Group items tagged

Students are more likely to watch a series of shorter videos than a single, longer video, which is why I recommend instructors try to divide long screencasts into five-to-ten minute segments (whenever possible)

asynchronous discussion with audio and video. If you’re not familiar with this concept, I’m referring to discussion tools that allow students to respond with audio and video instead of just text. One tool that’s been a leader for a long time in this multimedia discussion space is VoiceThread. While VoiceThread’s defining feature is its user-friendly approach to audio-based commenting, it can also be used to create narrated presentations with PowerPoints slides, images, and video. If you find yourself overwhelmed by the interface of a traditional screencasting tool, VoiceThread is worth exploring as a simpler way of recording online lectures and fostering discussions that go beyond plain text

tools that require both high bandwidth and high immediacy, and the best examples of this are videoconferencing tools like Zoom or Skype.  Videoconferencing is a great way to engage with students when they truly need to see and hear each other in real time. It can also be useful for online office hours, since it’s easier to feel connected and avoid misunderstandings when you have the benefit of tone of voice, facial expressions, and body language.  Unfortunately, videoconferencing is one of the most inflexible and bandwidth-intensive activities we can ask our students to do. Before you rely on it too heavily, look at the other quadrants and ask yourself if there’s any other way to accomplish your learning objectives without it. 

None of this is to say that videoconferencing is inherently bad or that it has no place in an online course. It’s simply a reminder that seemingly small (and sometimes unconscious) choices about the technologies we use can have a big impact on how inclusive and effective our teaching is.

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

large-language models like ChatGPT are often extolled as the cutting edge of artificial intelligence, it may sound dismissive—or at least deflating—to describe them as lossy text-compression algorithms. I do think that this perspective offers a useful corrective to the tendency to anthropomorphize large-language models

Even though large-language models often hallucinate, when they’re lucid they sound like they actually understand subjects like economic theory

The fact that ChatGPT rephrases material from the Web instead of quoting it word for word makes it seem like a student expressing ideas in her own words, rather than simply regurgitating what she’s read; it creates the illusion that ChatGPT understands the material. In human students, rote memorization isn’t an indicator of genuine learning, so ChatGPT’s inability to produce exact quotes from Web pages is precisely what makes us think that it has learned something. When we’re dealing with sequences of words, lossy compression looks smarter than lossless compression.

Even if it is possible to restrict large-language models from engaging in fabrication, should we use them to generate Web content? This would make sense only if our goal is to repackage information that’s already available on the Web. Some companies exist to do just that—we usually call them content mills. Perhaps the blurriness of large-language models will be useful to them, as a way of avoiding copyright infringement. Generally speaking, though, I’d say that anything that’s good for content mills is not good for people searching for information.

If and when we start seeing models producing output that’s as good as their input, then the analogy of lossy compression will no longer be applicable.

starting with a blurry copy of unoriginal work isn’t a good way to create original work

Having students write essays isn’t merely a way to test their grasp of the material; it gives them experience in articulating their thoughts. If students never have to write essays that we have all read before, they will never gain the skills needed to write something that we have never read.

Sometimes it’s only in the process of writing that you discover your original ideas. Some might say that the output of large-language models doesn’t look all that different from a human writer’s first draft, but, again, I think this is a superficial resemblance. Your first draft isn’t an unoriginal idea expressed clearly; it’s an original idea expressed poorly, and it is accompanied by your amorphous dissatisfaction, your awareness of the distance between what it says and what you want it to say. That’s what directs you during rewriting, and that’s one of the things lacking when you start with text generated by an A.I.

What use is there in having something that rephrases the Web?