The Future Is Here – AI Bots & Student Analytics

The video above is a recording of the presentation Tim Davidson from the Auckland University of Technology delivered at the Intergen Convergence 2017 conference. I had the pleasure of meeting Tim earlier in 2017 and seeing some of the work he described in the video above and was suitably impressed both by what they had already accomplished and by the ambitious vision he had for future developments. Tim works in the Strategy and Planning Team at AUT as the Manager of Business Intelligence, Strategy


The Kauri Tree of learning at AUT

and Planning. When I chatted with him he explained this was very freeing as it allowed the team to be “ultra agile” rather than being bound by the usual governance and regulatory precautions common in traditional ICT teams. When they came up with a good idea, they could explore it immediately, and he echoes this development cycle towards the end of the video (see below for some indexed reference points).

There is an introduction to the presentation by Steve Scarborough (GM of Dynamics Solutions at Intergen) and then he hands over to Tim to deliver some live examples of the systems at work. The slides are as follows:

Indexed Shortcuts In The Video:

If you don’t have time to watch the full video, I have referenced a few key areas that I encourage you to skip to:


  • Tim explains the BI journey at AUT and how the Deputy Vice-Chancellor at the time was looking to explore any correlations between student success and student satisfaction.
  • The benefits of being in Strategy and Planning and not the ICT Department.
  • The use of Bots and Artificial Intelligence (AI) at AUT – a live demonstration showing there are now multiple layers of bots e.g. one that works out the intent of the user’s question and then pass off the query to another bot.
  • Learning Analytics at AUT – Tim demonstrates some of the features trying to predict students who may not be successful in their studies so early intervention can occur. This take standard data such as what high school they attended, what their NCEA results were like, when they applied/enrolled, but then mixes in live engagement data e.g. are they using library services? Do they log into the Learning Management System? They even combined network access data (wifi, printing, AD authentications etc) and then compared them to scheduled class times as a form of attendance record keeping.
  • Machine Learning – Tim explains “you don’t need to be a data scientist anymore to do Machine Learning” before giving some examples from AUT. He goes on to explain the importance of preparing your data cleanly in a data warehouse as this will simplify future interactions you have with the data.
  • Development Cycle “How We Do Stuff” – Tim concludes his session with a brief overview of how his team works based on five key pillars that whilst they sound familiar, definitely have some unique tweaks to them:
    • Vision
    • Strategy
    • Documentation
    • Speed
    • Selling & Sponsorship

Final Thoughts:

There is a lot to like about the work coming out of AUT in the area of AI, Bots, Big Data and Learning Analytics. The key is they’re storing as much data as possible, even if they do not have an immediate use for it. This enables them to quickly apply historical data sets to new models or reports they build without necessarily having to wait to generate the data.

Additionally, Tim’s team looks for the “low hanging fruit” – the easy wins to convince the leadership team that the data is important and can make a difference in the experiences and outcomes of students. Importantly, they look to share these stories quickly, enabling other faculties or staff members to be inspired about what they could also do with data.

Finally, they’re keeping across the very rapidly changing sector and release of tools and features. Admittedly, this is not easy to do and it is hard to balance the competing demands of delivering (and implementing) completed reports and tools versus up-skilling in the latest features and tools and Tim acknowledges this tension in his presentation.

For me, this presentation reinforces the clear direction of technology in education and how traditionally “back end” services like data and analytics are now front and centre in the life of students – even if they are only ever experiencing it first hand through a bot on FaceBook Messenger!


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