College Cost Transparency Press Release — from collegeprice.org
Hundreds of Colleges and Universities Commit to Student Cost Transparency

WASHINGTON, D.C, SEPTEMBER 26, 2023 — The College Cost Transparency Initiative (CCT) — a task force composed of the leaders of 10 higher education associations representing college presidents, financial aid offices, and admissions and school counselors — today announced that more than 360 institutions of higher education have voluntarily committed to follow a set of principles and standards that ensure transparency, clarity, and understanding around communicating student financial aid offers. Together, these institutions serve more than 3.8 million college students in the United States.

The monumental commitment comes as lawmakers, think tanks, and government entities continue to scrutinize the financial aid offers that colleges and universities present to students. The principles and standards recommended by the CCT respond to the needs of students and families in a nuanced and careful manner.

 

As AI Chatbots Rise, More Educators Look to Oral Exams — With High-Tech Twist — from edsurge.com by Jeffrey R. Young

To use Sherpa, an instructor first uploads the reading they’ve assigned, or they can have the student upload a paper they’ve written. Then the tool asks a series of questions about the text (either questions input by the instructor or generated by the AI) to test the student’s grasp of key concepts. The software gives the instructor the choice of whether they want the tool to record audio and video of the conversation, or just audio.

The tool then uses AI to transcribe the audio from each student’s recording and flags areas where the student answer seemed off point. Teachers can review the recording or transcript of the conversation and look at what Sherpa flagged as trouble to evaluate the student’s response.

 

The Enemy Within: Former College Presidents Offer Warnings — from forbes-com.cdn.ampproject.org by David Rosowsky; via Robert Gibson on LinkedIn

Excerpt (emphasis DSC):

Brian Mitchell, former president of Bucknell University and Washington & Jefferson College, draws on his experience to offer insight in his newest Forbes contribution. He also offers a stern warning: “Boards, administrators, and faculty must wake up to the new realities they now face… the faculty can no longer live in a world that no longer exists… institutional change will happen at a speed to which they are unaccustomed and potentially unwilling to accept.” President Mitchell then goes on to offer some immediate steps that can be taken. Perhaps the most important is to “abandon the approach to governance where trustees are updated in their periodic board meetings.”

Incremental change is possible, but transformational change may not be.

Therein lies the conundrum about which Rosenberg writes in his new book. Higher ed’s own systems are inhibiting needed transformational change.

Also just published was the book, “Whatever It Is, I’m Against It: Resistance to Change in Higher Education” by Brian Rosenberg, former president of Macalester College. Articles on Rosenberg’s observations, analysis, and cautions have appeared this month in both The Chronicle of Higher Education and Inside Higher Ed, the two leading higher education publications in the US.


Addendum on 10/6/23:

Higher Education as Its Own Worst Enemy — from insidehighered.com/ by Susan H. Greenberg
In a wide-ranging discussion about his new book, Brian Rosenberg explains how shared governance, tenure and other practices stifle change on college campuses.

He argues that the institutions designed to foster critical inquiry and the open exchange of ideas are themselves staunchly resistant to both. 

The other would be some serious thinking about pedagogy and how students learn. Because the research is there if people were willing to take it seriously and think about ways of providing an education that is not quite as reliant upon lots of faculty with Ph.D.s. Is that easy to do? No, but it is something that I think there should at least begin to be some serious discussions about.

Shared governance is one of those things that if you ask any college president off the record, they’ll probably express their frustration, then they’ll go back to their campus and wax poetic about the wonders of shared governance, because that’s what they have to do to survive.

 

A three-headed monster — from rtalbert.org by Robert Talbert

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.


Americans Value Good Teaching. Do Colleges? — from chronicle.com by Beth McMurtrie

“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.

  1. Collaborate with accrediting bodies, employers and other HEIs
  2. Develop curricula with specific learning outcomes
  3. Review and update programmes regularly
  4. …and others mentioned here

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


Are you saving enough for college? Here’s what to know — from npr.org by Cory Turner

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?”


The Power of New Value Networks in Revolutionizing Education Systems — from michaelbhorn.substack.com by Michael B. Horn

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.

 

Comparing Online and AI-Assisted Learning: A Student’s View — from educationnext.org by Daphne Goldstein
An 8th grader reviews traditional Khan Academy and its AI-powered tutor, Khanmigo

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.


First Impressions with GPT-4V(ision) — from blog.roboflow.com by James Gallagher; via Donald Clark on LinkedIn

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.


 


The next phase of digital whiteboarding for Google Workspace— from workspaceupdates.googleblog.com

What’s changing

In late 2024, we will wind down the Jamboard whiteboarding app as well as continue with the previously planned end of support for Google Jamboard devices. For those who are impacted by this change, we are committed to help you transition:

    • We are integrating whiteboard tools such as FigJam, Lucidspark, and Miro across Google Workspace so you can include them when collaborating in Meet, sharing content in Drive, or scheduling in Calendar.

The Teacher’s Guide for Transitioning from Jamboard to FigJam — from tommullaney.com by Tom Mullaney


 

Four Scenarios for the Future of Legal Education — from denniskennedy.com by Dennis Kennedy

Scenario 1: Fully Digitalized Law School
Scenario 2: Blended Law School Experience
Scenario 3: Specialized Legal Education
Scenario 4: Decentralized Legal Education

In the decentralized legal education scenario, the traditional model of law schools is disrupted by the emergence of alternative education platforms and micro-credentialing. The concept of a law degree is replaced by a more flexible and personalized approach to legal education. Students can choose from an array of legal courses offered by various providers, including universities, law firms, online platforms, and even government agencies.

 

Evidence Is Mounting That Calculus Should Be Changed. Will Instructors Heed It? — from edsurge.com by Daniel Mollenkamp

Calculus is a critical on-ramp to careers in science, technology, engineering and mathematics (STEM). But getting to those careers means surviving the academic journey.

While there’s been progress of late, it’s been “uneven” and Black, Hispanic and women workers are still underrepresented in some STEM fields. Traditional methods of calculus instruction may be knocking students off the path to these vital occupations, which is why advocates warn that getting diverse students into these careers may require instructional models more responsive to students. Meanwhile, the country is struggling to fill vacancies in related fields like semiconductor manufacturing, despite sizable investments — a feat that may require stabilizing the pipeline.

Good news: There’s mounting evidence that changing calculus instruction works for the groups usually pushed out of STEM. At least, that’s according to a randomized study recently published in the peer-reviewed journal Science.

 

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:

  1. AI as feedback generator
  2. AI as personal tutor
  3. AI as team coach
  4. AI as learner

Recap: Teaching in the Age of AI (What’s Working, What’s Not) — from celt.olemiss.edu by Derek Bruff, visiting associate director

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.


Teaching: Want your students to be skeptical of ChatGPT? Try this. — from chronicle.com by Beth McMurtrie

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:


2023 EDUCAUSE Horizon Action Plan: Generative AI — from library.educause.edu by Jenay Robert and Nicole Muscanell

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.
.

2023-educause-horizon-action-plan-generative-ai


Will Teachers Listen to Feedback From AI? Researchers Are Betting on It — from edsurge.com by Olina Banerji

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.


Embracing weirdness: What it means to use AI as a (writing) tool — from oneusefulthing.org by Ethan Mollick
AI is strange. We need to learn to use it.

But LLMs are not Google replacements, or thesauruses or grammar checkers. Instead, they are capable of so much more weird and useful help.


Diving Deep into AI: Navigating the L&D Landscape — from learningguild.com by Markus Bernhardt

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

 

Higher Ed’s Ruinous Resistance to Change — from chronicle.com by Brian Rosenberg

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.”

 

Preparing Students for the AI-Enhanced Workforce — from insidehighered.com by Ray Schroeder
Our graduating and certificate-completing students need documented generative AI skills, and they need them now.

The common adage repeated again and again is that AI will not take your job; a person with AI skills will replace you. The learners we are teaching this fall who will be entering, re-entering or seeking advancement in the workforce at the end of the year or in the spring must become demonstrably skilled in using generative AI. The vast majority of white-collar jobs will demand the efficiencies and flexibilities defined by generative AI now and in the future. As higher education institutions, we will be called upon to document and validate generative AI skills.


AI image generators: 10 tools, 10 classroom uses — from ditchthattextbook.com by Matt Miller

AI image generators: 10 tools, 10 classroom uses


A Majority of New Teachers Aren’t Prepared to Teach With Technology. What’s the Fix? — from edweek.org by Alyson Klein

Think all incoming teachers have a natural facility with technology just because most are digital natives? Think again.

Teacher preparation programs have a long way to go in preparing prospective educators to teach with technology, according to a report released September 12 by the International Society for Technology in Education, a nonprofit.

In fact, more than half of incoming teachers—56 percent—lack confidence in using learning technology prior to entering the classroom, according to survey data included with the report.


5 Actual Use Cases of AI in Education: Newsletter #68 — from transcend.substack.com by Alberto Arenaza
What areas has AI truly impacted educators, learners & workers?

  1. AI Copilot for educators, managers and leaders
  2. Flipped Classrooms Chatbots
  3. AI to assess complex answers
  4. AI as a language learning tool
  5. AI to brainstorm ideas

AI-Powered Higher Ed — from drphilippahardman.substack.com by  Dr. Philippa Hardman
What a House of Commons round table discussion tells us about how AI will impact the purpose of higher education

In this week’s blog post I’ll summarise the discussion and share what we agreed would be the most likely new model of assessment in HE in the post-AI world.

But this in turn raises a bigger question: why do people go to university, and what is the role of higher education in the twenty first century? Is it to create the workforce of the future? Or an institution for developing deep and original domain expertise? Can and should it be both?


How To Develop Computational Thinkers — from iste.org by Jorge Valenzuela

In my previous position with Richmond Public Schools, we chose to dive in with computational thinking, programming and coding, in that order. I recommend building computational thinking (CT) competency first by helping students recognize and apply the four elements of CT to familiar problems/situations. Computational thinking should come first because it’s the highest order of problem-solving, is a cross-curricular skill and is understandable to both machines and humans. Here are the four components of CT and how to help students understand them.

 

Generative A.I. + Law – Background, Applications and Use Cases Including GPT-4 Passes the Bar Exam – Speaker Deck — from speakerdeck.com by Professor Daniel Martin Katz

 

 

 


Also relevant/see:

AI-Powered Virtual Legal Assistants Transform Client Services — from abovethelaw.com by Olga V. Mack
They can respond more succinctly than ever to answer client questions, triage incoming requests, provide details, and trigger automated workflows that ensure lawyers handle legal issues efficiently and effectively.

Artificial Intelligence in Law: How AI Can Reshape the Legal Industry — from jdsupra.com

 

Next, The Future of Work is… Intersections — from linkedin.com by Gary A. Bolles; via Roberto Ferraro

So much of the way that we think about education and work is organized into silos. Sure, that’s one way to ensure a depth of knowledge in a field and to encourage learners to develop mastery. But it also leads to domains with strict boundaries. Colleges are typically organized into school sub-domains, managed like fiefdoms, with strict rules for professors who can teach in different schools.

Yet it’s at the intersections of seemingly-disparate domains where breakthrough innovation can occur.

Maybe intersections bring a greater chance of future work opportunity, because that young person can increase their focus in one arena or another as they discover new options for work — and because this is what meaningful work in the future is going to look like.

From DSC:
This posting strikes me as an endorsement for interdisciplinary degrees. I agree with much of this. It’s just hard to find the right combination of disciplines. But I supposed that depends upon the individual student and what he/she is passionate or curious about.


Speaking of the future of work, also see:

Centaurs and Cyborgs on the Jagged Frontier — from oneusefulthing.org by Ethan Mollick
I think we have an answer on whether AIs will reshape work…

A lot of people have been asking if AI is really a big deal for the future of work. We have a new paper that strongly suggests the answer is YES.
.

Consultants using AI finished 12.2% more tasks on average, completed tasks 25.1% more quickly, and produced 40% higher quality results than those without. Those are some very big impacts. Now, let’s add in the nuance.

 

From DSC:
In Rick Seltzer’s Daily Briefing for 9-18-23, he ends the briefing with this important point:

The bigger picture: Culture is exceedingly hard to change, especially after trust evaporates in a crisis. And crises can be particularly wrenching when institutions haven’t established cultures of transparency and accountability during good times. Instead, trust continues to erode in a vicious cycle.

And I thought to myself, the scope of Rick’s conclusion could likely be expanded/applied to institutions of higher education as a whole.

 

What Will Determine AI’s Impact on College Teaching? 5 Signs to Watch. — from chronicle.com by Beth McMurtrie (behind a paywall)

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.


Also relevant/see:

An AI and higher education panel — from aiandacademia.substack.com by Bryan Alexander
Live notes

Today I took in a webinar on AI and higher education. The American Association of Colleges and Universities hosted “The AI Revolution: Transforming Higher Education for the Workforce of Tomorrow” and I’d like to share my running notes.


Also relevant/see:

Students’ Perspectives on Using AI — from er.educause.edu by Sarah J. Buszka, Jeremy Cortez, and Isabella Meltzer

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.

 
© 2024 | Daniel Christian