The Public Is Giving Up on Higher Ed — from chronicle.com by Michael D. Smith Our current system isn’t working for society. Digital alternatives can change that.
Excerpts:
I fear that we in the academy are willfully ignoring this problem. Bring up student-loan debt and you’ll hear that it’s the government’s fault. Bring up online learning and you’ll hear that it is — and always will be — inferior to in-person education. Bring up exclusionary admissions practices and you’ll hear something close to, “Well, the poor can attend community colleges.”
On one hand, our defensiveness is natural. Change is hard, and technological change that risks making traditional parts of our sector obsolete is even harder. “A professor must have an incentive to adopt new technology,” a tenured colleague recently told me regarding online learning. “Innovation adoption will occur one funeral at a time.”
But while our defense of the status quo is understandable, maybe we should ask whether it’s ethical, given what we know about the injustice inherent in our current system. I believe a happier future for all involved — faculty, administrators, and students — is within reach, but requires we stop reflexively protecting our deeply flawed system. How can we do that? We could start by embracing three fundamental principles.
1. Digitization will change higher education.
… 2. We should want to embrace this change. …
3. We have a way to embrace this change.
I fear that we in the academy are willfully ignoring this problem. Bring up student-loan debt and you’ll hear that it’s the government’s fault. Bring up online learning and you’ll hear that it is — and always will be — inferior to in-person education. Bring up exclusionary admissions practices and you’ll hear something close to, “Well, the poor can attend community colleges.”
In this second edition, award-winning educator Sue Ellen Christian offers students an accessible and informed guide to how they can consume and create media intentionally and critically.
The textbook applies media literacy principles and critical thinking to the key issues facing young adults today, from analyzing and creating media messages to verifying information and understanding online privacy. Through discussion prompts, writing exercises, key terms, and links, readers are provided with a framework from which to critically consume and create media in their everyday lives. This new edition includes updates covering privacy aspects of AI, VR and the metaverse, and a new chapter on digital audiences, gaming, and the creative and often unpaid labor of social media and influencers. Chapters examine news literacy, online activism, digital inequality, social media and identity, and global media corporations, giving readers a nuanced understanding of the key concepts at the core of media literacy. Concise, creative, and curated, this book highlights the cultural, political, and economic dynamics of media in contemporary society, and how consumers can mindfully navigate their daily media use.
This textbook is perfect for students and educators of media literacy, journalism, and education looking to build their understanding in an engaging way.
New York City Public Schools will launch an Artificial Intelligence Policy Lab to guide the nation’s largest school district’s approach to this rapidly evolving technology.
Kevin McCullen, an associate professor of computer science at the State University of New York at Plattsburgh, teaches a freshman seminar about AI and robotics. As part of the course, students read Machines of Loving Grace: The Quest for Common Ground Between Humans and Robots, by John Markoff. McCullen had the students work in groups to outline and summarize the first three chapters. Then he showed them what ChatGPT had produced in an outline.
“Their version and ChatGPT’s version seemed to be from two different books,” McCullen wrote. “ChatGPT’s version was essentially a ‘laundry list’ of events. Their version was narratives of what they found interesting. The students had focused on what the story was telling them, while ChatGPT focused on who did what in what year.” The chatbot also introduced false information, such as wrong chapter names.
The students, he wrote, found the writing “soulless.”
In the Wild West of generative AI, educators and institutions are working out how best to use the technology for learning. How can institutions define AI guidelines that allow for experimentation while providing students with consistent guidance on appropriate use of AI tools?
To find out, we spoke with Dr. Cristi Ford, vice president of academic affairs at D2L. With more than two decades of educational experience in nonprofit, higher education, and K-12 institutions, Ford works with D2L’s institutional partners to elevate best practices in teaching, learning, and student support. Here, she shares her advice on setting and communicating AI policies that are consistent and future-ready.
“If we want to use AI to improve education, we need more teachers at the table,” said Avery Pan, Class Companion co-founder and CEO. “Class Companion is designed by teachers, for teachers, to harness the most sophisticated AI and improve their classroom experience. Developing technologies specifically for teachers is imperative to supporting our next generation of students and education system.”
7 Questions on Generative AI in Learning Design — from campustechnology.com by Rhea Kelly Open LMS Adoption and Education Specialist Michael Vaughn on the challenges and possibilities of using artificial intelligence to move teaching and learning forward.
The potential for artificial intelligence tools to speed up course design could be an attractive prospect for overworked faculty and spread-thin instructional designers. Generative AI can shine, for example, in tasks such as reworking assessment question sets, writing course outlines and learning objectives, and generating subtitles for audio and video clips. The key, says Michael Vaughn, adoption and education specialist at learning platform Open LMS, is treating AI like an intern who can be guided and molded along the way, and whose work is then vetted by a human expert.
We spoke with Vaughn about how best to utilize generative AI in learning design, ethical issues to consider, and how to formulate an institution-wide policy that can guide AI use today and in the future.
Canva’s new AI tools automate boring, labor-intensive design tasks — from theverge.com by Jess Weatherbed Magic Studio features like Magic Switch automatically convert your designs into blogs, social media posts, emails, and more to save time on manually editing documents.
The more I look around higher education, the more clearly it seems to me that there are three practices which we carry out every day – which seemed baked right into the very DNA of our current system of higher education – that are inimical to the actual purpose of higher education. Those practices are:
Lecturing,
Traditional grading, and
Student evaluations of teaching.
Before you get upset, let me say: I don’t think any of these practices is “evil”, and my understanding of the history of education says that all three were developed with good intentions, for legitimate reasons, to solve real problems. (With the possible exception of student evaluations of teaching – I’m working on trying to figure out where these came from and why they were invented.) But regardless of the background and intentions, they have taken over higher education like an invasive species.
“If you looked at the average person outside of higher education and said, you know, ‘We’ve created a culture in higher ed where our core thing we do isn’t valued,’ that makes absolutely no sense,” says Amy Hawkins, assistant provost for teaching and academic leadership at the University of Central Arkansas, which has been working to change that dynamic on campus. “It would be like saying in a company, ‘Well, customer service isn’t really a big deal to us. We’re about product development. We treat our customers like crap.’ I mean. That’s nonsensical.”
Does the public know this? And does it care?
Surveys show that what the public values most about higher education is good teaching and meaningful learning.
What makes an effective microcredential programme? — from by Temesgen Kifle Short, flexible and skills-focused, microcredentials must balance the needs of students and industry. Here are tips on how to develop courses that achieve this
Here are tips for higher education institutions (HEIs) to consider when creating and delivering microcredential programmes so they meet the needs of all stakeholders.
Collaborate with accrediting bodies, employers and other HEIs
An introduction to creating escape rooms— from timeshighereducation.com by Bernardo Pereira Nunes Bernardo Pereira Nunes offers tips on how to get started on an escape room experience that will boost students’ teamwork, leadership, communication and problem-solving skills
But I’ve also been hearing one intriguing question, over and over, that isn’t directly about loans or repayment, so much as it is about how to avoid them entirely. And it’s coming from parents of kids who’ve not yet traded in their sticker collections for student loans.
“I’ve got one little guy who’s about six years old,” Caleb Queern, of Austin, Texas, told me recently. “And my questions are, number one: How much should we be saving between now and the time my little guy is ready for college? And number two: What’s the best way to save for it?”
Is school transformation possible without replacing the existing education system? In addition to Tom, Kelly Young of Education Reimagined joined me to argue that it’s not. In an educational landscape that constantly seeks marginal improvements, my guests spoke to the importance of embracing new value networks that support innovative approaches to learning. The conversation touched on the issue of programs that remain niche solutions, rather than robust, learner-centered alternatives. In exploring the concept of value networks, they both challenged the notion of transforming individual schools or districts alone. They argue for the creation of a new value network to truly revolutionize the education system. Of course, they admit that achieving this is no small feat, as it requires a paradigm shift in mindset and a careful balance between innovation and existing structures. In this conversation, we wrestle with the full implications of their findings and more.
Hi everyone, I’m Daphne, a 13-year-old going into 8th grade.
I’m writing to compare “regular” Khan Academy (no AI) to Khanmigo (powered by GPT4), using three of my own made-up criteria.
They are: efficiency, effectiveness, and enjoyability. Efficiency is how fast I am able to cover a math topic and get basic understanding. Effectiveness is my quality of understanding—the difference between basic and advanced understanding. And the final one—most important to kids and maybe least important to adults who make kids learn math—is enjoyability.
7 Questions on Generative AI in Learning Design — from campustechnology.com by Rhea Kelly Open LMS Adoption and Education Specialist Michael Vaughn on the challenges and possibilities of using artificial intelligence to move teaching and learning forward.
The potential for artificial intelligence tools to speed up course design could be an attractive prospect for overworked faculty and spread-thin instructional designers. Generative AI can shine, for example, in tasks such as reworking assessment question sets, writing course outlines and learning objectives, and generating subtitles for audio and video clips. The key, says Michael Vaughn, adoption and education specialist at learning platform Open LMS, is treating AI like an intern who can be guided and molded along the way, and whose work is then vetted by a human expert.
We spoke with Vaughn about how best to utilize generative AI in learning design, ethical issues to consider, and how to formulate an institution-wide policy that can guide AI use today and in the future.
On September 25th, 2023, OpenAI announced the rollout of two new features that extend how people can interact with its recent and most advanced model, GPT-4: the ability to ask questions about images and to use speech as an input to a query.
This functionality marks GPT-4’s move into being a multimodal model. This means that the model can accept multiple “modalities” of input – text and images – and return results based on those inputs. Bing Chat, developed by Microsoft in partnership with OpenAI, and Google’s Bard model both support images as input, too. Read our comparison post to see how Bard and Bing perform with image inputs.
In this guide, we are going to share our first impressions with the GPT-4V image input feature.
Student Use Cases for AI: Start by Sharing These Guidelines with Your Class — from hbsp.harvard.edu by Ethan Mollick and Lilach Mollick
To help you explore some of the ways students can use this disruptive new technology to improve their learning—while making your job easier and more effective—we’ve written a series of articles that examine the following student use cases:
Earlier this week, CETL and AIG hosted a discussion among UM faculty and other instructors about teaching and AI this fall semester. We wanted to know what was working when it came to policies and assignments that responded to generative AI technologies like ChatGPT, Google Bard, Midjourney, DALL-E, and more. We were also interested in hearing what wasn’t working, as well as questions and concerns that the university community had about teaching and AI.
Then, in class he put them into groups where they worked together to generate a 500-word essay on “Why I Write” entirely through ChatGPT. Each group had complete freedom in how they chose to use the tool. The key: They were asked to evaluate their essay on how well it offered a personal perspective and demonstrated a critical reading of the piece. Weiss also graded each ChatGPT-written essay and included an explanation of why he came up with that particular grade.
After that, the students were asked to record their observations on the experiment on the discussion board. Then they came together again as a class to discuss the experiment.
Weiss shared some of his students’ comments with me (with their approval). Here are a few:
Asked to describe the state of generative AI that they would like to see in higher education 10 years from now, panelists collaboratively constructed their preferred future. .
Julie York, a computer science and media teacher at South Portland High School in Maine, was scouring the internet for discussion tools for her class when she found TeachFX. An AI tool that takes recorded audio from a classroom and turns it into data about who talked and for how long, it seemed like a cool way for York to discuss issues of data privacy, consent and bias with her students. But York soon realized that TeachFX was meant for much more.
York found that TeachFX listened to her very carefully, and generated a detailed feedback report on her specific teaching style. York was hooked, in part because she says her school administration simply doesn’t have the time to observe teachers while tending to several other pressing concerns.
“I rarely ever get feedback on my teaching style. This was giving me 100 percent quantifiable data on how many questions I asked and how often I asked them in a 90-minute class,” York says. “It’s not a rubric. It’s a reflection.”
TeachFX is easy to use, York says. It’s as simple as switching on a recording device.
…
But TeachFX, she adds, is focused not on her students’ achievements, but instead on her performance as a teacher.
ChatGPT Is Landing Kids in the Principal’s Office, Survey Finds — from the74million.org by Mark Keierleber While educators worry that students are using generative AI to cheat, a new report finds students are turning to the tool more for personal problems.
Indeed, 58% of students, and 72% of those in special education, said they’ve used generative AI during the 2022-23 academic year, just not primarily for the reasons that teachers fear most. Among youth who completed the nationally representative survey, just 23% said they used it for academic purposes and 19% said they’ve used the tools to help them write and submit a paper. Instead, 29% reported having used it to deal with anxiety or mental health issues, 22% for issues with friends and 16% for family conflicts.
Part of the disconnect dividing teachers and students, researchers found, may come down to gray areas. Just 40% of parents said they or their child were given guidance on ways they can use generative AI without running afoul of school rules. Only 24% of teachers say they’ve been trained on how to respond if they suspect a student used generative AI to cheat.
The prospect of AI-powered, tailored, on-demand learning and performance support is exhilarating: It starts with traditional digital learning made into fully adaptive learning experiences, which would adjust to strengths and weaknesses for each individual learner. The possibilities extend all the way through to simulations and augmented reality, an environment to put into practice knowledge and skills, whether as individuals or working in a team simulation. The possibilities are immense.
Thanks to generative AI, such visions are transitioning from fiction to reality.
Video: Unleashing the Power of AI in L&D — from drphilippahardman.substack.com by Dr. Philippa Hardman An exclusive video walkthrough of my keynote at Sweden’s national L&D conference this week
Highlights
The wicked problem of L&D: last year, $371 billion was spent on workplace training globally, but only 12% of employees apply what they learn in the workplace
An innovative approach to L&D: when Mastery Learning is used to design & deliver workplace training, the rate of “transfer” (i.e. behaviour change & application) is 67%
AI 101: quick summary of classification, generative and interactive AI and its uses in L&D
The impact of AI: my initial research shows that AI has the potential to scale Mastery Learning and, in the process:
reduce the “time to training design” by 94% > faster
reduce the cost of training design by 92% > cheaper
increase the quality of learning design & delivery by 96% > better
Research also shows that the vast majority of workplaces are using AI only to “oil the machine” rather than innovate and improve our processes & practices
Practical tips: how to get started on your AI journey in your company, and a glimpse of what L&D roles might look like in a post-AI world
I dwell on this story not merely because the irony of defending the role of research by ignoring the research on the topic is exquisite, but because it is emblematic of a widespread problem within higher education. The resistance to anything like serious change is profound. By “change” I don’t mean the addition of yet another program or the alteration of a graduation requirement, but something that is transformational and affects the way we do our work on a deep level.
If maintenance of the status quo is the goal, higher education has managed to create the ideal system.
…
Cut through all the graphs and economic data and the problem is straightforward: When the service you provide costs more than people are willing and able to pay for it, when you are unable to lower the cost of that service, and when the number of your potential customers is shrinking, you have what one might describe as an unsustainable financial model.
…
“College teaching has probably seen less change than almost any other American institutional practice since the days of Henry Adams.”
One of the biggest challenges to navigate now is the fact that more digital tools will come with generative AI already embedded in them, says Annette Vee, director of composition and an associate professor at the University of Pittsburgh. “It’s everywhere in professional writing.”
“We need to be fundamentally rethinking ways we teach writing, so we are thinking about integrating tools mindfully,” says Vee, who helped develop a new resource, TextGenEd, that provides guidance in this area. “The real challenge is how do we teach courses that are preparing students and that are smart about generative AI? We have very few teachers currently equipped to do that work.”
“It’s best if there are real stakes attached to the work, for example, an authentic audience the student is writing to,” he writes. “A subject on which students have both sufficient interest and knowledge in order to feel as though they can write convincingly to this audience also matters a lot.”
Also relevant/see — via Robert Gibson on LinkedIn:
Learnt.ai — Built for Learning Specialists — from learnt.ai Harness the power of artificial intelligence to enhance your learning and development efforts with our easy-to-use platform – no technical expertise required!
Introducing Learnt.ai – a revolutionary collection of AI-powered content generation tools and AI chatbots that are specifically designed to support the common writing tasks of educationalists and learning and development professionals. Imagine being able to generate learning objectives on any topic of your choice, create engaging icebreakers and activities, write assessment questions with ease, and so much more.
Students are using artificial intelligence tools to assist them in their academic careers. Three students share their viewpoints on the tools they use and how using these tools helps them in their coursework and prepares them for the professional world.
Also relevant/see:
Why Professors Are Polarized on AI — from insidehighered.com by Susan D’Agostino Academics who perceive threats to education from AI band together as a survival mechanism. The resulting alliances echo divisions formed during online learning’s emergence.
Ask the Chair: Are Great Chairs Born or Made? — from chronicle.com by Kevin Dettmar (behind a paywall) Higher education is finally getting serious about training new department heads.
Great chairs aren’t born, but made; “trial and error” isn’t actually a professional-development strategy. The provost and deans should recognize that a confident and competent chair makes their job easier, creates a well-functioning department, and buoys faculty, student, and staff morale.
As someone vitally engaged with the chair’s role, I do think we are experiencing a sea-change when it comes to how institutions are preparing chairs. For too long, colleges have treated the position as simply a minor cog in the chain of command. But more and more institutions are now investing in their chairs.
Why do so many students have the impression that they should attend office hours only if they’ve got a question? Here’s my hunch: Well-meaning, supportive professors mention their office hours at various points throughout the course: If you have questions about fill-in-the-blank, come to my office hours. The professors mean, “I am here to help! Come talk to me.” Students hear: “If you have a question.”
It’s a frustrating misunderstanding, because it contributes to the big problem my article focuses on: Many students miss out on the support professors stand to provide.
… ‘Adjunct Faculty 101’
“Sessions offered this year included ‘An Orientation to the Canvas LMS,’ ‘The First Day of Class,’ ‘Creating Student-Centered Course Materials,’ ‘Classroom-Management Tips,’ ‘Academic-Integrity Tips and Processes,’ ‘An Introduction to Our Tutoring Services and Writing Center,’ ‘Writing Across the Disciplines With AI,’ and more.”
From DSC: I like the idea of using “office hours” for building relationships, helping students with their future career decisions, building broader understanding, ongoing mentoring, and for developing potential networking opportunities.
6. Create externship programs for faculty. Many college and university faculty have never worked outside of academia. Given a chance to be exposed to modern workplaces and work challenges, faculty will find innovative and creative ways to weave more work-integrated learning into their curriculum.
From DSC: This is a great idea — thanks Brandon!
I might add another couple of thoughts here as well:
And/or treat your Adjunct Faculty Members much better as well!
And/or work with more L&D Departments at local companies (i.e., to develop closer, more beneficial/WIN-WIN collaborations).
What does active learning require from students? There is no secret that PBL and all other active learning approaches are much more demanding from students compared to traditional methods, mainly in terms of skills and attitudes towards learning. Here are some of the aspects where students, especially when first faced to active learning, seem to struggle:
Formulating own learning goals and following through with independent study. While in traditional teaching the learning goals are given to students, in PBL (or at least in some of its purest variants), they need to come up with their own, for each problem they are solving. This requires understanding the problem well but also a certain frame of mind where one can assess what is necessary to solve it and make a plan of how to go about it (independently and as a group). All these seemingly easy steps are often new to students and something they intrinsically expect from us as educators.
From DSC: The above excerpt re: formulating one’s own learning goals reminded me of project management and learning how to be a project manager.
It reminded me of a project that I was assigned back at Kraft (actually Kraft General Foods at the time). It was an online-based directory of everyone in the company at the time. When it was given to me, several questions arose in my mind:
Where do I start?
How do I even organize this project?
What is the list of to-do’s?
Who will I need to work with?
Luckily I had a mentor/guide who helped me get going and an excellent contact with the vendor who educated me and helped me get the ball rolling.
I’ll end with another quote and a brief comment:
Not being afraid of mistakes and learning from them. The education system, at all stages, still penalises mistakes, often with long term consequences. So it’s no wonder students are afraid of making mistakes…
What we teachers desperately need, though, is an ocean of examples and training. We need to see and share examples of generative AI—any type of artificial intelligence that can be used to create new text, images, video, audio, code, or data—being used across the curriculum. We need catalogs of new lesson plans and new curriculum.
And we need training on theoretical and practical levels: training to understand what artificial intelligence actually is and where it stands in the development timeline and training about how to integrate it into our classes.
So, my advice to teachers is to use any and all the generative AI you can get your hands on. Then experience—for yourself—verification of the information. Track it back to the source because in doing so, you’ll land on the adjustments you need to make in your classes next year.
From DSC: Interesting.
Learners can now seamlessly transition between AI-powered assistance (AI Tutor) and Live Expert support to get access to instant support, whether through AI-guided learning or real-time interactions with a human expert.
ASSIGNMENT MAKEOVERS IN THE AI AGE WITH DEREK BRUFF — from teachinginhighered.com by Bonni Stachowiak Derek Bruff shares about assignment makeovers in the AI age on episode 481 of the Teaching in Higher Ed podcast
Comment on this per Derek Bruff:
Why not ask ChatGPT to write what King or X would say about a current debate and then have the students critique the ChatGPT output? That would meet the same learning goals while also teaching AI literacy.
(Be sure to read Asim’s contribution for a useful take.)
Here’s a closer look at the concurrent AI landscape in schools — and a prediction of what the future holds.
So far, high-profile ventures in the instruction realm, such asKyron Learning, have fused teacher-produced, recorded content with LLM-powered conversational UX. The micro-learning tool Nolej references internet material when generating tasks and tests, but always holds the language model closely to the ground truth provided by teachers. Both are intriguing takes on re-imagining how to deliver core instruction and avoid hallucinations (generated content that is nonsensical).
As a result, real-time 3D jobs are among the most in demand within the tech industry. According to Unity’s vice president of Education and Social Impact, Jessica Lindl, demand is 50% higher than traditional IT jobs—adding that salaries for real-time 3D jobs are 60% greater.
“We want to provide really simple on ramps and pathways that will lead you into entry level jobs so that at any point in your career, you can decide to transfer into the industry,” Lindl says.
University World News continues its exploration of generative AI in our new special report on ‘AI and Higher Education’. In commentaries and features, academics and our journalists around the world investigate issues and developments around AI that are impacting on universities. Generative AI tools are challenging and changing higher education systems and institutions — how they are run as well as ways of teaching and learning and conducting research.
My advice for you today is this: fill your LinkedIn-feed and/or inbox with ideas, inspirational writing and commentary on AI.
This will get you up to speed quickly and is a great way to stay informed on the newest movements you need to be aware of.
My personal recommendation for you is to check out these bright people who are all very active on LinkedIn and/or have a newsletter worth paying attention to.
I have kept the list fairly short – only 15 people – in order to make it as easy as possible for you to begin exploring.
It is crucial to recognize that the intrinsic value of higher education isn’t purely in its ability to adapt to market fluctuations or technological innovations. Its core strength lies in promoting critical thinking, nurturing creativity, and instilling a sense of purpose and belonging. As AI progresses, these traits will likely become even more crucial. The question then becomes if higher education institutions as we know them today are the ony ones, or indeed the best ones, equipped to convey those core strengths to students.
Higher education clearly finds itself caught in a whirlwind of transformation, both in its essence and execution. The juxtaposition of legacy structures and the evolving technological landscape paints a complex picture.
For institutional leaders, the dual challenge lies in proactively seeking and initiating change (not merely adapting to it) without losing sight of their foundational principles. Simultaneously, they must equip students with skills and perspectives that AI cannot replicate.
“They begged, bargained with, and berated their instructor in pursuit of better grades — not “because they like points,” but rather, “because the education system has told them that these points are the currency with which they can buy a successful future.””
Habit #2: Engage students in a brain dump or two things as an entry ticket or exit ticket. Spend one minute or less having students write down everything (or just two things) they remember from class. The key: Don’t grade it! Keep retrieval practice no-stakes to emphasize it’s a learning strategy, not an assessment strategy.
Teaching from the heart in 13 steps — from timeshighereducation.com by Beiting He Engaging your students through empathy requires teachers to share their own stories and vulnerabilities and foster a safe space for learning. Here, Beiting He offers 13 ways to create a caring classroom
In summary, “I wish” is about proposing positive changes and improvements, while “I wonder” is about asking thoughtful questions to gain insight and foster meaningful conversations within the team.
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