Adaptive learning

The adaptive learning project will explore the use of artificial intelligence (AI)-powered adaptive learning technology and the value it could bring to vocational training in the human services sector.  Adaptive learning is the delivery of custom learning experiences that address the unique needs of an individual through just-in-time feedback, pathways, and resources powered by AI. This contrasts with the one-size-fits-all learning experience that is often provided with online content delivery.

During the second half of 2022, up to 100 entry level workers (or potential workers) undertaking the Entry into care skill set (or the associated units out of the Certificate III in Individual Support (CHC33015)) will complete their program via adaptive learning.

Swedish-based company Sana Labs will support the project by providing access to their adaptive learning technology platform.

The project will seek a national sample for participation and the Human Services Skills Organisation will work with registered training organisations (RTOs) across Australia to trial the technology.

Project timeframe

The project will run from June 2022 until June 2023, with educational delivery commencing in July 2022. All students will be required to complete their skill set by June 2023.

Once the project is finalised an outcomes report will be made available in the second quarter of 2023.

Skills focus for the trial

The adaptive learning project will focus on the Entry into care skill set (or the associated units out of the Certificate III in Individual Support).

About the technology

We have partnered with Swedish based company Sana Labs to run a pilot project based on their machine learning technology. The technology personalises the learning experience for individuals with AI-powered content recommendations and adaptive paths.

Technology capability:

• supports adaptive pre-assessments that fast-track information learners already know
• adapting of instruction after every interaction
• serving spaced repetition to improve long-term knowledge retention
• neural searching which allows students to ask questions in the same way they would ask a colleague
• ‘next-gen authoring’ to accelerate content creation with collaborative and AI-assisted authoring
• analytics allows for analysis down to question level, individual performance level and provides proactive intervention recommendations.

FREQUENTLY ASKED QUESTIONS

What are the benefits to the human services sector?

This trial will help us investigate how technology, in this instance artificial intelligence (AI)-powered adaptive learning technology, can add value to the sector.

This type of technology can help prioritise learning for individuals, and as the AI develops an understanding of the individual’s knowledge, educators can modify learning materials. One of the benefits of AI supported learning, is that it can sometimes reduce the time it takes for individuals to complete.

What are the benefits to students?

Undertaking learning supported by AI promises some unique benefits. Throughout a student’s course of study, the AI may adjust their learning journey, so that it is more personalised to their understanding of the topics being covered.  The AI completes analysis on assessment completion, which supports teachers to provide feedback to students faster. These students will be some of the first to undertake adaptive learning, and there is no additional cost to students to be part of the trial.

What are the benefits to registered training organisations?

RTOs who participate will be involved in an innovative, game-changing program that could help shape the vocational education and training and human services sectors.

Because the project is fully funded by the Human Services Skills Organisation, participation by registered training organisations is free, which means trialling a leading-edge technology at no cost.

RTOs will gain access to insights that will help them determine if using adaptive learning technology can become part of their student value proposition—in terms of whether it increases personalisation, improves the turn-around time of assessment feedback and more.