NZIEC 2017: Some reflections on a whirlwind trip to Auckland.
On the flight back to Australia, I got the opportunity to reflect a little on the New Zealand International Education Conference I had just attended in Auckland. Overall, a fun, though slightly tiring, slog across the Tasman. I got to meet a heap of new people in and around the conference and was lucky enough to be involved in two sessions.
On Tuesday, I spent 30 minutes talking to delegates about how to build the analytical mindset during my session called Getting started in the Data Game. Mostly, I was emphasising the base skills needed in analytics and how … Read the rest
The Data Game: Building Analytics Capability in International Education
[Originally published by IEAA’s Vista Magazine (Summer 2016/17) — I’d strongly recommend following them online and reading their publications if you’re interested in Australian international education!]
Embracing an analytic mindset and capitalising on the technologies in the era of big data are key to reaching Australia’s strategic international education goals, writes Darragh Murray.
A tale of prediction and teenage pregnancy
In 2012, journalist Charles Duhigg came across a fascinating story concerning the power of prediction and teenage pregnancy. Writing for the New York Times, Duhigg told how an irate man confronted the manager of a Target department store … Read the rest
Student mobility, international and the power of data
Too good not to share.
Rob Malaki, Director of AIM Overseas (an Australian company specialising in organising short-course programs for higher education students) has put together a very interesting blog on using data and analytics to empower and measure student mobility. It’s a well-written post praising the power of data for empowering good business decisions in the international student recruitment and mobility space.
Rob makes a very pertinent point about the relationship between data and student mobility:
… Read the rest
So where do student mobility teams start looking to answer the data collection/analysis question?
The starting point should be the following principle: measure