Artificial intelligence in education and learning

This is just a quick post as I’m reading up a bit on AI in education and was taken with the following quote from the Pearson Report Intelligence Unleashed:

The increasing range of data capture devices – such as biological data, voice recognition, and eye tracking – will enable AIEd systems to provide new

By Alejandro Zorrilal Cruz [Public domain], via Wikimedia Commons
types of evidence for currently difficult to assess skills. For example, a practice-based learning experience that incorporates elements of problem solving or collaboration might be assessed using a combination of data sources including voice recognition (to identify who is doing and saying what in a team activity) and eye tracking (to explore which learner is focusing on which learning resources at any particular moment in time).

Now this would totally change the options available for (on-campus) assessment of students including in the identification and recognition of generic transferable skills. But such an approach could also be used in recruitment in general (for assessment centres) as well as corporate learning and development (learning needs analysis, development centres etc..) and work practice improvements. However, this quote, while acknowledging such skills may be difficult to assess, appears to assume ‘we’ know what these skills look like and how they ought to be performed.

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