The Future of Teaching is Here — from samchaltain.substack.com by Sam Chaltain

Excerpts (emphasis DSC):

It’s not sexy, but I feel like Sal Khan’s recent video introducing his Academy’s GPT-fueled AI tutor augurs the future of the teaching profession — and not just at Khan Academy.

The tutor is already fully capable of offering personalized feedback, hints and suggestions for just about any topic for which there are already clearly established answers — from solving math equations with parentheses to digesting John Locke’s political philosophy.

But now we’ve entered a new chapter — dare I say, a Technological Singularity (20 years early) — one in which Chat-GPT in particular, and the daily flood of AI tools more generally, has changed the nature of the teacher/student relationship even more irrevocably than before.

As a result, from this day forward, the job of a teacher REALLY needs to stop being about transmission.

So what should it start being instead?

In which case, the future of teaching is not about transmission, but it is about the other trans- words: transmedia exploration, transdisciplinary weaving, transcultural understanding, and, yes, personal and societal transformation.

 

Why some college professors are adopting ChatGPT AI as quickly as students — from cnbc.com by Carolyn Chun

Key Points:

  • A recent analysis by researchers at NYU, Princeton and the Wharton School finds that many of the jobs that will be most “exposed” to generative AI such as ChatGPT are in the college teaching profession.
  • One of the first narratives to emerge from the sudden explosion in usage of ChatGPT is the risk of students cheating on writing assignments.
  • But use by college teachers is growing quickly too, and adoption by educators may be critical to making the case that AI will augment the jobs humans are doing rather than replace them.

Also relevant/see:


 

When It Comes to College Closures, the Sky Is Never Going to Fall — from chronicle.com by Lee Gardner
Are you tired of reading nearly annual predictions of a looming wave of colleges shutting down? Not nearly as tired as one Chronicle reporter.

Excerpts:

I’ve learned a lot of things about how colleges work in the last 10 years, including that they die hard. They make new appeals to students and alumni. They scrimp. They raise their tuition-discount rate yet again. They limp along with budget deficits, sometimes for years. They make withdrawals from their endowments. They sell off assets. They look for partnerships, mergers, and buyers, although sometimes when it’s far too late.

I could be wrong, of course, and there may be a giant wave of college closures rearing somewhere on the horizon. But I can guarantee you that there are dozens of institutions in danger of quietly slipping toward a gradual end as you read this.

Also highly relevant here/see:

Contingent faculty jobs are still the standard, AAUP report finds — from highereddive.com by Laura Spitalniak

Dive Brief:

  • Colleges are continuing to increase their reliance on faculty positions that lack pathways to tenure, according to a new report from the American Association of University Professors. Over two-thirds of faculty members, 68%, held contingent positions in fall 2021, compared to about 47% in fall 1987.
  • Part-time work is also becoming more common. Almost half of faculty, 48%, taught part time in fall 2021, up from 33% in fall 1987. Less than 1% of all part-time faculty positions are tenured or tenure-track, according to AAUP.
  • Both of these factors are cutting into the number of available tenured positions, the report said. Fewer than 1 in 4 faculty members, 24%, held tenured full-time positions in fall 2021. That number fell from 39% in fall 1987.

Americans Are Losing Faith in College Education, WSJ-NORC Poll Finds — from wsj.com by Douglas Belkin (behind a firewall)
Confidence in value of a degree plummeted among women and senior citizens during pandemic

Excerpt:

A majority of Americans don’t think a college degree is worth the cost, according to a new Wall Street Journal-NORC poll, a new low in confidence in what has long been a hallmark of the American dream.

The survey, conducted with NORC at the University of Chicago, a nonpartisan research organization, found that 56% of Americans think earning a four-year degree is a bad bet compared with 42% who retain faith in the credential.

Skepticism is strongest among people ages 18-34, and people with college degrees are among those whose opinions have soured the most, portending a profound shift for higher education in the years ahead.
 

Higher Learning Commission's 2023 Trends

 
 

On the K-12 side of things:

6 Ways to Use ChatGPT to Save Time — from edutopia.org by Todd Finley
Teachers can use the artificial intelligence tool to effectively automate some routine tasks.

Excerpt:

In the paragraphs that follow, I’ve divided these tasks into the following categories: planning instruction, handouts and materials, differentiation, correspondence, assessment, and writing instruction and feedback. Welcome to the revolution.

Lesson plans: Ask ChatGPT to write a lesson plan on, say, Westward Expansion. The tool composes assessments, activities, scaffolding, and objectives. Want that in the form of problem-based learning or revised for a flipped classroom? ChatGPT can adjust the lesson plan according to your instructions. 

I’m a high school math and science teacher who uses ChatGPT, and it’s made my job much easier — from businessinsider-com.cdn.ampproject.org by Aaron Mok; with thanks to Robert Gibson on LinkedIn for this resource

Shannon Ahern teaching her class with the help of a ChatGPT-generated slide. Photo courtesy of Shannon Ahern

Excerpt:

  • Shannon Ahern, a high school math and science teacher, was afraid that ChatGPT would take her job.
  • But her mind changed after she started using the AI for class prep, which saved her hours of time.
  • Here’s how Ahern is using ChatGPT to make her job easier, as told to Insider’s Aaron Mok.

On the higher education side of things:

Using AI to make teaching easier & more impactful — from oneusefulthing.substack.com by Ethan Mollick
Here are five strategies and prompts that work for GPT-3.5 & GPT-4

Excerpt:

But one thing that is not changing is the best way for people to learn. We have made large advances in recent years in understanding pedagogy – the science of learning. We know some of the most effective techniques for making sure material sticks and that it can be retrieved and used when needed most.

Unfortunately, many of these advanced pedagogical techniques are time-consuming to prepare, and many instructors are often overworked and do not have the resources and time to add them to their teaching repertoire. But AI can help. In the rush to deliver AI benefits directly to students, the role of teachers is often overlooked.

Teaching: What You Need to Know About ChatGPT — from chronicle.com by Beth McMurtrie

Excerpt:

Digital literacy is more important than ever. Artificial-intelligence tools, and generative AI in particular, raise a host of ethical, political, economic, and social questions. Plus, this tech is soon going to be everywhere, including students’ future professions. (The technology behind ChatGPT, in fact, just got an upgrade this week.) Colleges need to figure out how to graduate digitally savvy students in all disciplines.

“The integration of technology into our lives is so pervasive that the restriction of education about AI to the computer scientists and the computer engineers makes no more sense than the restriction of taking English classes by English majors,” said Weber.

 

Designing Virtual Edtech Faculty Development Workshops That Stick: 10 Guiding Principles — from er.educause.edu by Tolulope (Tolu) Noah
These ten principles offer guidance on ways to design and facilitate effective and engaging virtual workshops that leave faculty feeling better equipped to implement new edtech tools.

Excerpt:

I share here ten guiding principles that have shaped my design and facilitation of virtual synchronous edtech workshops. These guiding principles are based on lessons learned in both my previous role as a professional learning specialist at a major technology company and my current role as a faculty developer at a university. In the spirit of James M. Lang’s book Small Teaching, my hope is that the principles shared here may prompt reflection on the small yet impactful moves academic technology specialists, instructional designers, and educational developers can make to create virtual learning experiences whereby faculty leave feeling better equipped to implement the edtech tools they have learned.


Somewhat relevant/see:

Evidence-Based Learning Design 101 — by Dr. Philippa Hardman
A practical guide on how to bake the science of learning into the art of course design

Excerpt:

As I reflect on the experience and what I’ve learned so far, I thought I’d share a response to the question I probably get asked most: what process do you use to go from an idea to a designed learning experience?

So, let’s do a rapid review of the four step process I and my bootcamp alumni use – aka the DOMS™? process – to go from zero to a designed learning experience.

 

ChatGPT as a teaching tool, not a cheating tool — from timeshighereducation.com by Jennifer Rose
How to use ChatGPT as a tool to spur students’ inner feedback and thus aid their learning and skills development

Excerpt:

Use ChatGPT to spur student’s inner feedback
One way that ChatGPT answers can be used in class is by asking students to compare what they have written with a ChatGPT answer. This draws on David Nicol’s work on making inner feedback explicit and using comparative judgement. His work demonstrates that in writing down answers to comparative questions students can produce high-quality feedback for themselves which is instant and actionable. Applying this to a ChatGPT answer, the following questions could be used:

  • Which is better, the ChatGPT response or yours? Why?
  • What two points can you learn from the ChatGPT response that will help you improve your work?
  • What can you add from your answer to improve the ChatGPT answer?
  • How could the assignment question set be improved to allow the student to demonstrate higher-order skills such as critical thinking?
  • How can you use what you have learned to stay ahead of AI and produce higher-quality work than ChatGPT?
 

Teaching: A University-Wide Language for Learning — from chronicle.com by Beckie Supiano

Excerpt (emphasis DSC):

Last week, as I was interviewing Shaun Vecera about a new initiative he directs at the University of Iowa, he made a comment that stopped me in my tracks. The initiative, Learning at Iowa, is meant to create a common vocabulary, based on cognitive science, to support learning across the university. It focuses on “the three M’s for effective learning”: mind-set, metacognition, and memory.

“Not because those are the wrong ways of talking about that. But when you talk about learning, I think you can easily see how these skills transfer across not just courses, but also transfer from the university into a career.”


From DSC:
This reminds me of what I was trying to get at here — i.e., let’s provide folks with more information on learning how to learn.

Lets provide folks with more information on learning how to learn

Lets provide folks with more information on learning how to learn

Lets provide folks with more information on learning how to learn


Also relevant/see:

Changing your teaching takes more than a recipe — — from chronicle.com by Beckie Supiano
Professors have been urged to adopt more effective practices. Why are their results so mixed?

Excerpts:

When the researchers asked their interview subjects how they first learned about peer instruction, many more cited informal discussions with colleagues than cited more formal channels like workshops. Even fewer pointed to a book or an article.

So even when there’s a really well-developed recipe, professors aren’t necessarily reading it.

In higher ed, teaching is often seen as something anyone who knows the content can automatically do. But the evidence suggests instead that teaching is an intellectual exercise that adds to subject-matter expertise.

This teaching-specific math knowledge, the researchers note, could be acquired in teacher preparation or professional development, however, it’s usually created on the job.

“Now, I’m much more apt to help them develop a deeper understanding of how people learn from a neuroscientific and cognitive-psychology perspective, and have them develop a model for how students learn.”

Erika Offerdahl, associate vp and director of the Transformational Change Initiative at WSU

From DSC:
I love this part too:

There’s a role here, too, for education researchers. Not every evidence-based teaching practice has been broken into its critical components in the literature,

 

Challenging ‘Bad’ Online Policies and Attitudes — from insidehighered.com by Susan D’Agostino
Academic and industry leaders spoke with conviction at the SXSW EDU conference this week about approaches that impede educational access to motivated, capable learners.

Excerpts:

“It’s driven by artificial intelligence,” Barnes said of IBM’s training and reskilling effort. “It’s a Netflix-like interface that pushes content. Or an employee can select content…

The leaders discussed the ways in which colleges, policymakers, and employers might work together to help more Americans find or advance in viable employment, while also addressing the workforce skills gap. But some “bad” policies and attitudes about online learning undermine their efforts to work together, expand access and deliver outcomes to motivated, capable learners.

“Employers were saying, ‘We have job openings we can’t fill, and we want to work with the education system, but it is so unbelievably frustrating because they’re very rigid, and they don’t want to customize to our needs,’” Hansen said. These employers sought workforce training that could produce a pipeline of learners-turned-employees, and Hansen said they told him, “If you can do that, I’ll pay you.”

 

The Librarian: Can we prompt ChatGPT to generate reliable references? — from drphilippahardman.substack.com by Dr. Philippa Hardman

Lessons Learned

  • Always assume that ChatGPT is wrong until you prove otherwise.
  • Validate everything (and require your students to validate everything too).
  • Google Scholar is a great tool for validating ChatGPT outputs rapidly.
  • The prompt works better when you provide a subject area, e.g. visual anthropology, and then a sub-topic, e.g. film making.
  • Ignore ChatGPT’s links – validate by searching for titles & authors, not URLs.
  • Use intentional repetition, e.g. of Google Scholar, to focus ChatGPT’s attention.
  • Be aware: ChatGPT’s outputs end at 2021. You need to fill in the blanks since then.
 

ChatGPT is Everywhere — from chronicle.com by Beth McMurtrie
Love it or hate it, academics can’t ignore the already pervasive technology.

Excerpt:

Many academics see these tools as a danger to authentic learning, fearing that students will take shortcuts to avoid the difficulty of coming up with original ideas, organizing their thoughts, or demonstrating their knowledge. Ask ChatGPT to write a few paragraphs, for example, on how Jean Piaget’s theories on childhood development apply to our age of anxiety and it can do that.

Other professors are enthusiastic, or at least intrigued, by the possibility of incorporating generative AI into academic life. Those same tools can help students — and professors — brainstorm, kick-start an essay, explain a confusing idea, and smooth out awkward first drafts. Equally important, these faculty members argue, is their responsibility to prepare students for a world in which these technologies will be incorporated into everyday life, helping to produce everything from a professional email to a legal contract.

“Artificial-intelligence tools present the greatest creative disruption to learning that we’ve seen in my lifetime.”

Sarah Eaton, associate professor of education at the University of Calgary



Artificial intelligence and academic integrity, post-plagiarism — from universityworldnews.com Sarah Elaine Eaton; with thanks to Robert Gibson out on LinkedIn for the resource

Excerpt:

The use of artificial intelligence tools does not automatically constitute academic dishonesty. It depends how the tools are used. For example, apps such as ChatGPT can be used to help reluctant writers generate a rough draft that they can then revise and update.

Used in this way, the technology can help students learn. The text can also be used to help students learn the skills of fact-checking and critical thinking, since the outputs from ChatGPT often contain factual errors.

When students use tools or other people to complete homework on their behalf, that is considered a form of academic dishonesty because the students are no longer learning the material themselves. The key point is that it is the students, and not the technology, that is to blame when students choose to have someone – or something – do their homework for them.

There is a difference between using technology to help students learn or to help them cheat. The same technology can be used for both purposes.

From DSC:
These couple of sentences…

In the age of post-plagiarism, humans use artificial intelligence apps to enhance and elevate creative outputs as a normal part of everyday life. We will soon be unable to detect where the human written text ends and where the robot writing begins, as the outputs of both become intertwined and indistinguishable.

…reminded me of what’s been happening within the filmmaking world for years (i.e., such as in Star Wars, Jurrasic Park, and many others). It’s often hard to tell what’s real and what’s been generated by a computer.
 

As Colleges Focus on Quality in Online Learning, Advocates Ask: What About In-Person Courses? — from chronicle.com by Taylor Swaak

Excerpt (emphasis DSC):

As colleges’ online catalogs grow, so too has the push to develop standards of quality for those courses. But are in-person classes getting the same attention?

If you ask many online-education advocates, the answer is “no.” And the solution, many say, is for colleges to adopt standards and policies that set consistent expectations for quality across all courses, whether they’re remote or in a classroom.

While decades of research and the pandemic-spurred expansion of online learning have helped demystify it, and build confidence in its efficacy, these advocates say the misconception lingers that remote education is inherently lower in quality than instruction in the classroom. And that stigma, they say, puts a magnifying glass to online ed, while largely leaving in-person classes to business as usual.

The focus instead, Simunich said, should be on a big-picture question: Is this a high-quality learning experience for students?

From DSC:
These are great points. I find them to have been very true.

Reflections of a College Adjunct After 31 Years — from insidehighered.com by Stephen Werner
We’ve proven over and over that there’s enough work to give many of us full-time positions, writes Stephen Werner, but things are moving in the opposite direction.

Four Pieces of Advice (emphasis DSC)
In closing, I offer the following recommendations:

  • See the big picture. We adjuncts are workers in the gig economy. We are part of the new normal where so many jobs are on-demand, temporary work, with few or no benefits and no long-term security. Even with our M.A.s and Ph.D.s, we have much in common with workers at all levels, including the lowest-skilled workers.
  • Make a serious effort to meet and talk to other adjuncts.
  • Unionize! Organize with your fellow adjuncts! 
  • Start saving for retirement.

The fact is that college and universities are totally dependent on us. They know it. We adjuncts need to act like we know it, too. We need to overcome our isolation and work together to have a voice.

How Mega-Universities Manage to Teach Hundreds of Thousands of Students — from edsurge.com by Robert Ubell (Columnist)

Excerpt:

One key difference at SNHU is how it hires faculty, relying on an academic army of about 8,000 adjuncts who earn $2,000 per semester for teaching an undergrad course and $2,500 for a grad course. Reliance on adjuncts, especially in online instruction, is a national trend. Today, gig faculty occupy about three-quarters of all U.S. college instructors. But Southern New Hampshire and other online operations depend even more on contingent labor than most of their traditional peers.

For colleges to depend entirely on an Uber-style instructional workforce may be financially prudent, but I argue it’s academically risky, with little continuity and no permanent faculty. It’s also exploitative, with instructors ending up in precarious work arrangements without living wages and benefits.

First Person: Why college matters for people serving extreme sentences — from opencampusmedia.org by Rahsaan “New York” Thomas

Excerpt:

For incarcerated people, the quality or success of a college program is often measured by recidivism rates. By that standard, Mount Tamalpais, formerly the Prison University Project, is a success. Its students had a recidivism rate of 17 percent compared to the 65 percent recidivism rate for the California Department of Corrections and Rehabilitation as a whole, according to a 2011 program evaluation.

Personally, I see education as the key to my success from behind bars. After getting sentenced to a term beyond my life expectancy I needed a path to redemption in the eyes of my mother, my sons, and society that didn’t involve going home. I came up with becoming a writer because my voice was the one part of me that was still free.

 

It’s Not Just Our Students — ChatGPT Is Coming for Faculty Writing — from chronicle.com by Ben Chrisinger (behind a paywall)
And there’s little agreement on the rules that should govern it.

Excerpt:

While we’ve been busy worrying about what ChatGPT could mean for students, we haven’t devoted nearly as much attention to what it could mean for academics themselves. And it could mean a lot. Critically, academics disagree on exactly how AI can and should be used. And with the rapidly improving technology at our doorstep, we have little time to deliberate.

Already some researchers are using the technology. Among only the small sample of my work colleagues, I’ve learned that it is being used for such daily tasks as: translating code from one programming language to another, potentially saving hours spent searching web forums for a solution; generating plain-language summaries of published research, or identifying key arguments on a particular topic; and creating bullet points to pull into a presentation or lecture.

 
© 2024 | Daniel Christian