Gender issue in the ICT field

in higher education B. Divjak, V. Vidaček-Hainš & M. Ostroški

- Varaždin County- Faculty of Organization and Informatics Varaždin, University of Zagreb

VIIth Conference of the European Regions on Equal Opportunities

Timisoara (Timis, Romania), October 11-12, 2007

http://images.google.com/imgres?imgurl=http://www.dvorci.hr/slike/Clanci/Varazdinska03.jpg&imgrefurl=http://www.dvorci.hr/page.aspx%3FPageID%3D1117&h=331&w=440&sz=87&hl=en&start=2&um=1&tbnid=PidYAgBuXQw4RM:&tbnh=96&tbnw=127&prev=/images%3Fq%3Dvara%25C5%25BEdinska%2B%25C5%25BEupanija%26svnum%3D10%26um%3D1%26hl%3Den%26sa%3DN

Population aged 15 or more according to the level of education (%):

http://www.dzs.hr (Croatian Bureau of Statistics – 2001 Census)

Varaždin Countyhttp://www.dzs.hr (Croatian Bureau of Statistics – 2001 Census)

Croatian Employment Servicehttp://www.hzz.hr

Unemployment rate by gender

• July 2007: Only 4.2% of unemployed persons have a HE degree

• Most of them are aged over 50 (28.7 %)

Male

Female

Proportion of female full professorsSource: National Science Foundation (2003). In Beyond Bias and Barriers: Fulfilling the Potential of Women in

Academic Science and Engineering, pp 17. National Academy of Sciences, N.A. of Engineering and Institute of Medicine. National Academy Press, Washington D.C.

Percentage of female and male doctoral scientists (Computer Science)

Source: National Science Foundation (2003). In Beyond Bias and Barriers: Fulfilling the Potential of Women in Academic Science and Engineering, pp 171. National Academy of Sciences, N.A. of Engineering and Institute of

Medicine. National Academy Press, Washington D.C.

Legend: 1= percentage of female d.s. ; 2= percentage of male d.s.

0

10

20

30

40

50

60

70

80

90

1 2

With children

Married

Croatia: Doctors of science – technical sciences http://www.dzs.hr

Female students (20,3%)

Male students (79,8%)

Gender budgetinghttp://www.dfid.gov.uk/aboutdfid/organisation/pfma/pfma-gender-budget.pdf

• Tools and processes designed to facilitate a gender analysis in the formulation of government budgets and the allocation of resources

• European Women’s Lobby – more than 3000 women’s associations in Europe

Our research – the goals

• To define connections between the social and economic status and secondary education as pre-entry factors determining results achieved in higher education (HE)

• Information and Communications Technology (ICT)

Respondents

• N = 271 first-year students of Information Systems in the field of Organization and Computer Sciences

Male

Female

Part-time

Full-time

Measurement(Survey)

ResultsFull-time vs. part-time students:

0

0,5

1

1,5

2

2,5

3

3,5

4

4,5

Male

Female

Average number of learning hours per week

Legend: Y axis = average number of hours

● Full time students achieved better results

Male vs. Female students:

● Female students study 1.46 h more than male students; female students – more motivated to fulfill their tasks than male students (r= -0.217, p>0.05): Pearson correlation between gender and motivation

Results

• Statist. sign. variables:

• Not significant variables:

Size of residence

Availability of the Internet

Type of secondary school

(r=0.219, p>o.o5)

Gender differences(t=3,255; df=128;p>0.01)

Female students learn more

Very important: curriculum and pre-knowledge from secondary school

Full-time studentsvs. Part-time

(full-time learn more)

Conclusion

Pedagogical implications of the research:• The need to familiarize the students with the

aims and outcomes of courses • The redefined role of the teacher in ICT

supported learning environment • Meta-skills – “learning to learn” strategies

Prerequisites for teachers

1. Objective insight into students’ behavior

2. Adapting the learning strategies to students / teachers

3. Quality communication

Thank you!