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The most important things to me are quickly establishing, and having backup modes, for students to be in touch with you, and you with them. As individuals. It might be direct messaging, email, texting. It could be but need not be something Slack-like. I’d really go simplest (email)

Get going with web annotation tools

We need not have just talking sessions for use of video. Think about drop in hours with Whereby (the new appear.in) – it lacks a need for logins and downloads, and works on mobile.

This experiment is going to.. well I bet, go bad in a lot of ways. I don’t know what we can expect of un-experienced teachers and unprepared students, who on top of all the concerns they carry and we rarely see, now have to ponder where they might live and sustain income to live on. It will be interesting… but it need not be awful nor a disaster, if we go about as sharing in the situation.

a possible structure recommended by one of the faculty we were talking to was – read/watch, quiz, lecture, student group discussion, reflection. The reasoning here is that if you give learners (particularly new learners) a reading without some form of accountability (a quiz) they are much less likely to do it. I know that for me, when I’ve done the readings, I’m far more likely to attend class. Putting the student group discussion after the lecture gives students who can’t attend a synchronous session a chance to review the recording

The standardization police have been telling us for years that each student must learn the same things. Poppycock. Scaffolding doesn’t mean taking away student choice. There are numerous approaches to allowing a little or a lot of choice into your classes (learner contracts come to mind). Just remember, most students don’t want choice – at first. 12-16 years of training has told them that you the faculty member have something you want them to do and they need to find the trick of it. It will take a while until those students actually believe you want their actual opinion.

You can have a goal like – get them acculturated to the field – and work through your activities to get there. It’s harder, they will need your patience, but once they get their minds around it, it makes things much more interesting.

Reasons why people want to keep their cameras off include: Discomfort or shyness with showing their faces online. This is real, people. For most people, it gets better with time, but not always and not in every context.Noisy or busy home environments e.g. spouse or kids or siblings moving about. I have occasionally had to mute and turn camera off in the middle of a webinar I am personally giving for those reasons! Women and girls can be especially vulnerable to kids and spouses not respecting their work/learning timeNot being dressed for company (for me personally, I often don’t want to cover my hair for a meeting where I’m not presenting, I want to lounge around in comfy clothes). Or your home not being tidy enough for company. This is a thing.Slow/unstable internet connection. Turning off webcam can be the easiest way to get better quality audioDiscomfort over recording

Ask questions and ask everyone to respond in the chat. You will know if they are focused and engaged by their responses and every single person can participateAsk questions for them to answer orally. Either call on people round robin, or call out some people from the chat (also keeping in mind some people are voice shy, and some people have noisy home environments)If you can divide students into smaller groups go talk to each other and you can move between them like a butterfly, this can help some people engage/talk more and occasionally even turn their cameras onUse things like Annotation or Google docs to have folks contributeAsk students to have a profile picture up when their camera is off. This helps sometimes.You might learn to distinguish student voices as you would close friends on the phone (remember life pre-caller ID where close friends and family would expect that?) and use them as proxies for how they are feeling. You already have this skill, but are not expecting to use it.If you record, consider having an unrecorded portion. You will be surprised how much some people participate or are willing to turn cameras on in the unrecorded portion.

it seems we need to consider ways of allowing people to “be there” in alternative ways that they are comfortable with and that tell us they are really listening to us and responding in more explicit ways

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).