AI & LLMs Teaching & Education

My gut tells me that we need to rethink assessment from top to bottom, but that nearly all colleges lack the resources to do this.

Otherwise I think we’re in serious trouble. It’s possible that no combination of these practices will significantly dent the AI-enabled cheating problem, which will mean more students will fail to learn, which in turn depresses the value of post-secondary education.

Aside from those messages, documents also revealed that the company took steps so that its infrastructure wasn’t used in these downloading and seeding operations so that the activity wouldn’t be traced back to Meta. The court documents say that this constitutes evidence of Meta’s unlawful activity, which seems like it’s taking deliberate steps to circumvent copyright laws.

Generative AI is the canary in the coal mine for teacher preparation. It is revealing, in real-time, the ways in which higher education’s slow-moving shifts in programs and policies are failing to keep up with the world their graduates will enter.

Teachers urgently need help shifting their mindset on AI, moving from reflexive fear and resistance to curiosity and hands-on engagement with the technology.

Many still see AI primarily as a tool for cheating rather than as a transformative force in education.

AI literacy is quickly becoming as fundamental as reading and math, yet higher education is nowhere near ready to meet this challenge.

assist in completing administrative tasks or generating individualized assignments for students.

Text-generating A.I. programs are the sworn enemy of that lectio difficilior potior principle—and thereby of human complexity itself. What those programs essentially do is choose, with merely probabilistic variations, the words that most often follow the preceding words in the giant tangle of documents used to train the program. Let the bullshit fall where it may. And there it stays, getting stinkier, because increasingly the documents those programs are being trained on were written by other such programs.

This helps explain the current landscape of responses: those mourning the loss of established ways, the evangelists who want to overlay AI on existing systems whilst leaving them essentially unchanged, and those who see potential for radical transformation of what education, schools, and teaching might become.

Most importantly, will AI-enabled education serve genuine democratic transformation or simply make existing educational hierarchies more efficient and palatable?

They are political questions about power, access, and the purpose of education itself. This should grab the attention of every educator because rather than just being a technological problem, it is a political one that can be shaped by others if we let it.

Bibliography of British and Irish History

By fostering AI competency, we will equip our students with the foundational knowledge and skills necessary to adapt to and thrive in an increasingly digital society.  Early learning and exposure to AI concepts not only demystifies this powerful technology but also sparks curiosity and creativity, preparing students to become active and responsible participants in the workforce of the future and nurturing the next generation of American AI innovators to propel our Nation to new heights of scientific and economic achievement.

teaching K-12 students foundational AI literacy and critical thinking skills.

This utterance is a reminder of the ongoing threat U.S. educators face. OpenAI is the most prominent of many EdTech enterprises, most owned by venture capital and private equity, whose mission is to automate and gigify education, to surveil students, mine their data and modify their behavior. And legacy publications like the Times have made it abundantly clear that they are only too happy to provide cover for these “disruptors.”

What the Times profile obscures is that these companies plan to make American schools the site where reactionary policy-makers like Stephen Miller and Christopher Rufo can find common cause with the technolords of Silicon Valley who threw their wealth behind the MAGA movement last year.

The technofeudal capture of core scholastic infrastructure depends on retaining the emphasis on transactional education which emerged under neoliberalism. Certification, assessment, accreditation, and many other buzzwords were popularized by administrators and politicians to justify the rising tuition rates that resulted from Reaganomic defunding of public schools and state colleges. When college was cheap, students cared less about how they were graded and grades were less inflated.

We lose abilities whenever we farm out tasks to other people or machines. Because our brains have limited real estate, they actively lose facts and skills we no longer use, to make room for new facts and skills.

When AI frees up all the neurons that currently are busy at finding the right adjective or trope,

The primary question for educators is: What can and should education achieve for humans? Essays may or may not be part of the answer. Further, the challenges of evaluating student work when AI is available should not obscure the question.

But the product leaves invisible the tangled lines of inquiry, the false but interesting starts, the productive, beautiful chaos of thinking and writing made of things that at one point seemed relevant but turned out not to be. Those things are a mix of sand and gold. Amidst this chaos is epistemic progress.

Finally, when we outsource the task of finding words to express things, we lose all the kinds of mental activation that come from those searches. Words and ideas are laden with associations, reminders, emotional charges — a whole forest of connections to our past and future tasks, ideas, and relationships.

They lose whatever it is writing essays is meant to teach.

Some of the relevant cognitive science to draw on is related to active versus passive learning. Active learning — generating content yourself — helps retention

generating content yourself

This is where I think it’s ultimately about the student’s learning goals when writing an essay. We as professors can communicate what we hope they get out of the writing process, and what we think would count as success. But, as with any assignment, the student can engage more or less actively with that process. AI may make it easier or more tempting to be passive learners, but I do think AI can equally make us more efficient active learners as well.

When students let AI do the thinking for them, they miss out on learning how to think better. What these students lose today is what past students lost by enlisting a friend, parent, or hired gun to do the work.

Even if the economic demand for human cognitive labor is dramatically diminished, we still want wise humans in charge.

This requires that at least some humans — and ideally all humans — maintain the intellectual skills needed to envision and realize a good future. In the decades to come, the need for clear thinking may be less technocratic and more democratic.

The objective of writing is not just the product but also the process. Students who exclusively use AI to write their essays lose the process of thinking. And that is, after all, what we’re trying to do: produce new knowledge. If the goal is thinking or producing new knowledge, then a human being is the only one who can do that.

Writing leads to thinking; it’s not an end product, it’s a process that stimulates thought.

We argue for developing students’ capabilities to identify and calibrate quality of work – uniquely human capabilities at a time of technological acceleration – through existing formative assessment strategies. These approaches circumvent and interrupt students’ uncritical usage of generative AI. The relationship between evaluative judgement and generative AI is more than just the application of human judgement to machine outputs. We have a collective responsibility, as educators and learners, to ensure that humans do not relinquish their roles as arbiters of quality.