All aboard the AI train!
We’re closing in on two years since OpenAI released ChatGPT 3.5 to the world. Right off the back of COVID-19, commentators were pronouncing AI as the catalyst for either imminent doomsday or righteous deliverance. And while no one has totally figured this out—nor knows precisely where AI will take us—we have begun to settle back into a new normal.
On one hand, educational innovators like Khan Academy have implemented a truly impressive AI tutoring system for their free course content. On the other, teachers and professors are still figuring out how to motivate students to think and write for themselves amidst the luring temptation of free essay generators.
If you’re a higher education leader, you may be exploring how AI can help you reshape and run effective institutional operations. But you likely have more questions than answers. One of those questions might resemble the following:
If generative AI can do everything from psychoanalysing our personalities through to accelerating drug discovery, then why can’t I use it to streamline academic operations?
Data management is both the problem and the solution.
At AptoNow, we believe that machine learning and AI can become a major facilitator of smoother, more effective educational delivery. But there are roadblocks.
The biggest of these roadblocks is disconnected datasets and the lack of university IT system interoperability. How many times have we asked questions like:
Is there an API for that? Is there any way to consolidate all the systems we use? If all the data is just sitting there, why can’t we use it to generate quality insight?
Unfortunately (and as you’re probably aware), it’s just damn hard to address these concerns because universities — as the name implies — are their own tiny universes. The experts who design scheduling software aren’t the same as those who design the facilities management system. The payroll staff likely aren’t the folks with the sharpest insight on curriculum management, and vice versa.
But all the systems and expertise must still come together to make education happen! University timetabling stands out as a quintessential example of the need for broad orchestration across university departments, data systems, staff and students.
Timetabling is an ambitious target for automation but promises a step change in strategic operations.
When you start looking beyond the dates and times, you quickly realise how the academic timetable is perhaps the primary artefact of the educational delivery strategy of the institution. Building the timetable requires answers to questions as diverse as:
Pedagogically speaking, how well are classes matched to particular facilities, equipment and venue types?
Are students actually registering for what’s set out in the handbook?
Does the scheduling of classes across disciplines truly allow for student choice in recommended electives?
Do schedules allow for students to engage in part-time or full-time work?
Do academic staff have dedicated research time, and are university teaching, lab and collaborative-working spaces well utilised?
The academic timetable not only serves as a single source of truth to objectively answer every question above, but also it is created often by a single team who works in isolation on the actual allocation of classes to times to rooms.
The challenge that Timetabling teams often have, is how be a strategic partner to help answer these questions intelligently, rather than “just get a workable Timetable out the door”. At AptoNow, we believe that with better tools, Timetabling teams can play a critical strategic role in educational delivery and operational business outcomes.
A treasure map for better outcomes across educational delivery and resource use.
What tools would help Timetablers to play this more strategic role? At AptoNow, we’re building an Academic Scheduling Co-Pilot based on what clients have told us would make the biggest difference. Things like:
Assess your university’s current timetable build process and life cycle. Determine from where data is sourced and how it all gets married together.
Run a current state diagnostic to generate a balanced scorecard and objective measures on the outcomes of your educational delivery, space utilisation, staff workload and student experience.
Pinpoint common key constraints to optimising the timetable, and then lift those constraints through advanced analytics and automation.
Deploy AI scheduling tool to drastically shorten the timetable build process.
Use the AI tool to build multiple versions of the timetable and test strategic scenarios for improving student satisfaction, improving space utilisation, or testing alternatives for class delivery modes.
Each step of this journey produces significant value. It’s up to leaders decide where they currently sit and which step to take next. The real treasure at the end of the rainbow, however, is when you can successfully implement each step to then simulate what it would take to make real change, understand the magnitude of trade-offs and, be able to communicate them across stakeholder groups, and then significantly reduce the time to exact change. At AptoNow, we help higher education institutions to optimise their academic timetable with AI-driven data tools and enablement services. We are working with leading Australian institutions including Curtin University, the University of Western Australia and the University of Wollongong. Contact us today to explore how we can support your institution to realise your strategic objectives.
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