The Impact of Technology on Research

Examples are NCI and Intersect. Rather than each institution developing high performance computing facilities to manage peak demand, the shared facilities can be used when demand rises. While this is a very effective model in the sector, it is hard to imagine other sectors adopting it!

Cornucopia of online tools to support effective learning

CIOs everywhere are plagued by requests from their organization’s staff to use this or that app to support different aspects of the organization’s work. In higher education this is taken to a whole new level. There has been a boom in new online tools to support learning - polling tools, captioning tools, tools to support self-paced learning, tools to support group work and so on. Students bring their own technology on campus and have strong views about the applications they want to use. They are savvy and demanding consumers of technology.

In response, IT teams in universities have needed to develop the capability to prototype rapidly, while at the same time thinking about potential for scaling. One of the key lessons in this is the importance of spending adequate time at the start of a project in understanding the nub of the problem that is being solved. Design thinking approaches are proving useful here. The lessons are similar to those in other industries using agile approaches - don’t underestimate the amount of time required from both IT and colleagues across the institution when using agile approaches and maintain a strong focus on reviews along the way.

A right-sized approach to technical architecture is also essential for avoiding road-blocks, excessive complexity, and technology debt. There is frequently more than one tool that can be used to address a particular problem. Ensuring that the selected tool complies to the extent necessary with well articulated architectural principles and agreed application platforms is critical for future agility. In addition to learning technology, our universities also leverage specific technology for each discipline. For example, robotic “patients” are used in nursing education, VI/AI/MR are used in social sciences, design and engineering related disciplines, and 3D imaging machines of all varieties are used across disciplines.

Data, AI and IT security

Some IT trends are universal. Like our peers, higher education CIOs are grappling with how best to leverage and protect data. This is an area of increasing investment and CIO attention. One interesting use of data and artificial intelligence in higher education is to support student success. A number of universities use a range of approaches to analytics to identify students at risk of performing poorly and to tailor learning to individual requirements.

Universities have also been quick to embrace the concept the use of chat bots to enhance the student experience.

Leveraging technology investments

Universities have a strong focus on ensuring that the funds entrusted to them are used effectively. When it comes to technology that involves ensuring that all staff and students have the digital literacy skills required to enable them to leverage the technology available. As complexity continues to increase, digital literacy is becoming an increasingly important focus for many institutions. To maximize the competitive advantage from our technology investments, it is the collective digital capability of the entire organization that will make the difference.