Paper – Beyond the binary definition of “Stupid” and “Smart” education: towards “Smupid” education? | Smart Learning Environments | Springer Nature Link

Source: Beyond the binary definition of “Stupid” and “Smart” education: towards “Smupid” education? | Smart Learning Environments | Springer Nature Link

Here’s a new editorial paper from an excellent team of researchers (and me), published in Smart Learning Environments. I was called in some way through the process because of my earlier work on stupid learning environments  that had already been cited in the text (and published in the same journal), not unrelated to the fact that most of the other authors knew me. A largely implicit central premise of the paper is that the opposite of “smart”, as it is commonly used to talk about education, is “not smart” rather than “stupid”. Smartness is a situated aspect of the system as a whole, as viewed from the perspective of whoever is perceiving it: everyone has a unique view on this. Smartness is essentially a measure of that system’s ability to adapt to changing needs and constraints. Stupidity is not the absence of smartness but, far worse, something that is positively harmful to learning (and, often enough, to teaching – the most stupid systems of all hurt everyone). We thus describe the “smupidity” of a system, seen from an individual’s perspective, on two axes, one (smartness) related to the degree of adaptability, the other (stupidity) relating to the extent to which it causes harm. We divide the area formed by these two dimensions into four sectors:

benign: unadaptive but none-the-less beneficial to learning (e.g. a well-written textbook)

inept: unadaptive and harmful to learning (e.g. use of high stakes high pressure assessments such as exams to drive compliance)

pernicious: capable of adaptation but the adaptation causes harm to learning (e.g. the use of an LLM to write or, perhaps controversially, to mark an essay)

wise: adaptable and beneficial to learning (e.g. personal assessment interviews to help learners achieve what they need or, perhaps controversially, challenging AI tutors)

As I hope the examples illustrate, the smartness can be in machines, but it can equally be in the people whose orchestration contributes to the system, including teachers, students and a potential cast of thousands. It is important to remember that technologies as they are enacted are almost always partly intracranial: there are things we have to do, ways we must participate, many of which demand intelligent choices to be made. In this sense, even the benign textbook referred to above may, in combination with a critical reader (along with all the other parts of the assembly like reading skills, decent light, lack of interruption, etc), have a fair amount of smartness, especially if it also supports an internal didactic dialogue. In this context, a book with more signposts to enable the reader to choose which parts to read with care, which to ignore, which to skim, etc, and that mindfully challenges the learner to engage in active construction of knowledge, is part of a wiser assembly than one that must be read from the beginning to end, regardless of interest, existing knowledge, or learning plan, and that makes no concession to teaching the learner. There’s a lot more in the paper than that – this was just the part that I found most interesting and that sparked some really useful conversations. My co-authors are truly brilliant so this was a lot of fun to write. I may be a little biased, but I recommend it!

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