Editorial
Imagine you're a professor.
You're teaching a course on something you love and care about. You plan your lessons with gusto. You talk to your students and strive to meet them where they are.
About three weeks in, you assign the first project. Throughout the next couple of weeks, you witness students work on that project in front of you. You had class time to talk about how things are going. You use their facial expressions to decide whether everything is going swimmingly or if you need to intervene.
Then, the time comes. You finally get the batch of assignments and begin to read through them. You have a couple of projects that seem AI-generated. So you meet with the students during class time and iron things out. The conversations aren't tense or anything. One student admits to using an AI bot, so you give them more support and let them re-do it in a new way. Another student used Grammarly and didn't know how AI-infused that program is now.
Things are fine.
Now, let's re-run the scenario. But we're going to make one major change.
The course is now an asynchronous, online one.
You don't get to see the students working on the project. You don't get to talk to students directly about it. You never even meet your students.
You're not allowed to ask students to attend a mandatory Zoom. After all, the students are taking the course this way to work around their busy schedules. Yes, these courses exist. They are very common and becoming increasingly popular.
If a problem arises, you're limited to sending emails or giving phone calls. Or you can hand it off to their advisor and hope that conversation goes well.
Hopefully, this scenario shows just how daunting it can be teach an online course right now.
And as we'll see, that really matters for the workforce.
Online Learning and the Workforce
The number of college students taking online courses has steadily increased over the past decade.
In 2012, about 25% of college students in the U.S. reported taking at least one online course. The pandemic saw that number increase to a staggering 75%, before settling down to about 54% of students in 2022, according to Forbes.
Even with the dip, which is unsurprising, the increase from 25% to 54% within a decade is quite interesting.
Suffice it to say, online courses have become an increasingly important way for college students to upskill and enter the workforce. They make upskilling accessible to millions of students who otherwise would have been left out.
More and more students are taking online courses to upskill and prepare for their jobs and careers.
Increasingly, those same students are pushing for asynchronous courses in which they can complete the work at their own pace. Some colleges even require all components of those courses be asynchronous. This means a professor cannot require a student to, for example, attend a Zoom meeting at a specified time.
This brings us to a major question.
How can college professors make sure students are gaining the foundational skills and knowledge they need, without being able to meet with them or see them work?
It's a tough bind.
How is AI Changing Assessment?
The bind, in many ways, comes down to assessment.
Online professors need to be able to assess student achievement to make sure they are upskilling in a way that prepares them for the workforce.
But the vast majority of the time, online professors only see the products handed in through a learning management system (LMS).
Meanwhile, in in-person classes, many professors are doubling down on process-based assessment. They are focusing less on products a student creates and more on the process they use to create the product. This allows the professor to look at intent and purpose. It also allows them to push the student to develop their metacognitive skills.
Making the process visible has been relatively easy in in-person courses. But in online, asynchronous environments, it has been exceedingly difficult.
The Way Forward
Difficult but not impossible.
There are ways to make the student’s process visible, so the professor can offer feedback, encourage metacognition and help ensure the student is actually upskilling.
Here are some of the more popular approaches:
- Project-based learning: In this model, the professor allows the students to create their own projects to focus on their own passion and on a project that is immediately relevant to their lives. Phillip Alcock, an AI consultant and strategist, does some excellent work in this sector. Chad Raymond writes about the approach in The Chronicle of Higher Education.
- AI transcripts: Increasingly, professors are asking students to submit AI chat logs. This allows the professor to see how the students used the technology as part of their process. Mike Kentz writes about this approach.
To give one more example, in one of my literature classes last semester, I provided students with a Word document, which they filled in on their own. That document walked students through a series of steps, in which they engaged in free writing, marked up a passage, conversed with chatbot, etc.
With some creativity and grit, it is possible to adapt online teaching to a world where AI bots can perform many of the assignments we give our students.
We need to experiment.
We need to rise to the occasion.
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