20 October 2021

Written by Zoe Guzman Martinez - Supervising Editor: Instructional Design

Imagine hiking up a mountain with a group of people, but each person takes a route that is suited to their unique needs and abilities. The aim is to meet on the summit at a certain time and have a picnic to celebrate the accomplishment: the goal is the same, but the journey that each individual takes, the amount of time spent walking, and the degree to which they need guidance will depend on their level of physical fitness and requirements. This is the premise upon which adaptive learning is based – that the outcomes of learning are what students have in common, but that the learning process should accommodate differences in students’ strengths and weaknesses and learning styles, and it should take into account prior learning.

Traditionally the focus of learning has been on “one-size fits-all delivery” rather than “reception” – with all students reaching the endpoint of a learning experience at very different levels of knowledge; however, this approach is changing, and learning is becoming more student-centred, with content being designed in a manner that prioritises how it will be received, and the needs of the receiver. The use of technology in learning has drastically increased the possibilities for adaptive learning, using algorithms and artificial intelligence in elearning to gather data from individual learners to customise their learning pathways. So, for example, if two learners do a course on the POPIA requirements, and one learner is an HR Manager and the other is a Legal Adviser, by the end of the course they would both have met all the learning outcomes of the course, but their journey would be completely different based on their different strengths and weaknesses and specialised areas of knowledge relating to the topic of the legalities of protecting personal information. Regular activities and questions would be embedded with algorithms to identify where they lack knowledge, and direct them towards this content for further practise. No time would be wasted on subject matter that they are already experts on.

Adaptive elearning tends to be better suited to microlearning, which would mostly be used in organisations for training purposes – for short courses with a very specific focus. In a corporate setting, where “time is money”, it is also a great way to save on working hours spent in training. Adaptive elearning isn’t necessarily a good fit for full qualifications in the context of higher education. However, it can be argued that the adaptive model is a consideration in processes like Required Prior Learning (RPL) and carrying credits from one course into another qualification, as learners will take different routes to attain the same degree. In essence, tertiary institutions are generally dealing with adult learners, and adaptive learning aligns with the principles of andragogy, which are that learners need content that takes into consideration what they already know, and learning applies to their context and specific needs.