There’s always a buzz word, and it the world of education technology at the moment it is probably adaptive. But what does this mean, and how does an adaptive product differ from a product that personalises?
design or produce (something) to meet someone’s individual requirements.
We personalise things ourselves by making them individual to us. Most products in edtech that claim to be personalised do so through allowing choice: as well as choosing motivational features such as avatars (fairly standard these days) you may also make choices about the work that you do. Alternatively, tasks might be selected by a teacher or a parent, either in the app or website itself or remotely through a dashboard.
1. make (something) suitable for a new use or purpose; modify.
2. become adjusted to new conditions.
For an edtech product to adapt to a new purpose or new conditions, first it is necessary to assess or measure what those conditions are. Learning systems that are adaptive will incorporate three elements:
- data collection on existing progress
b. analysis of data, leading to
c. adaptations in the child’s work program.
Easiest here to use DoodleMaths as an example:
- aside from the initial assessment, the following data is collected for every child for every question answered: time taken, attempts taken, and date stamp.
b. this is then analysed to gain an understanding of both the child’s progress and also the population as a whole (as a basis for comparison)
c. the work program is adapted in three ways: level (on a general basis, are the questions too difficult, too hard, or just right for the child?); strengths and weaknesses (e.g. what are they finding difficult? Do we need to remediate here? – if yes, add it into the work program); pace of learning (e.g. if they found the last topic easy, let’s crack on, but if it’s tricky, let’s stick with it until they’ve mastered it).
There are other ways a program can adapt, too, for example, confidence level (some children are disheartened getting lots wrong, others can cope) or learning style (some children will exhibit more success with questions delivered in particular styles).
In the future, it will even be possible to adapt according to misconceptions: if a child consistently believes that a negative multiplied by a negative is a negative, for example, a really smart system will be able to detect this, adapt, and deliver the correct lesson to address this misconception.
So personalised and adaptive mean very different things: personalising is done by the user, usually at the start of using a product; adapting is done on an ongoing basis by the product itself. You might say that an adaptive product is aspiring to make decisions on an individual basis in a way that a good tutor might. Most edtech products have some kind of personalisation feature, but very few are truly adaptive.