The learning analytics TEQSA expects from a private provider are modest in technology and demanding in use: data from the learning management system and the student management system, read early enough to identify a student at risk under Standard 1.3, aggregated into the course review that Standard 5.3 requires, and reported to the academic board in a form it can act on. The regulator does not ask for a data science unit. It asks whether the provider noticed, and what it did.
This article describes what that looks like at a provider with a few hundred students, where the data already exists and the question is whether anyone reads it. It draws on fifteen years of TEQSA registration and renewal work with private providers.
What do the Threshold Standards actually require?
Standard 1.3 of the Higher Education Standards Framework (Threshold Standards) 2021 requires that students at risk of unsatisfactory progress be identified and offered support in a timely way. Standard 5.3 requires regular review of courses and units, informed by data on student performance, attrition, completion and feedback, with the outcomes used to improve them. Standard 6.3 requires academic governance that monitors academic quality, and that means the academic board sees the data too.
None of those standards uses the phrase learning analytics, and no guidance note makes it compulsory, with the usual reminder that guidance notes are not Threshold Standards. But the standards are written in the present tense, and in 2026 the honest answer to whether a provider identifies, reviews and monitors almost always involves data the LMS and SMS already hold. A provider that says it identifies students at risk but cannot show how is claiming a process it does not have.
Early intervention: the learning analytics TEQSA assessors value most
The most valuable use is the simplest. Most learning management systems can report which students have not logged in, have not opened the week's material, have not submitted the first assessment or are falling behind their cohort on engagement. Read weekly from the third week of term, that report identifies most of the students who will fail or withdraw before they have decided to.
The intervention then has to be real and recorded: a message from the unit coordinator, a call from student support, an offer of a study plan, and a note in the student's file that it happened. In my experience the evidence TEQSA asks for at renewal is precisely that trail, together with aggregate data showing whether contacted students progressed at a better rate than the cohort. A provider that can produce it has met Standard 1.3 in operation. A provider with a support policy and no trail has met it on paper.
Course review: turning the SMS into evidence under Standard 5.3
The student management system holds the numbers that course review needs: enrolments, attrition by unit and by cohort, grade distributions, progression rates, time to completion. Combined with student feedback, that data is the basis of a review that says something.
The discipline is to report the same measures for every unit on the same cycle, so that outliers are visible. A unit with a fail rate twice the course average, or where the online cohort withdraws at three times the on-campus rate, is a finding that leads to action, and it only appears when the data is presented consistently. Our guide to designing a continuous improvement framework for course reviews describes how to build that cycle so that a completed loop exists before renewal.
Reporting to the academic board in a form it can use
The academic board is where analytics becomes governance. Assessors read board papers to see whether it received data at all and, if so, whether it did anything. A dashboard tabled without discussion is not monitoring. A one-page report that names three units of concern, states what has been done and asks the board to endorse further action is.
In my experience the effective format is short, comparative and repeated: the same measures each meeting, trends over time, the outliers flagged, and a record of what the board decided last time and whether it worked. That record is also the raw material for the self-assurance report at renewal. The institutional research function that produces it is discussed in our article on institutional research and TEQSA reporting requirements.
Privacy and proportionality
Analytics involves personal information, and a private provider handling it is bound by the Privacy Act 1988 and the Australian Privacy Principles, which require that personal information be used for the purpose it was collected for or a reasonably expected related purpose. Using engagement data to support students is plainly related to the purpose of enrolment. Sharing it with third parties or profiling students for marketing is not, and Standard 7.3 on information management adds its own requirements about security.
Proportionality is the other test. A provider of three hundred students does not need predictive modelling, and an assessor is more impressed by a weekly engagement report that is acted on than by a platform nobody looks at. In my experience the right scale is the smallest set of measures that lets the provider identify students early, review courses honestly and give the academic board something to decide.
What I tell providers about analytics
Use the data you already have, read it early, act on what it shows, and record that you did, because the learning analytics TEQSA values are the ones that led somewhere. Report the same measures to the academic board every time so trends and outliers are visible. Handle the personal information as if a student would read your file note. Do that for two years and you have the completed review cycle TEQSA looks for at renewal, built from systems you were already paying for.
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— including the analytics and review measures that map to Standards 1.3, 5.3 and 6.3, drawn from our TEQSA registration and renewal work with private providers. Get the template
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Frequently asked questions
Does TEQSA require learning analytics?
Not by name. The Threshold Standards require providers to identify students at risk, review courses using performance data and monitor academic quality through the academic board, and in practice that means using the data the LMS and SMS already hold.
What data should a small provider track?
Weekly LMS engagement and submission data for early intervention, and unit-level enrolments, attrition, grade distributions and progression from the student management system for course review, reported consistently on the same cycle.
How should analytics be reported to the academic board?
As a short, comparative report using the same measures each meeting, flagging outliers, recording what was decided previously and whether it worked, so that the board can act and the minutes show it did.
Are there privacy limits on using student data for analytics?
Yes. The Privacy Act 1988 and the Australian Privacy Principles limit use to the purpose of collection or reasonably expected related purposes. Supporting students' progress is related; profiling or sharing data for marketing is not.
Dr Brendan Moloney is CEO of Darlo Higher Education, Australia's largest specialist TEQSA consultancy. He holds a PhD from the University of Melbourne, is a Cambridge University Press author on governance in higher education, and has advised private providers on registration and course accreditation for more than fifteen years.