Higher Learning, Basic Skills

“If its object were scientific and philosophical discovery, I do not see why a University should have students.” (John Henry Newman, 1852)

In the coming years, I expect, the purpose of higher education will be a recurring topic of discussion among academics. What are students supposed to learn at university? How are they to be improved? What do we want them to become better at? The answer will have to take seriously the fact that we have the authority only to impart and certify knowledge, to arm them only with ideas and “the authority of right reason,” as Scotus Erigena put it. We may only teach and examine our students. Why should students submit to this authority? What do they gain from it? What does society gain from demanding it of them?

An alternative, after all, is fast coming into view. Students are learning to use artificial intelligence to “support their learning,” which, unfortunately, is often indistinguishable (sometimes to themselves and sometimes, it seems, even to their teachers) from avoiding the problem of learning altogether. I’ve pointed out before that when Bertrand Russell suggested that a “system of notation” could almost serve as a “live teacher,” and “a perfect notation would be a substitute for thought,” he was probably not imagining the “stochastic parotting” of large language models. But they certainly do seem capable of substituting for a great deal of the thinking we’ve traditionally demanded of our students. We seem to be on the verge of automating the very problem of knowledge. Our students have been given an epistemic workaround.

Now, I have served for about two decades as a writing coach at a major European business school and during that time I have developed what I think is a healthy, working epistemology. I don’t claim to have solved all the problems that philosophers have raised in regards to the nature of knowledge, but I have a confident grasp of what we mean, or should mean, when we say that we are “knowledgeable” people and are helping our students to become likewise “able”. As I never tire of telling them, to be knowledge-able is both to be able-to-know things and en-abled by that knowledge to do things they would not otherwise be capable of doing. Knowledge is a competence that is manifest in a performance. In what, then, does that performance consist? What should university students become increasingly better at doing? What does it mean to be able to “know something” for, let us say, “academic purposes”?

First, if you are knowledgeable about something you are able to make up your mind about it. Invoking the long tradition of Western epistemology, I usually characterize this competence as the ability to form a justified, true belief. Given a series of experiences or a set of materials, a knowledgeable person is able to reach a determination of what is going on and what it means. They can convert what William James (and, later, Thomas Kuhn) called “the bloomin’, buzzin’ confusion of experience” into sterner stuff: propositional attitudes about stable facts, and theories that arrange concepts into orderly frameworks. Obviously, even very knowledgeable people can be wrong about particular facts and this is why I have increasingly come to emphasize that knowledge isn’t so much being right about things as being able to change your mind about them in an orderly fashion. On the path “from stimulus to science,” as Quine puts it, “we are faced with the problem of error” at every step. Knowledgeable people face this problem, let’s say, squarely.

But forming a belief, no matter how true or justified, is not sufficient to be considered knowledgeable in an academic setting. You must not only know what you’re talking about, you must be able to talk about what you know. To know something at university is to be able to hold your own in a discussion about it with other knowledgeable people. For students, this should be understood as an ability to discuss topics raised in class with their fellow students. It is sometimes argued that “academic writing” lacks “relevance” for students because it doesn’t relate to their “lived experience” or “real life”. Against this, I have long tried to argue that the “academic situation” offers an entirely meaningful context for rhetorical engagement. The classroom is a microcosm of the discipline and the students are learning to address their peers and respect their criticism. In that sense, students are apprentice scholars.

But nor is that all there is to knowing things “for academic purposes”. Knowledgeable people are not just able to make up their minds and speak their minds; they are able to write it down. The test that I recommend is whether you are able to compose a coherent prose paragraph about something you know in under half an hour. More specifically, are you in an epistemic position to decide at the end of one day to write a paragraph a start of the next about something you knew was true last week? This is not just a good test of whether you actually know the thing you think is true, it is also a good skill to have in itself. It’s nice to know that you can write half a page about anything you know in half an hour. Doing it regularly should give you a certain confidence, not least that confidence which comes from regularly experiencing that you do, in fact, know things to be true.

It is this competence that I hope the university will continue to represent and this confidence (which is not without humility) that I hope we will continue to instill in our students. To that end, I never miss an opportunity to plead for a shift of focus in our assessments, from homework assignments back to on-site, off-line, invigilated written examination. A university student who has taken a course (or is in the middle of a term) should be able to answer a relevant 20-word question given 4 hours and 1000 words (with relevant accommodations for disability) in a way that can be easily graded by their teacher. The ability to write, say, five coherent prose paragraphs is a good proxy for whether the student is able to make up their mind on the subject they are studying, speak their mind, and (of course) write it down. I would certainly argue that the plain in-ability (that the exam conditions of course make, precisely, plain) to write such an essay should call into question their claim to be a “knowledgeable” person on the subject in question. Higher learning is manifest in such basic skills.

2 thoughts on “Higher Learning, Basic Skills

  1. Yup, only way to test reasoning and ability to craft an argument. The course content can be delivered by textbook or AI, and I am increasingly of the opinion that AI can be used to better deliver standard content in modalities suited to each learner, than one live lecturer can BUT the thinking, reasoning, argumentation skills – yet AI can partly be used to great effect there as well – but in-person, even one-to-one mediation, is far more effective.

    I taught a critical thinking course (also included cognitive heuristics & biases, cross-cultural psychology research on thinking and reasoning and introductory research methodology) to MBAs and used Toulmin’s Anatomy of an Argument to teach them how to not only think but structure an essay – frightening how post-grads, ostensible bright, were still so poor at crafting coherent essays.

    My current interest is in how to use AI to undertake Socratic Dialogue with a students – Claude.ai’s new Skills ability looks very promising in this regard and easy to create.

    Want to collaborate on something? I am no longer in academia but doing IT dev work and this interests me. I can do the IT bit, you have the students as guinea-pigs. 🙂 Maybe there is some interesting research project here – I am interested in developing some AI-enabled platform that enhances metacognitive skills in students.

    METACOGNITIVELY-AWARE AI LEARNING SYSTEMS.
    The Central Paradox: Educational AI tools demonstrate substantial performance gains but simultaneously risk undermining the metacognitive processes essential for deep learning and intellectual independence. Students produce better work with AI assistance but may develop dependency rather than capability, experiencing “cognitive debt” – long-term learning deficits masked by short-term performance improvements.
    Objective: Design and validate AI learning systems that actively promote metacognitive engagement through process constraints and scaffolding, capturing AI’s performance benefits while preventing cognitive debt and dependency formation. And then build the platform.

    1. Thanks for the comment. My view is that it’s not much of a “paradox”. A forklift “demonstrates substantial performance gains” qua lifting things and if workers leave all the lifting to machines they will suffer long-term muscle deficits. Eventually they become dependent on machines to lift things they could once lift themselves. This is acceptable in a modern warehouse operation because the management need not worry about the physical strength of the individual worker.

      The question is whether this analogy should lead us to accept AI in higher education. I like an analogy suggested by Umberto Eco. Using a book to learn things is like using a spoon to eat soup. Literacy (the ability of a human body to read and write texts) is simply the best learning platform we’ve got and, like the spoon, can’t really be improved upon as a basic form. Learning in any subject (and especially in higher education) simply expands your grammar and vocabulary (and may also improve your style if you work at it).

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