Figure 1: Good mathematics ability is needed
| Australian Journal of Educational Technology 2002, 18(3), 341-358. |
AJET 18 |
Is mathematics anxiety contributing to the declining numbers of females enrolling in tertiary computing courses? Initial observation of enrolments in tertiary computing courses at an Australian university suggests a direct correlation between the number of females in a course and the prerequisite level of mathematics required at entry. A study involving over 550 female students in Australia and Singapore was undertaken to determine student perceptions of the importance of mathematics to computing and information technology degrees. All of the students were either studying a computing subject at secondary school or university and some were already enrolled in a computing degree. Results indicate that students studying computing at tertiary level in both countries believe that computing courses require good mathematical ability, while secondary school students express high levels of uncertainty when asked the same question. The majority of students surveyed believe that females and males are equal in mathematical ability, while thirty percent of the cohort from Singapore believes that males are more able than females in mathematical ability. This paper uses these responses, combined with observation and statistical data, to posit that females perceive a strong link between mathematical ability and success in computing courses. Consequently mathematics anxiety in females could be a contributing factor to their under-representation in tertiary computing courses. Computing and mathematics educators need to combine their efforts to encourage females into computing courses and dispel this anxiety.
If access to and control of technologies bestows power, women disenfranchise themselves by ignoring or rejecting technology (Spender, 1995, p.35).A closer investigation of the Monash enrolment statistics showed an apparent correlation between the level of difficulty of the mathematics prerequisite required for a computing course, and the percentage of females enrolled in that course. This study aims to evaluate how much the perception of computing being a technical discipline based on the prerequisite mathematical entry requirement influenced female students' course choices.
At the time of this study there were three mathematics courses available to final year (Year 12) students in the Victorian Certificate of Education (VCE). Firstly, Further Mathematics, considered a generalist course suitable for students contemplating employment or tertiary study without a strong mathematical component. This subject covered the areas of data sets, statistical concepts, arithmetic, algebra and some geometry used to solve routine problems. Secondly Mathematical Methods, the more advanced application intended to provide a good foundation for further study in science, economics or medicine and the norm for further study in computer science. Lastly Specialist Mathematics, aimed at serious mathematics students with strong ability in the area wishing to undertake further study in mathematics related disciplines. It was and still is the most complex mathematics subject available at secondary school.
| Name of course | % First Year on campus females in course | Mathematics prerequisite |
| Bachelor of Information Management | 48% | No mathematical prerequisite |
| Bachelor of Business Systems | 36% | Year 11 mathematics |
| Bachelor of Computing (Peninsula Campus) | 36% | Year 11 mathematics |
| Bachelor of Computing (Caulfield Campus) | 30% | Year 11 mathematics |
| Bachelor of Computing - Computer Science | 16% | Year 12 Mathematical Methods (Specialist Mathematics and physics recommended) |
| Bachelor of Computing (Gippsland Campus) | 10% | Year 12 mathematics (any) |
| Bachelor of Digital Systems | 7% | Year 12 Mathematical Methods (Specialist Mathematics and physics recommended) |
| Source: Monash University, Budget and Statistical Services | ||
The Bachelor of Digital Systems and the Bachelor of Computer Science both required Mathematical Methods as a prerequisite, with Specialist Mathematics and Physics recommended. Both courses had a very small percentage of female enrolments, 7% and 16% respectively (Table 1). At the other end of the scale, the Bachelor of Information Management has no mathematical requirement, and had the highest percentage of female enrolments (48%). As can be seen in Table 1, as the prerequisite level of mathematics increases, the number of females in each course decreased. Further emphasising this pattern is The Bachelor of Computing at the Gippsland Campus that required Year 12 mathematics as a prerequisite and had 10% female enrolment, while the same degree at Caulfield and Peninsula Campuses required year 11 mathematics and had 30% and 36% female enrolments, respectively. The Faculty had an overall female enrolment of 27%.
On an Australia wide scale, Department of Employment Training and Youth Affairs (DETYA) statistics presented in Table 2 indicate that computing courses that require the lowest level mathematics prerequisite attracted the largest number of female enrolments, and that the trend of females turning their back on this career path is increasing.
The classifications in Table 2 are those used when gathering data from all Australian universities. The pattern observed in the Monash enrolment is mirrored in the Australia wide statistics. The "harder" computing classified as computer science, which requires a higher mathematics for entrance, had the least number of full time female enrolments (decreased by 3% over 3 years). The more generalist "soft" courses (Information Systems and the last classification that includes Business Data Processing) had the highest percentage of female enrolments (also a decrease of 7% female enrolment over last 3 years). The national percentage of female international students in the computer science and information systems field of study in all Australian institutions was 44% in 1995, and 34% in 1999.
| DETYA classification | % full time females in courses | |
| 1996 | 1999 | |
| 9.02.01 Computer Science, Information Systems - General (not Business Data Processing) | 31.4% | 23% |
| 9.02.02 Computer Science | 22% | 19% |
| 9.02.03 Information Systems | 44% | 33% |
| 9.02.99 Computer Science, Information Systems - other | 44% | 34% |
| Source: DETYA, Data Services and Resources Branch (2001) | ||
We train girls in the component skills of a soft approach - negotiation, compromise, give and take - as psychological virtues, while dominant models of desirable male behaviour stress decisiveness and the imposition of wills (Turkle, 1995, p.56).Beall and Sternberg (1993) stated that gender is a socially constructed category that differs across cultures and quoted examples of these differences in several cultures. The gender schema of western society is portrayed as males being dominant and liking mathematics and science, while females are the passive members, not liking mathematics and science. When the gender schema was applied in tests and observers were asked to assign gender to behaviour, people interpreted any dominant behaviour as male (Beall & Sternberg, 1993, p.114).
Many of these researchers drew on the understanding that females have different learning styles from males and different preferred modes of instruction. Belenky, Clinchy, Goldberger and Tarule (1986) conducted a 5-year study in America interviewing 135 women and analysing the perspectives from which women view reality and draw conclusions about truth, knowledge and authority. The resulting descriptive phenomenon is referred to as five different ways of knowing. Belenky et al discussed the cultural conditioning of females and how that influenced their learning. They claim that many women do not move past the subjective state of knowing, and that those who do move on to believing knowledge as a construction, a state that most males attain, are inhibited by social expectations of female behaviour. Koertge (1995) disagreed with the claims made by Belenky et al, that the standard norms and methods of scientific inquiry are sexist because they are incompatible with women's ways of knowing, and argued that society must simply place more value on material thinking. She disputed the claims made by many feminist groups that logic is a tool of domination (Koertge, 1995, p.43).
Other research in the field draws attention to the increasing emergence of sex differences in the use of computer technology in education (Hawkins, 1985). As early as 1985, when PC labs were becoming common in most secondary schools, it was observed that because computers were assimilated to the category of science, mathematics and technology, the discipline of computer science was acquiring a gender differentiated interest associated with these fields. A survey of over 17,000 American students (Fetler, 1985) found that boys outscored girls in all areas of computer literacy. In this study, sixth and twelfth grade students were surveyed during the 1982-1983 school year and the analysis was organised under the headings of performance, attitude and experience. Boys outscored girls in every major area in performance, girls generally had a less positive attitude towards computers, and there was an overall pattern of lesser experience with computers both at school and at home for girls. It is acknowledged that this is old data for the computing discipline, but it shows a trend reaffirmed by a more recent Australian study (Australian Bureau of Statistics, 1999) that compared children's advanced computer skills by gender. In this study boys outscored girls in twelve out of the thirteen areas.
Koch (1994) referred to a "Women in Industry" program that involved female computing professionals visiting schools and talking to students in the 11-15 year old age groups. Some results from this program included the observation that the number of females in the computing club at one school increased from 5% to 53%, and the number of females enrolled in programming increased to 31% from zero in another school. Koch emphasised the importance of demonstrating that females can be competent scientists, mathematicians, engineers and computer scientists, to help overcome social stereotyping to both male and female students (Koch, 1994, p.7)
The general belief in the literature is that society encourages males to be inquisitive and technical minded to a greater extent than females. This influences the choices females make from a very early age and impacts on their desire to follow career paths that may be perceived to be of a technical nature, and since computing evolved from the mathematics and science area, it is seen to be technical. The aim of this study was to test the hypothesis that females perceive a strong link between mathematical ability and success in computing courses.
All first year female Monash computing and information technology students were surveyed either at the end of a core lecture or during a practical laboratory session. There were varying response rates, which could not be avoided due to the wholly voluntary nature of the survey. The total number of students surveyed was 168. The questionnaire was administered to 256 VCE students from regional secondary colleges, as well as students from two schools considered exemplary in their use of computers. All students were studying VCE Information Technology or had studied it in previous years. The questionnaire was administered to 133 students from three levels of educational institutions in Singapore, including two junior colleges (equivalent to senior secondary schools in Australia) and two polytechnics. The questionnaire was also administered to first year computing students at the National University of Singapore and to students from a private computing school that acts as an agent for Monash University and assists in the delivery of distance learning courses.
A small number of the students who had completed the questionnaire from each Monash campus and each of the courses agreed to meet for a group discussion session. These focus groups were used to augment the data from the questionnaire. A total of 19 current first year undergraduates took part in these focus group sessions. The Australian Computing Society (ACS) provided a list of females who were currently working in the information technology field. Four professionals were interviewed to determine if the perceived mathematical ability required in computing had changed over time. Their positions ranged from a self employed businesswoman to a public service professional. Very similar questions to those used in the questionnaire were used as a basis for these interviews.
This method of data collection provided both quantifiable statistical data and qualitative data. The surveys were distributed in early 1996 and the interviews were conducted later in the year.
| Monash % | Singapore % | Secondary % | |
| Prior computing knowledge | 29.8 | 24.3 | 50.0 |
| Logical thinking (mathematics ability) | 23.8 | 31.3 | 8.4 |
| Communication skills | 12.5 | 22.6 | 0.9 |
| Patience | 10.7 | 6.1 | 7.9 |
| Programming | 8.3 | 0.9 | |
| Interest | 2.4 | 7.8 | 4.7 |
| Cope with constant change | 1.8 | 3.5 | 3.3 |
| Keyboarding | 21.5 | ||
| Don't know | 2.3 | ||
| Creativity | 4.3 | ||
| No data | 10.7 |
Monash students most frequently mentioned "Prior computing knowledge" as the most important skill needed in computing courses (29.8%). The logical thinking responses were interpreted as referring to mathematical ability, and while this was not the first skill listed by the majority of Monash respondents, it was listed by 23.8% of the students as the second most frequently mentioned skill. It was the most important skill listed by the Singaporean students.
When the responses from the Monash students were cross tabulated with the courses the students were enrolled in, the biggest group who rated logical thinking as the most important skill were those students in non-computing degrees. These students were studying one computing subject as an elective, or as a minor stream in their degree in another discipline.
Some comments made in follow up interviews to the same question show that the ability to think logically is considered very important.
I think that it is just that you need to be able to understand the concepts involved and apply them. S1One third of the Singaporean students surveyed (31.3%) listed logical thinking as the most important skill required, prior knowledge was the next largest response (24.3%), followed by communication skills (22.6%). Some typical responses to this question were:You need to be logical. S2 non-computing students
For software development, the capability for logical clear thinking, being challenged by problems being excited by technology. P5 Self employed professional
I think you have to be able to think very logically, I think that competition is really going to arise, and I think that you need to be pretty assertive. In system analysis you need to be able to take things apart and look at them separately. S3 Bachelor of Computing
Logical thinking and understanding the limitations of computers. Singapore 9The results from secondary school students to the same question asking what is the most important skill needed for computing did not show that mathematics was a priority. The most common response was some sort of prior computing knowledge or experience earlier in their secondary education. Only 8.4% listed logical or analytical skills, which relate to mathematical ability, as being important.Technology aspect (knowledge of both the hardwares (sic) and software), good communication skills with others and good human management. Singapore 16
Analytical mind, good mathematical/programming knowledge and capability to produce what is requested. Singapore 21
Strong communications skill. Good programming background/skill and methodlogy (sic). Good time and stress management skill. Singapore 20
Be logical, determine what problem you have to solve. Secondary school 38These results show that the secondary school students do not have as strong a perception as the Monash students of the link between mathematical skills and computing.Typeing (sic), basic computer knowledge, logical thinking. Secondary school 39
Mathematical mind, logical thinking, understanding technology. Secondary school 52
Typing, good mathematics skills and you need a wide knowledge of technology. Secondary school 88
Two statements in section (ii) of the survey were used to ascertain perceptions about mathematics and computing. The responses to the statement, "Good mathematical ability is needed for success in computing degree courses" are shown in Figure 1 with 54.1% of the Monash students agreeing or strongly agreeing with this statement, and 20.8% disagreeing. The Singaporean students are even stronger in their affirmation with 67.7% agreeing or strongly agreeing. The majority of the secondary school students either disagree or are uncertain, and under one third agree with the statement.
Figure 1: Good mathematics ability is needed
In follow up interviews Monash students' comments show that views on the need for mathematics vary between courses.
I don't like mathematics so I would probably emphasise that there is not a lot of mathematics.(but I did do Methods in Year 12.) S3 Bachelor of ComputingThe deliberately provocative statement "Men are better at mathematics than women", resulted in 71.4% of the Monash respondents disagreeing or strongly disagreeing with the statement. Interestingly 32.4% of the Singaporean students believed that men are better at mathematics than women. Considering the age of the sample and the fact that a large percentage of the sample consisted of well-educated females, the high percentage of assent as well as the uncertainty is surprising (51.6%). The secondary school students are the firmest in opposition to the statement, with 86.7% of the sample either disagreeing or strongly disagreeing.Before coming they should have mathematics. We do need it. Most of the people did not do it in high school. You do need it. At least Further Mathematics, need a Year 12 Mathematics. S2 Bachelor of Business Systems
Figure 2: Men are better at mathematics than women
Some of the literature in the field disputes the belief that men are better at mathematics than women because of a better ability. A study completed in 1989 stated that they were only better because they had completed more mathematics in their schooling (Clarke & Teague, 1994 p. 259). This was also noticed by one of the students interviewed whose comments support the belief that it is a lack of exposure to certain forms of mathematics, rather than a lack of ability, that hinders the progress of females in computing.
Then you come and have to do data logic and some programming, like I came into this course and I didn't know what the hell programming was, like at all, and even data logic. And like I'm talking to my male friends, and I said, like, where did you learn this stuff? How come you already know this? And they say, oh we did it in Year 10, and a bit in Specialist Mathematics. S2 Bachelor of Computer ScienceWhile Specialist Mathematics is available to males and females, it does not have a good gender balance with only 35% of the total enrolment being female in 1996 and 36% in 2000 (Board of Studies, 2001).
I was from a co-ed school, yeah, I was actually, we had a small Physics class and I was the only girl out of 13 people, and in Specialist Mathematics as well, I was the only girl out of 26. S3 non-computing studentThe responses to the question "What mathematics subjects have you completed?" were classified into one year, two years, or more than two years. 61.9% of the respondents had completed two years of senior secondary mathematics or more, as indicated in Figure 3. Very few of the students surveyed had not completed any senior secondary mathematics.
Figure 3: Years of senior secondary school mathematics completed
Mathematics is considered an important subject and a prerequisite for many university courses and generally most students are counseled to keep it in their secondary school course for as long as their ability allows. The results shown in Figure 3 indicate that very few students do not complete any final year mathematics courses.
The critical focus of the ANOVA results are that the secondary school students surveyed are the least diverse in their opinions, when compared with the other two cohorts. Table 4 shows that the differences between each of the three samples on whether good mathematical ability is needed for success in computing degree courses is unlikely to have happened by chance (F(2,551) = 29.333, p<.001). The secondary school students have the highest mean (3.04) and the lowest standard deviation (.87), indicating that this group in general has a greater disagreement with the statement than the other two groups. The Singaporean students agree most with the statement (lowest mean 2.33) and the Monash group has the greatest spread in their responses (SD .95).
| Monash | Secondary School | Singaporean | ANOVA | |||||
| Mean | SD | Mean | SD | Mean | SD | F (2,551) | P | |
| Good mathematical ability is needed for success in computing degree courses | 2.58 | .95 | 3.04 | .87 | 2.33 | .92 | 29.553 | .001 |
| Men are better at mathematics than women | 3.96 | .93 | 4.32 | .81 | 3.20 | 1.12 | 62.747 | .001 |
The opinion that men are better at mathematics than women also shows significant differences (F(2,551)=62.747, p<.001). The responses to this statement once more show the secondary school students have the strongest disagreement (mean 4.32) with the statement and that their responses are the least spread (SD .81). The Singaporean cohort has the least strength of disagreement (mean 3.20), and the most spread in the responses (SD 1.12).
The responses to these statements could also be interpreted to be merely a reflection of the fact that males actually do study more mathematics than females in both Australia and Singapore, and the egalitarianism of the youngest cohort could be a support for their stronger disagreement with the statements.
The Post Hoc (Scheffe) analysis in Table 5 shows significant differences in the means of the Monash and secondary school groups, but not between the Monash and Singapore groups, in the responses to the statement that good mathematical ability is needed for success in computing degree courses. Both the Monash and Singaporean cohorts have studied more computing, and both groups agree with the statements indicating that their increased knowledge of the area should be taken into account. The secondary school students have a greater disagreement with the statement than either of the other two groups. They are the youngest cohort and also the group with the least computing experience, which could account for the difference in their responses.
| Dependent Variable | Groups (G1) | Groups (G2) | Mean Difference (G1 - G2) |
| Good mathematical ability is needed for success in computing degree courses | Monash | Sec.School Singapore | -.46* .25 |
| Sec.School | Monash Singapore | .46* .71* | |
| Singapore | Monash Sec. School | -.25 -.71* | |
| Men are better at mathematics than women | Monash | Sec.School Singapore | -.36* .76* |
| Sec.School | Monash Singapore |
.36* 1.12* | |
| Singapore | Monash Sec. School | -.76* -1.12* |
When expressing an opinion on whether men are better at mathematics than women, the Post Hoc (Scheffe) analysis shows significant differences in the means of all three groups. The secondary school students have a greater disagreement with the statement than the Monash students (-.36) and both the Monash and secondary school students have greater disagreement than the Singaporean students (Monash -.76, secondary school -1.12). As stated earlier, all the students surveyed had completed a substantial amount of mathematics at secondary level or higher (Figure 3).
To further elucidate the hypothesis that mathematics anxiety is a contributing factor to the low female enrolments in computing degree courses, one other question on the survey can be analysed. Students were asked to nominate the gender of their teachers in information technology and mathematics subjects. The results are shown in Figure 4. The column headed "Both" means that these students were taught by both genders at various times during their senior secondary education.
These results show that the Singaporean students have been exposed to teachers of both genders in computing to a much greater degree than the Monash students, and a slightly greater degree than the secondary school students. The gender of the mathematics teacher is more likely to be male in the secondary schools than in the other two groups. The higher exposure to female mathematics teachers with both the Singapore and Monash groups could indicate a positive three-way correlation between mathematics, gender of teachers and information technology.
Figure 4: Gender of IT and mathematics teachers
The survey and interview results presented support the proposition that, while computing and mathematics are closely aligned in most female minds, there is a difference in perception across culture and age regarding whether good mathematical ability is needed for success in computing. Secondary school students, the youngest cohort of the sample, are split almost equally between agreeing, disagreeing and being uncertain about the importance of mathematics for computing degrees (Figure 1).
The Singaporean students have been exposed to female mathematics and information technology teachers during their education to a greater degree than the Australian students, and a significantly greater percentage of them have undertaken computing degree courses. This may be ascribed to the effects of having female role models in both disciplines, and therefore having reduced mathematics anxiety, and a less gendered view of the computing career path.
There is a mathematics anxiety in females (Clarke & Teague, 1994; Grundy, 2000), whether it can be accounted for by a lesser exposure to mathematics than their male counterparts or not. The field of computing, which is strongly founded on constructed knowledge, is believed to be more suited to the male pattern of learning than the female (Turkle, 1995). While women's subjective way of knowing needs to be valued more by society, equality of mathematical exposure and erosion of the misconception that females cannot do mathematics also need to be addressed. The data presented show that there is a lack of female role models in both mathematics and computing in Victorian secondary schools, to a greater extent than in Singapore.
They need to be exposed to an equivalent amount of mathematics as their male counterparts, as well as exposed to female role models in mathematics and computing to a much greater extent than at present. Positive marketing about the benefits to females of a career path in computing would also help dispel the myth that it is a male occupation. If popular culture could also enhance this view, the gender enrolment imbalance may improve considerably, as was succinctly put in an anecdotal comment "If only Allie McBeal was a systems analyst and not a lawyer". Computing faculties have little influence on popular culture, but may benefit from looking closely at the type of mathematics prerequisite for their courses. An easing of the complexity of the mathematics prerequisite or the provision of bridging classes could result in more females enrolling in computing degrees.
The concern of the profession over the last 20 years is reflected by the number of studies investigating why females are not embracing computing to the same extent as males (Fetler 1985, Hawkins 1985, Lim 1990, Spertus 1991, Vinagradoff 1995, Margolis & Fisher 2002), and the formation of "Women in Computing" groups in Australia and around the world. Mathematics anxiety in females is a contributing factor to their under-representation in tertiary computing courses. Researchers in this field need to look wider than the computing discipline and combine with mathematics educators to encourage females into computing courses by working to dispel mathematics anxiety.
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| Author: Catherine Lang, School of Information Technology Swinburne University of Technology Email: clang@it.swin.edu.au http://www.it.swin.edu.au/staff/clang/ Please cite as: Lang, C. (2002). Tertiary computing course selection: The impact of mathematics anxiety on female decision making. Australian Journal of Educational Technology, 18(3), 341-358. http://www.ascilite.org.au/ajet/ajet18/lang.html |