The Aurora Tech Award aims to support women founders. In Malaysia we face the same gap between the number of startups founded by women vs. those founded by men.

5%
80%

Currently, there is a gender gap between people who are building their career 
in technology in favour of  males.

76%
24%

Total

78%
22%

Male

75%
25%

Female

n=300 (Total)
Yes
No
Significantly higher/lower than opposite gender at 95% significance level: >M,F/<M,F

Reasons for choice of educational direction

Malaysian students choose their educational paths for pragmatic reasons rather than according to gender stereotypes. Moreover, women state that their choice of STEM subjects is not motivated by gender stereotypes.

However, it is possible that gender stereotypes still affect women's choice of educational direction. However, they don't follow these, but contradict them.

STEM subjects
n=126 (Total)
42%
  • STEM subjects are relevant to the
    career I plan to choose
    54%
  • For me STEM subjects are interesting
    48%
  • There was a lot of information about
    possible careers at school
    37%
  • I’m better in STEM subjects
    36%
  • In school teachers make STEM
    subjects appealing for me
    26%
  • STEM subjects are for everyone, there is
    no gender connection
    19%
    Top-3 reason of choice 
among women
  • I am okay with a primarily male environment
    6%
non-STEM subjects
n=173 (Total)
58%
  • I’m better in humanities or other
    subjects
    44%
  • There was a lack of information about
    possible STEM careers at school
    31%
  • STEM subjects are not relevant
    to the career I plan to choose
    24%
  • For me STEM subjects are not interesting
    20%
  • In school teachers didn’t make STEM
    subjects appealing for me
    20%
  • I didn’t want to be active
    in a male dominated environment
    5%
  • STEM subjects are for boys only,
    
there is no place for women
    3%
  • Girls studying IT experience bullying/
    special attention
    3%
option was shown only for women

Job offerings from companies

There is no statistically significant difference in job offerings between genders. Malaysian companies don’t prioritize men above women in the technology sector. Neither do Brazilian ones.

n=142 (Male)
Yes
78%
No
22%
n=158 (Female)
Yes
75%
No
25%
Significantly higher/lower than opposite gender at 95% significance level: >M,F/<M,F

Information channels about tech careers

Most information is found through active search. Meanwhile, government institutions and channels are the bottom 3 sources of information about STEM careers.

Information channels about tech careers

  • Publications

    45%
  • Social media

    39%
  • Professional websites

    34%
Details
  • Found information on professional
    websites
    45%
  • I conduct research
    
about STEM careers by myself
    39%
  • Found information
    
in online forums
    34%
  • Visited conferences
    
and got knowledge there
    33%
  • Saw information on social media
    32%
  • My friends/relatives worked
    
in STEM companies
    30%
  • I was told about it in school
    28%
  • Read publications
    28%
  • Official information
    
from the authorities
    28%
Significantly higher/lower than opposite gender at 95% significance level: >M,F/<M,F

Barriers for work in technology. Gender aspect

High pressure to meet deadlines affects women more than men.

TOTAL

  • The market is very competitive
    41%
  • High pressure to meet deadlines
    38%
  • Excessive competition for job opportunities
    35%
39%
32%
34%
43%
45%
35%
Details
  • There is big competition
    on the market
    41%
  • High pressure to meet deadlines
    38%
  • Excessive competition
    
for job opportunities
    35%
  • Lack of sufficient training
    opportunities
    35%
  • Difficulty keeping up with the latest
    technological advances
    34%
  • Fast-paced work environment
    33%
  • Limited opportunities
    
for career progression
    23%
  • Lack of job security
    21%
  • Difficulty building and maintaining
    customer relations
    20%
  • Unclear job roles and responsibilities
    19%
Significantly higher/lower than opposite gender at 95% significance level: >M,F/<M,F

Reasons to work in technology. Gender aspect

In general there is no statistically significant difference between males and females regarding their reasons for work in technology.

TOTAL

  • Attractive salary and benefits
    47%
  • Opportunity for career growth
    45%
  • Interest in technology and its possibilities
    44%
49%
42%
48%
45%
49%
40%
Details
  • Attractive salary and benefits
    47%
  • Opportunity for career growth
    45%
  • Interest in technology
    and its possibilities
    44%
  • Desire to work with an innovative
    and modern team
    43%
  • Access to the latest technology
    
and tools
    41%
  • Job stability
    40%
  • Personal interest
    40%
  • Desire to make a positive impact
    in the world
    35%
  • Strong sense of purpose
    32%
  • A challenge and the creative
    
freedom it offers
    30%
  • Possibility to work
    
from home or remotely
    28%
Significantly higher/lower than opposite gender at 95% significance level: >M,F/<M,F

Role models awareness

STEM workers are well aware of tech sector role models, especially female ones. Non-STEM workers, however, are less so, with over a third unaware of female role models.

  • STEM workers

    61%
    39%
  • non-STEM workers

    40%
    60%

Most common role models by gender

Male role models

  • Elon Musk
    26%
  • Bill Gates
    19%
  • Steve Jobs
    15%

Female role models

  • Ada Lovelace
    11%
  • Grace Hopper
    4%

Male role models

  • Elon Musk
    20%
  • Mark Zuckerberg
    15%
  • Steve Jobs
    13%

Female role models

  • Ada Lovelace
    12%
  • Marissa Mayer
    5%
  • Grace Hopper
    5%

Local names

STEM workers

  • Ahmad Rubi
  • Jensen Huang
  • Nikolas Kokkalis
  • Dato Rosyam Nor
  • Anwar Ibrahim
  • Mahathir Mohamad
  • Sheikh Muszaphar
  • Shukor
  • Sundai Pic Hai
  • Mohd Hassan Marican
  • Ir Abdul Rahman
  • Bahasa
  • Irfan Khairi
  • Sofyank
  • Syahmi Sazli
  • Vincent Tan
  • Jack Ma
  • Micheal Ang
  • Myisha Mohd Khairul
  • Quek Siu Rui
  • Qian Xuesen
  • Ricky Elson
  • Syed Moktar
  • Syed Muzzaffar
  • Belinda Parmar
  • Nancy Xu
  • Kate Kallot
  • Dato Seri Vida
  • Datuk Nicol David
  • Dorcas Muthoni
  • Dr Nur Adlyka Annuar
  • Dr Rebecca Wong
  • Dr Siti Hasmah
  • Fadhlina Sidek
  • Serena Nik-Zainal
  • Dr Hidayah
  • Feng Jue
  • Ayyalasomayajula Lalitha
  • Hu Hailan
  • Janna Nick
  • Lisa Su
  • Marina Mahathir
  • Meng Wanzhou
  • Mira Filzah
  • Dr Balqis
  • Dr Zed
  • Puan Maznah Awang
  • Puan Nur Laila
  • Rini Suqiantro
  • Sharala Axyrd
  • Chern Ein
  • Siti Farida
  • Soo Winci
  • Soumya Swaminathan
  • Nadiah Wan
  • Tian Demei
  • Tu Youyou
  • Wan Azizah
  • Zeti Aziz

non-STEM workers

  • Alif Satar
  • Dato Dr Sheikh Muszaphar
  • Dr Mazlan Abbas
  • Hassan Merican
  • Alif Satar
  • Azalina Oyhman
  • Dr Serina Ha
  • Melanie Perkins
  • Nora Danish
  • Zeti Akhtar Aziz
  • Nur Amalina Che Bakri