for men. The traditional informational style of teaching present in most university classrooms today is a style that is more suited toward “masculine” learning styles. Understanding that the current trend in online course delivery is that the majority of courses are being adopted directly from their classroom counterparts (Twigg, 2001), with no modifications in presentation and content, it is easily apparent that the traditional, linear information style, the masculine norm, is being perpetuated.

A third theoretical framework that needs to be explored is the newness of the field of instructional technology and the implications of this newness on teaching. Unlike email and the internet, which have been widely available to the general public since around 1995, using technology in teaching, particularly course management systems, is still in its infancy and therefore teaching styles have not yet been personalized. Faculty are still getting their feet wet in using these systems to enhance their teaching and the students’ learning. The University of Alabama has only 174 active WebCT courses, while there are thousands of traditional classroom courses. This means that no one can expect teaching methods in an online course to be as polished and established as those in the traditional classroom courses. Faculty need more time and experience to evolve into what may be a more comfortable, typical and beneficial use of online modules for each individual.

Conclusion

Regardless of the causes behind the gender difference, the results of this study do have implications for higher education in general and for web-based teaching and learning in particular. Gender influences almost all aspects of our lives to some degree. Teaching and learning is no different, nor is technology. To serve the interests of education, we must not only be aware of the issue of gender bias, but also take active steps to minimize this bias in all areas of education. In web-based teaching and learning, we, as educators, need to make sure we have a reason for what we do online. We need to know what our educational goals and objectives are and to choose modules or other tools that will help us achieve those goals in the most effective manner possible, in a manner that does not cater to gender bias either real or perceived.

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Tables

Table 1: The progression of use and skill of the Internet, the Web and Email

This table synthesizes the progression of skills and knowledge in using the various technologies of males compared to females.

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