On gender issues in informatics – the next edition Mirjana Ivanović Department of Mathematics and Informatics, Faculty of Sciences University of Novi Sad.

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Presentation transcript:

On gender issues in informatics – the next edition Mirjana Ivanović Department of Mathematics and Informatics, Faculty of Sciences University of Novi Sad

Agenda 1.Basics 2.Related Work 3.Structure of the Survey 4.Most Interesting Findings 5.Conclusions 2/36

Basics Analysis of gender related influences for students of computer science in several countries of the west Balkan region was conducted. We offered a large survey with about 120 different options (within 33 questions) and interviewed about 350 students. 3/36

Basics Survey data was available for students from: –Serbia, –FYR of Macedonia, –Bosnia and Herzegovina, and –Albania. In short, our analysis shows: –more maturity within the female population –more vanity within male population. Yet in general, both genders are: –quite satisfied with their choice of profession, and –look into the bright future, by their opinion. 4/36

Preliminaries Previously, we published several papers on gender issues: –at SISY’08 (International Symposium on Intelligent Systems and Informatics) we researched general gender issues about our computer science students. –at CSEDU’09 (International Conference on Computer Supported Education) and in ITALICS e-journal (2010), (The Higher Education Academy, Information and Computer Sciences) we investigated results of the female population at DMI, and –in TOJDE (2010) (The Turkish Online Journal of Distance Education) we extended earlier research with the new generations and higher number of female students. 5/36

Preliminaries Some issues needed further exploration, some questions were still unanswered. For example: –There is an obvious and considerable lack of female students at west Balkan universities, particularly in the field of computer science. Why? –What are the reasons for inadequate involvement of women in IT industry and research in west Balkan region? 6/36

Preliminaries We involved students from various countries 7/36

Agenda 1.Basics 2.Related Work 3.Structure of the Survey 4.Most Interesting Findings 5.Conclusions 8/36

Related Work There is a huge inequality in numbers comparing female and male students, all over the world. For example: –In the 1980s, around 35% of applicants for CS degrees in UK were female, around 2000, percentage is close to 10%, still monotonically decreasing. –In USA, the situation is very similar – the percentage of bachelor’s degrees in CS for women is declining from 37.1% in 1983/84 to 26.7% in 1997/98. –In Italy, around 2000, only 15% of CS students are female, while the overall percentage of females enrolled at Universities is about 55%. 9/36

Related Work There is a huge inequality in numbers comparing female and male students, all over the world. For example: –Department of Mathematics and Informatics at the University of Novi Sad is following this depressing trend. –Just between years 2006 and 2010, the number of female students dropped from around 35%, to the mere 20%. –Unfortunately this trend is continued in the following years, also. 10/36

Related Work Two main reasons that are most often reported in literature for a decreasing number of women in computer science are: –negative stereotypes and –low confidence regarding the field. It is even claimed that –women often do not receive the same level of support as men for entering and persisting in the field, and that –“parents, friends and classmates seldom encourage women to choose and continue in the field of information technology”. 11/36

Agenda 1.Basics 2.Related Work 3.Structure of the Survey 4.Most Interesting Findings 5.Conclusions 12/36

Structure of the Survey Questionnaire consisted of more than 100 options dispersed over 33 questions, of either nominal scale questions (yes/no), or ordinal scale questions (1 to 5, Lickert scale). The questionnaire is divided into three main sections: –General data: average grade of study, grade for some characteristic courses, rating of the quality of studies on various points, rating of their skills on listed aspects of their studies … 13/36

Structure of the Survey "Motivation for enrollment”: questions about role models, influence of some listed factors on their enrollment into studies, opinion on the coverage of certain listed fields within studies, and so on; "Ambitions regarding future career”: job position they see themselves in after the completion of their studies, and ten years later, or opinion about the most promising fields of computer science… 14/36

Statistical Analysis For interpretation of gathered statistical data, we used the following methodology: –Data processing was performed using the open-source “R software environment”, appropriate for statistical computing and graphical presentation of results, –Also, the following non-parametric methodologies were applied: Nominal scale data was analyzed using Fisher exact test and Phi correlation coefficient; Lickert scale data was analyzed using Mann–Whitney–Wilcoxon test and Freemans Theta coefficient; For "yes/no" questions "Fourfold" graphic charts were used; For Lickert scale questions the standard bar-charts were used. –Emphasis was put on finding correlations between gender and some other questions. 15/36

Agenda 1.Basics 2.Related Work 3.Structure of the Survey 4.Most Interesting Findings 5.Conclusions 16/36

The Most Interesting Findings On some points, both genders have the same view: 17/36

The Most Interesting Findings … preparation for the future life, or job positions immediately after finishing their studies, also very similar: 18/36

Some opinions were not that similar On certain points, male students were pretty sure on themselves … on their knowledge, success in life and so on: –Do you think studies positively influence your intellectual development? Only about 2% of females say they didn't, More than 10% of males claim that! –Do you feel worried about your future career in the CS field? More than 45% of female say they are worried, Only about 30% of males say the same. 19/36

Some opinions were not that similar On certain points, male students show that they have difficulties to fit in: –Are you satisfied with the quality of communication with the faculty staff? More than 70% of females are satisfied with the communication, Yet only 55% males. –During your studies, have you felt as part of academic community? 85% of females felt as a part of an academic community, But only 70% males! 20/36

Some opinions were not that similar On certain points, male students are so different, it seems they are not satisfied with their studies: –Are you satisfied with the quality of mathematical courses during studies? Around 60% of females are satisfied with math courses, While only about 40% of males claim the same. –Or questions about "Please rate if you're satisfied with skills gained in each of the following aspects”: 21/36

Some opinions were not that similar Considering their future career, everyone is satisfied with the choice of profession (more than 95%), And everyone thinks CS is a good field for men (99%). About some other points, genders disagree: –“Is computer science a good field for women” : Answer was yes by 95% of females, And by 81% of males; –“Is there a lack of women in the field”: Answer was yes by 67% of females, And just 45% of males; 22/36

Some opinions were not that similar Now we come to the … insulting part? –“Are women better in computer science than men” : About half of female students (51%) say they are, Disappointing 8% of male thinks the same. –Why? What are the reasons for such opinion? 23/36

Why do they study? What were the reasons for their enrollment into the field of CS? –Low risk of unemployment? 74% of femaleOnly 62% male –Financial security? 59% of femaleJust 46% male –Potential high income? 59% of female51% male What then? –“Interest in computers” – says 90% of males! 24/36

Yet, some things are true all over West Balkans! 25/36

And opinions on the importance of certain topics also Pretty same: Fairly same: 26/36

What about their grades? CourseAverage grade females Average grade male Introduction to programming – I year course Data Structures and Algorithms – I year course Data bases – II year course Software Engineering – Final year course Mathematical Analysis – I year course Algebra – I year course Things change as they “grow up”! 27/36

What should be added to your studies? Also similar 28/36

And who were their role-models? We already mentioned that parents were not their role-models. Who was? Role-model% of females % of males Male teachers from previous schools – not too much31% Female teachers from previous schools – look at the difference! 39%26% Older male colleagues32% Older female colleagues25%21% 29/36

How do they rate others? Why is that? What do they think about knowledge of others? Rate the knowledge of:% of females vote GOOD % of males vote GOOD Male professors – relatively high graded by both gender 80%73% Female professors – huge difference, almost insulting! 75%55% Parents – with CS being a relatively young field, and with the degree of the development of west Balkan countries, this is something to be expected. 14% Older male colleagues – some vanity of males? 70%58% Older female colleagues – again the same (male chauvinist) consideration, as with some previous questions 60%37% 30/36

Back to “similar answers” Final group of questions was about their opinion on “future position in a society”. 31/36

Agenda 1.Basics 2.Related Work 3.Structure of the Survey 4.Most Interesting Findings 5.Conclusions 32/36

Conclusions So – why did we claimed that “males show vanity”? Let’s group some of the results for male students: –more than 10% of them thinks that studies did not positively influence their intellectual development; –much more than females, males are dissatisfied with mathematical and general courses, and communication with the faculty staff; –males rate the knowledge of their lecturers much lower than females specially female lecturers are graded lower; –males do not have anyone as a role-model especially females are low graded as a possible reasons for their studies; 33/36

Conclusions Males rate the knowledge of their colleagues drastically lower than females, Their grades of female colleagues are embarrassing: –only 37% male has positive opinion about female colleagues, –their opinion about their computing skills is even lower – only 12% positive. Males think that there is no lack of women in computer science, that stereotypes about women are justified, that women are not more careful than men in computer science, and specially are not better workers. 34/36

Conclusions Since for females we might claim pretty much the opposite considering the mentioned statements, we will not repeat them, but perhaps just sum it up to a few words – more mature. Or is it just another stereotype? 35/36

Thank you for attention 36/36