By leveraging AI in vocational education, RTOs can enhance student engagement, improve learning outcomes, and better align their programs with industry needs, ultimately preparing students for successful careers. But there’s a catch. Who will be preparing the AI applications and how will they be administered by the RTO staff, and used effectively by the learners?
Firstly, let’s look at how it may be used in VocEd presently. Open AI’s ChatGPT came up with a few ideas of its own. They are:
- Personalised learning: AI can adapt and personalise learning materials and approaches based on individual student needs and preferences. It can analyse student performance, identify areas of improvement, and provide tailored recommendations or interventions.
- Virtual simulations and training: AI-powered virtual simulations can recreate real-world vocational scenarios, allowing students to practice and develop skills in a safe and controlled environment. AI can provide real-time feedback and guidance to enhance learning outcomes.
- Intelligent tutoring systems: AI can act as a virtual tutor, providing interactive and dynamic guidance to students. It can answer questions, explain concepts, and offer step-by-step instructions, helping students overcome difficulties and improve their understanding.
- Automated assessments and feedback: AI can automate the grading and assessment process, saving time for instructors and providing instant feedback to students. It can analyse answers, evaluate practical skills, and offer detailed feedback, enabling students to track their progress and identify areas for improvement.
- Career guidance and job matching: AI algorithms can analyse labour market data, industry trends, and individual skills to provide personalized career guidance to vocational students. It can suggest suitable job opportunities, highlight skill gaps, and recommend relevant training pathways to enhance employability.
- Predictive analytics: AI can analyse large amounts of educational data to identify patterns and trends. It can predict student performance, dropout rates, and employment outcomes, enabling educators to intervene early and provide targeted support to at-risk students.
- Adaptive curriculum development: AI can assist in designing and updating vocational curricula based on emerging industry needs and technological advancements. It can analyse industry trends, job requirements, and skill demands, ensuring that vocational programs align with the rapidly evolving job market.
Personally, I think all of these have a reasonable chance of being implemented in the not-too-distant future by a majority of RTOs who choose to do so.
An impressive TED presentation by Sal Khan, of the Khan Academy recently spoke of their efforts to address suggestions 3 and 4, by using ‘Khanmigo’ – a Socratic-based model that adapts ChapGPT’s responses to ask follow up questions rather than just give answers to students who wish to study or need tutoring in subjects like Maths and English.
My mind twisted and turned, thinking of this type of application in Australian VocEd circles. I’m truly excited to imagine that this will provide students with the next level of personalised learning (point 1) and feedback (Point 4). It’s just a matter of making the technology accessible, understandable and above all, affordable.
It’s no secret that RTO margins have been falling over the last decade as the cost of great teachers rises, the demand for cheaper qualifications persists. All underpinned by a more expensive economy (at least in 2023).
So it’s inevitable also, that RTOs with the means will look at AI alternatives to offer personalised support to students and even automate as many processes as practicable – whilst still sustaining quality student outcomes for the next generation of Australian workers.
What are your thoughts on the subject? You can email me at email@example.com or comment on the post or blog page. I’d love to know your opinion of the future.