AI Case Study
European Institute for Innovation – Technology, Germany
Artificial Intelligence (AI)
Artificial intelligence (AI) and machine learning in vocational education and training (VET)is expected to alter the environment as we know it. According to the Artificial Intelligence Market in the US Education Sector report as featured in Forbes Magazine in 2018, AI in U.S. education is expected to grow by 47.5% from 2017-2021 – and subsequently, the EU VET systems shall be altered also during this period. In this document, we explore some examples of what AI in an educational context and what it may look like.
At the moment, AI in education refers mainly to streamlining administrative services in colleges and universities, but as yet is not mainstream in the VET system. However, as AI technologies develop, AI in VET will allow for more individualised and accessible learning for all, evidence from its use in the higher educational sector is the driver for this, with many positive examples being reported.
One example of a European project that has explored the early stages of AI usage in education is iTalk2Learn, a 3 year collaborative European project (Nov 2012 – Oct 2015) with the aim of developing an open-source intelligent tutoring platform that supports learning for mathematics students aged 5 to 11. The goal of the project was to pool expertise from machine learning, user modelling, intelligent tutoring systems, natural language processing, educational psychology and mathematics education to create an efficient and effective application of AI in education.
Companies such as Content Technologies and Carnegie Learning develop intelligent instruction design and digital platforms that utilise AI/machine learning to better identify gaps in knowledge and allow teaching and learning materials to be adapted accordingly. As AI becomes more advanced, these programmes may be able to allow the machine to read students’ facial expressions indicating they are struggling to understand, and then will adjust a lesson in response to learners reactions. AI can also provide on the spot translation services (e.g. Presentation Translator, a free plug-in for Microsoft PowerPoint) allowing for increased accessibility of learning resources on all levels of education from across the globe, this is of particular relevance for learning on Erasmus mobility programmes.
AI allows for more individualised, effective learning that will save time and resources of both learners and their teachers. This is especially important in the context of VET, where additional needs can be met for learners.
Further, the iTalk2Learn project in addition to other learning platforms utilising AI provided feasibility research on and flexible and scalable infrastructure for the elements of the AI learning platform, in which the elements can be exchanged independently of each other and replaced by other elements in the future.
It is important to research and choose a technology that is scalable and adaptive meeting the needs of a specific VET provision. Other learnings from the European iTalk2Learn project can be found in the publications here: Of course there are financial decisions to be made in the purchase of AI applications, some of the more bespoke applications can be expensive. However, as the technology mature and scale has been built costs shall reduce by market forces.
Formative evaluation strategies: https://www.italk2learn.com/about/evaluation-overview/