#ThinkUHI #BalanceforBetter look at enablers/drivers for the use of Learning Technology (#femedtech)

Today I’m joining Maren Deepwell in talking at the University of the Highland and Islands (UHI) for their #BalanceforBetter event organised as part of International Womens Day. As part of our talk I was asked to speak about equality as a challenge for Learning Technology professionals. As part if this I thought I would revisit responses to the 5 years of the ALT Annual Survey results. At the back of my mind when doing this was a recent interview I read with Caroline Criado Perez journalist and author of ‘Invisible Women: Data Bias in a World Designed for Men’. In this book Caroline highlights “how women are harmed because everything from crash-test dummies to voice technologies are modeled and trained on men”.
I like to think ALT has a very diverse membership and while we don’t collect demographics like gender of our membership for our Annual Surveys we do and the responses have been fairly balanced for all the surveys since 2014:

ALT Annual Survey Response breakdown

One of the questions we’ve asked for all the surveys since 2014 is for respondents to indicate which areas they think are important to enabler/driver the use of Learning Technology. One of the ways we interpret this data is to aggregate and rank the responses allowing us to see changes over time:

Ranked historic enablers/drivers for use of Learning Technology

Using gender as an additional dimension to this analysis provides some evidence of different priorities for men and women. Looking at responses to the 2018 survey (203 respondents) it’s interesting to see differences in the ranked importance for women for dedicated time and recognition for career development.

Comparison of ranking for male/female responses

As part of the ALT Annual Surveys we also include a free text response for the respondent’s job title. Looking at occurences of the terms of ‘Senior’, ‘Head’ and ‘Director’ over the survey responses from 2014, while there is relative balance between those with directorships there are clear differences between ‘Senior’ and ‘Head’:

Senior, head and director job titles

I’m still reflecting on what we do with this data but I hope this post is beneficial in making the invisible more visible. If you’d like to look at the data yourself I’ve put this particular analysis in the ALT Repository which includes hi-res versions of the graphs, or you can view the slides from our talk. Look forward to any comments you have.