Women dropouts in engineering and computer science

Transcription

1 Women dropouts in engineering and computer science Dipl.-Ing. Wibke Derboven Dr. phil. Andrea Wolffram Technical University Hamburg-Harburg The 3rd CHRISTINA CONFERENCE on Women s Studies and the 4th European Gender & ICT Symposium; March 8-10, 2007 GENDER, IMAGES AND GLOBAL CONTEXTS

2 Women dropouts in engineering and computer science Project management: Prof. Dr. Gabriele Winker Project implementation: Dr. phil. Andrea Wolffram Dipl.-Ing. Wibke Derboven Dipl.-Psych. Simone Tosana ( ) The project is funded by the German Federal Ministry of Education and Research (12/ /2007)

3 Overview Problems and research questions Framework of our study Provisional model of student dropout Findings: Types of student dropouts Conclusions

4 Problems and research questions Problems: Dropout rates at technical universities in Germany: more than 50 % and up to 80 % in certain degree courses Higher attrition rate of women than men at some technical universities. Many projects encourage young women into engineering, but only few projects support them during their studies. We recruit young women and then leave them alone in the gendered field of technology studies Research questions: Which are the main social practices in engineering studies that include or exclude students? What are the main conflicting experiences of withdrawers? What are the characteristics of the field that cause these conflicts?

5 Framework of the study Tp0007//99 Instruments and volume of data: Qualitative, episodic interviews at 10 technical universities in Germany Sample: 30 women, 10 men Questionnaire concerning attitudes to technology and achievement in exams Data interpretation: Single case analysis Case synopses Key sentence method

6 Provisional model of student dropouts Tp0007//99

7 Findings: Types of student dropouts Tp0007//99 1. Type: don t know how to study Mismatch in the study logic: Learning experiences vs. academic demands Key sentence: I don t know how to study, I passed my school exams without a major effort. Gender neutral 2. Type: don t know what I need the subject matter for Mismatch in the content of study: Intention to learn job-related contents of study vs. intention to impart general basics Key sentence: I had a clear occupational goal. I knew exactly what I wanted to learn at the university. Mostly men 3. Type: don t know how put my grades into relation 4. Type: don t know how to understand 5. Type: don t know how to get integrated

8 Type: don t know how put my grades into relation Mismatch in the assessment logic: assessment by standards of learning objective vs. assessment by rates of selection Key sentence: I always suffer from my average performance Mostly women Personal characteristic at the beginning: Type of performance Used to be under the best at school Type of attitude to technology Varying (regarding experience, interest) Confidence: Due to school performance Intention To get a good job Central dropout reasons: Can t bear poor grades Can t develop job-related selfconfidence

9 Type: don t know how to understand Mismatch in the subject matter of study: intention to comprehend technology vs. intention of training skills, e.g. applying formula Key sentence: You only hear the backgrounds to things you don t even know. Mostly women Personal characteristics at the beginning: Type of performance High performance Type of attitude to technology Beginners: low technical experience, high interest in technology Confidence Due to high school performances Intention Deep understanding of technology Central dropout reasons: Can t bear that they don t understand the things they have to learn Can t develop job-related selfconfidence

10 Type: don t know how to get integrated Tp0007//99 Mismatch in identity: Own identity vs. mainstream identity Key sentence: I looked totally different to the other women; they all looked a bit like the guys. Mostly women Personal characteristics at the beginning: Type of performance Average performance Type of attitude to technology Beginners: low technical experience, some interest in technology Confidence Due to general confidence in her own performance abilities Intention Have heard really positive things about engineering degrees from female friends (in Italy and Greece) To have fun in the engineering degree with regard to her own learning and with the other students Central dropout reasons: Socially excluded No academic support through the other students Low performance in courses with high mathematics requirements

11 Conclusions Tp0007//99 Field characteristics that influence the decision to dropout: The Grundstudium (semster 1 to 4) is a stage of selection. Type: don t know how put my grades into relation Previous knowledge is implicitly demanded without being stated explicitly in the information about the engineering degree. Type: don t know how to understand Temporal separation of basic knowledge (Grundstudium) and applicationorientated knowledge (Hauptstudium = second stage study) In the Grundstudium students find an extremely one-sided learning environment: the main activity of the students consists of calculating (solving mathematical tasks). The students mostly do not identify the technology-related problems behind the task. Type: don t know how to understand Type: don t know how to study The students are reliant on mutual academic support through their fellow students. Type: don t know how to get integrated

12 Contact: Dr. Andrea Wolffram, Dipl.-Ing. Wibke Derboven Hamburg University of Technology