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The open model of participation calls into question where value is created in the education system. Gutenberg created a means to duplicate content. The social web creates the opportunity for many-to-many interactions and to add a global social layer on content creation and knowledge growth.

Whatever can be easily duplicated cannot serve as the foundation for economic value. Integration and connectedness are economic value points.

In education, content can easily be produced (it’s important but has limited economic value). Lectures also have limited value (easy to record and to duplicate). Teaching – as done in most universities – can be duplicated. Learning, on the other hand, can’t be duplicated. Learning is personal, it has to occur one learner at a time. The support needed for learners to learn is a critical value point.

Learning, however, requires a human, social element: both peer-based and through interaction with subject area experts

Content is readily duplicated, reducing its value economically. It is still critical for learning – all fields have core elements that learners must master before they can advance (research in expertise supports this notion). - Teaching can be duplicated (lectures can be recorded, Elluminate or similar webconferencing system can bring people from around the world into a class). Assisting learners in the learning process, correcting misconceptions (see Private Universe), and providing social support and brokering introductions to other people and ideas in the discipline is critical. - Accreditation is a value statement – it is required when people don’t know each other. Content was the first area of focus in open education. Teaching (i.e. MOOCs) are the second. Accreditation will be next, but, before progress can be made, profile, identity, and peer-rating systems will need to improve dramatically. The underlying trust mechanism on which accreditation is based cannot yet be duplicated in open spaces (at least, it can’t be duplicated to such a degree that people who do not know each other will trust the mediating agent of open accreditation)

The skills that are privileged and rewarded in a MOOC are similar to those that are needed to be effective in communicating with others and interacting with information online (specifically, social media and information sources like journals, databases, videos, lectures, etc.). Creative skills are the most critical. Facilitators and learners need something to “point to”. When a participant creates an insightful blog post, a video, a concept map, or other resource/artifact it generally gets attention.

Intentional diversity – not necessarily a digital skill, but the ability to self-evaluate ones network and ensure diversity of ideologies is critical when information is fragmented and is at risk of being sorted by single perspectives/ideologies.

The volume of information is very disorienting in a MOOC. For example, in CCK08, the initial flow of postings in Moodle, three weekly live sessions, Daily newsletter, and weekly readings and assignments proved to be overwhelming for many participants. Stephen and I somewhat intentionally structured the course for this disorienting experience. Deciding who to follow, which course concepts are important, and how to form sub-networks and sub-systems to assist in sensemaking are required to respond to information abundance. The process of coping and wayfinding (ontology) is as much a lesson in the learning process as mastering the content (epistemology). Learners often find it difficult to let go of the urge to master all content, read all the comments and blog posts.

e. Learning is a social trust-based process.

Patience, tolerance, suspension of judgment, and openness to other cultures and ideas are required to form social connections and negotiating misunderstandings.

An effective digital citizenry needs the skills to participate in important conversations. The growth of digital content and social networks raises the need citizens to have the technical and conceptual skills to express their ideas and engage with others in those spaces. MOOCs are a first generation testing grounds for knowledge growth in a distributed, global, digital world. Their role in developing a digital citizenry is still unclear, but democratic societies require a populace with the skills to participate in growing a society’s knowledge. As such, MOOCs, or similar open transparent learning experiences that foster the development of citizens confidence engage and create collaboratively, are important for the future of society.

LLMs usually cannot do a good job of explaining how a particular passage from a longer text illuminates the whole of that longer text. Moreover, ChatGPT’s outputs on comparison and contrast are often superficial. Typically the system breaks down a task of logical comparison into bite-size pieces, conveys shallow information about each of those pieces, and then formulaically “compares” and “contrasts” in a noticeably superficial or repetitive way. 

In-class writing, whether digital or handwritten, may have downsides for students with anxiety and disabilities

ChatGPT can produce outputs that take the form of  “brainstorms,” outlines, and drafts. It can also provide commentary in the style of peer review or self-analysis. Nonetheless, students would need to coordinate multiple submissions of automated work in order to complete this type of assignment with a text generator.  

No one should present auto-generated writing as their own on the expectation that this deception is undiscoverable. 

LLMs often mimic the harmful prejudices, misconceptions, and biases found in data scraped from the internet

Show students examples of inaccuracy, bias, logical, and stylistic problems in automated outputs. We can build students’ cognitive abilities by modeling and encouraging this kind of critique. Given that social media and the internet are full of bogus accounts using synthetic text, alerting students to the intrinsic problems of such writing could be beneficial. (See the “ChatGPT/LLM Errors Tracker,” maintained by Gary Marcus and Ernest Davis.)

Since ChatGPT is good at grammar and syntax but suffers from formulaic, derivative, or inaccurate content, it seems like a poor foundation for building students’ skills and may circumvent their independent thinking.

Good journalism on language models is surprisingly hard to find since the technology is so new and the hype is ubiquitous. Here are a few reliable short pieces.     “ChatGPT Advice Academics Can Use Now” edited by Susan Dagostino, Inside Higher Ed, January 12, 2023  “University students recruit AI to write essays for them. Now what?” by Katyanna Quach, The Register, December 27, 2022  “How to spot AI-generated text” by Melissa Heikkilä, MIT Technology Review, December 19, 2022  The Road to AI We Can Trust, Substack by Gary Marcus, a cognitive scientist and AI researcher who writes frequently and lucidly about the topic. See also Gary Marcus and Ernest Davis, “GPT-3, Bloviator: OpenAI’s Language Generator Has No Idea What It’s Talking About” (2020).

“On the Dangers of Stochastic Parrots” by Emily M. Bender, Timnit Gebru, et al, FAccT ’21: Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, March 2021. Association for Computing Machinery, doi: 10.1145/3442188. A blog post summarizing and discussing the above essay derived from a Critical AI @ Rutgers workshop on the essay: summarizes key arguments, reprises discussion, and includes links to video-recorded presentations by digital humanist Katherine Bode (ANU) and computer scientist and NLP researcher Matthew Stone (Rutgers).

Generally these papers are just pumped-up versions of the five-paragraph essay, with filler added. Thesis-driven, argumentative, like the newspaper editorials the genre is based on, this "researched writing" promises to solve big questions with little effort: "Reproductive rights resolved in five pages!"

Actual writing related to research is modest, qualified, and hesitant

our actual model involves elaborately respectful conversation, demonstrating sensitivity to the most nuanced claims of previous researchers

Academic, legal, medical, and business writing has easily understandable conventions. We responsibly survey the existing literature, formally or informally creating an annotated bibliography. We write a review of the literature, identifying a "blank" spot ignored by other scholars, or a "bright" spot where we see conflicting evidence. We describe the nature of our research in terms of a contribution to the blank or bright spot in that conversation. We conclude by pointing to further questions.

Millions of pieces of research writing that aren’t essays usefully circulate in the profession through any number of sharing technologies, including presentations and posters; grant and experiment proposals; curated, arranged, translated, or visualized data; knowledgeable dialogue in online media with working professionals; independent journalism, arts reviews, and Wikipedia entries; documentary pitches, scripts and storyboards; and informative websites.

real researchers don’t write a word unless they have something to contribute. We should teach our students to do the same

This generation, the first not to have known life before the internet, has acquired a battery of skills in navigating digital environments, but it isn’t clear how well those skills line up with the ones traditionally accredited by universities.

From the perspective of students raised in a digital culture, the anti-plagiarism taboo no doubt seems to be just one more academic hang-up, a weird injunction to take perfectly adequate information, break it into pieces and refashion it. Students who pay for essays know what they are doing; others seem conscientious yet intimidated by secondary texts: presumably they won’t be able to improve on them, so why bother trying? For some years now, it’s been noticeable how many students arrive at university feeling that every interaction is a test they might fail. They are anxious. Writing seems fraught with risk, a highly complicated task that can be executed correctly or not.

Many students may like the flexibility recorded lectures give them, but the conversion of lectures into yet more digital ‘content’ further destabilises traditional conceptions of learning and writing

the evaluation forms which are now such a standard feature of campus life suggest that many students set a lot of store by the enthusiasm and care that are features of a good live lecture

the drift of universities towards a platform model, which makes it possible for students to pick up learning materials as and when it suits them. Until now, academics have resisted the push for ‘lecture capture’. It causes in-person attendance at lectures to fall dramatically, and it makes many lecturers feel like mediocre television presenters. Unions fear that extracting and storing teaching for posterity threatens lecturers’ job security and weakens the power of strikes. Thanks to Covid, this may already have happened.

In the utopia sold by the EdTech industry (the companies that provide platforms and software for online learning), pupils are guided and assessed continuously. When one task is completed correctly, the next begins, as in a computer game; meanwhile the platform providers are scraping and analysing data from the actions of millions of children. In this behaviourist set-up, teachers become more like coaches: they assist and motivate individual ‘learners’, but are no longer so important to the provision of education. And since it is no longer the sole responsibility of teachers or schools to deliver the curriculum, it becomes more centralised – the latest front in a forty-year battle to wrest control from the hands of teachers and local authorities.

an injunction against creative interpretation and writing, a deprivation that working-class children will feel at least as deeply as anyone else.

There may be very good reasons for delivering online teaching in segments, punctuated by tasks and feedback, but as Yandell observes, other ways of reading and writing are marginalised in the process. Without wishing to romanticise the lonely reader (or, for that matter, the lonely writer), something is lost when alternating periods of passivity and activity are compressed into interactivity, until eventually education becomes a continuous cybernetic loop of information and feedback. How many keystrokes or mouse-clicks before a student is told they’ve gone wrong? How many words does it take to make a mistake?

This vision of language as code may already have been a significant feature of the curriculum, but it appears to have been exacerbated by the switch to online teaching. In a journal article from August 2020, ‘Learning under Lockdown: English Teaching in the Time of Covid-19’, John Yandell notes that online classes create wholly closed worlds, where context and intertextuality disappear in favour of constant instruction. In these online environments, readingis informed not by prior reading experiences but by the toolkit that the teacher has provided, and ... is presented as occurring along a tramline of linear development. Different readings are reducible to better or worse readings: the more closely the student’s reading approximates to the already finalised teacher’s reading, the better it is. That, it would appear, is what reading with precision looks like.

Constant interaction across an interface may be a good basis for forms of learning that involve information-processing and problem-solving, where there is a right and a wrong answer. The cognitive skills that can be trained in this way are the ones computers themselves excel at: pattern recognition and computation. The worry, for anyone who cares about the humanities in particular, is about the oversimplifications required to conduct other forms of education in these ways.

Blanket surveillance replaces the need for formal assessment.

Confirming Adorno’s worst fears of the ‘primacy of practical reason’, reading is no longer dissociable from the execution of tasks. And, crucially, the ‘goals’ to be achieved through the ability to read, the ‘potential’ and ‘participation’ to be realised, are economic in nature.

since 2019, with the Treasury increasingly unhappy about the amount of student debt still sitting on the government’s balance sheet and the government resorting to ‘culture war’ at every opportunity, there has been an effort to single out degree programmes that represent ‘poor value for money’, measured in terms of graduate earnings. (For reasons best known to itself, the usually independent Institute for Fiscal Studies has been leading the way in finding correlations between degree programmes and future earnings.) Many of these programmes are in the arts and humanities, and are now habitually referred to by Tory politicians and their supporters in the media as ‘low-value degrees’.

studying the humanities may become a luxury reserved for those who can fall back on the cultural and financial advantages of their class position. (This effect has already been noticed among young people going into acting, where the results are more visible to the public than they are in academia or heritage organisations.)

given the changing class composition of the UK over the past thirty years, it’s not clear that contemporary elites have any more sympathy for the humanities than the Conservative Party does. A friend of mine recently attended an open day at a well-known London private school, and noticed that while there was a long queue to speak to the maths and science teachers, nobody was waiting to speak to the English teacher. When she asked what was going on, she was told: ‘I’m afraid parents here are very ambitious.’ Parents at such schools, where fees have tripled in real terms since the early 1980s, tend to work in financial and business services themselves, and spend their own days profitably manipulating and analysing numbers on screens. When it comes to the transmission of elite status from one generation to the next, Shakespeare or Plato no longer has the same cachet as economics or physics.

Leaving aside the strategic political use of terms such as ‘woke’ and ‘cancel culture’, it would be hard to deny that we live in an age of heightened anxiety over the words we use, in particular the labels we apply to people. This has benefits: it can help to bring discriminatory practices to light, potentially leading to institutional reform. It can also lead to fruitless, distracting public arguments, such as the one that rumbled on for weeks over Angela Rayner’s description of Conservatives as ‘scum’. More and more, words are dredged up, edited or rearranged for the purpose of harming someone. Isolated words have acquired a weightiness in contemporary politics and public argument, while on digital media snippets of text circulate without context, as if the meaning of a single sentence were perfectly contained within it, walled off from the surrounding text. The exemplary textual form in this regard is the newspaper headline or corporate slogan: a carefully curated series of words, designed to cut through the blizzard of competing information.

Visit any actual school or university today (as opposed to the imaginary ones described in the Daily Mail or the speeches of Conservative ministers) and you will find highly disciplined, hierarchical institutions, focused on metrics, performance evaluations, ‘behaviour’ and quantifiable ‘learning outcomes’.

If young people today worry about using the ‘wrong’ words, it isn’t because of the persistence of the leftist cultural power of forty years ago, but – on the contrary – because of the barrage of initiatives and technologies dedicated to reversing that power. The ideology of measurable literacy, combined with a digital net that has captured social and educational life, leaves young people ill at ease with the language they use and fearful of what might happen should they trip up.

It has become clear, as we witness the advance of Panopto, Class Dojo and the rest of the EdTech industry, that one of the great things about an old-fashioned classroom is the facilitation of unrecorded, unaudited speech, and of uninterrupted reading and writing.