An Oracle blog about Education and Research

  • May 22, 2019

When and how to adopt new technology (part 2)

David Ebert
Director – Public Sector, Education, Healthcare - Industry Solutions (EMEA)

For those that missed part 1, fear not, you can catch it here!

Okay, so assuming you have now caught-up, let’s crack-on with part 2. The focus of part 2 is on some of the innovative/emerging/transformational technologies available today, and how they can help education and research institutions.

Internet of Things (IoT)

IoT is certainly well established but the on-going potential and impact is still astounding. This year we will reach 50B smart connected devices, producing 8 zettabytes of data!

Facilities management is a very frequent immediate focus and rightly-so. It can be very beneficial in terms of utility savings, as well as increased comfort and security. Buildings and facilities that are monitored, automated and integrated using sensors and computer systems are becoming increasingly commonplace.

But don’t only focus on facilities management. Consider using it to improve the student experience with — person specific, location based — services, modelled on profiles and past behaviours.

  • Guiding first year students to lectures using beacons and their smart phones.
  • Sending alerts as they pass the bookstore, reminding them to buy their outstanding books today, offering a discount.
  • Encouraging healthy eating by immediately sending a digital coupon for free fruit, when they buy something unhealthy!

Conversational Interfaces

Conversational interfaces, such as chatbots and digital assistants, are fast replacing the most common interfaces on computers and connected devices, because the user experience is so much better. These computer programmes leverage artificial intelligence to enable natural conversations with people.

The most common first step to use chatbots is for frequently asked questions. Applicant — “When is the next university open day?”  Student — “When is the library open on Sunday?” Staff — “When is the sports centre least frequented by students?”

But the key differentiator is that they not only provide information but actually suggest and making transactional changes. So they can help students with class choices and then enrol them. They can help students pay fees and find the right type of Advisor. They can also help with a lot of administration by booking — rooms, parking, sports facilities — and resetting passwords.

Think about the savings in administration cost for each support call, plus providing a more efficient and better service. The University of Adelaide significantly improved their processes and service levels at a critical time of year for their applicants.


Artificial Intelligence (AI) and Machine Learning (ML)

Artificial intelligence might still be a scary term for some, but the fact is, AI is driving the very consumer experiences we are all use and really appreciate in our daily lives. Various consumer services would not be able to deliver the same experience and delight without AI and ML.

AI and ML use data-patterns to improve student enrolment, student outcomes and student success.

  • Student Enrolments: Improve the selection of students to courses by matching the right students to the right courses. Similar logic helps identify which candidates might be the best fit for a job.
  • Student Outcomes: Suggest specific learning paths for each student.
  • Student Success: Predict which students are at risk and intervene with an appropriate action, at the right time.

AI and ML can assist with automating routine tasks such as expense — entry, approval and fraud detection. Also inventory management can be automated – monitoring of stock levels, learning lead times and reordering.


These decentralised ledgers for keeping track of secure records are an example of technology advancing brand new business models. Trust models between individuals and organisations can be re-designed; with the individual truly owning the data.

The most common example generally is for payments and digital smart contracts. The most common use case in education and research is for authenticating learning records with digital competency indicators. I believe MIT was one of the first institutions to deliver digital diplomas via an app based on blockchain, to a pilot graduate cohort. Since then, many other institutions are developing the capability to do the same. For example New Mexico College and China Distance Education.  

However I think there is an even bigger case for using it in research — for securing publications and data sets. Similarly there is a place for it to track the provenance and use of materials.

Adopting these yet?

I wonder how far your institution has gone down the path of using these technologies. I expect you will be further along with some than others, but still probably nowhere near taking full advantage of the technologies available to you today. Don’t worry, that’s a fairly normal pattern and in part 3 — coming in a few weeks — I’ll cover some strategies to help you decide how and when to embrace innovative technologies. Until then, please follow the prompt below; I’d love your feedback, ideas and examples.

Join the discussion

Comments ( 1 )
  • Mr Dominic Watts Thursday, May 23, 2019
    Thanks David, once again some really good and easy to follow ideas. I'm seeing many instances of Conversational Interfaces and AI as completely separate initiatives with no common data model or strategy. This creates further internal complexity and fails to deliver a cohesive and sustainable strategy that can be built upon.
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