This week, as I kick off the 20th cohort of my AI-Learning Design bootcamp, I decided to do some analysis of the work habits of the hundreds of amazing AI-embracing instructional designers who I’ve worked with over the last year or so.
My goal was to answer the question: which AI tools do we use most in the instructional design process, and how do we use them?
Here’s where we are in September, 2024:
…
Developing Your Approach to Generative AI — from scholarlyteacher.com by Caitlin K. Kirby, Min Zhuang, Imari Cheyne Tetu, & Stephen Thomas (Michigan State University)
As generative AI becomes integrated into workplaces, scholarly work, and students’ workflows, we have the opportunity to take a broad view of the role of generative AI in higher education classrooms. Our guiding questions are meant to serve as a starting point to consider, from each educator’s initial reaction and preferences around generative AI, how their discipline, course design, and assessments may be impacted, and to have a broad view of the ethics of generative AI use.
AI technology tools hold remarkable promise for providing more accessible, equitable, and inclusive learning experiences for students with disabilities.
The Voice of the Online Learner report highlights the journey of online learners, and the vital role education plays in their personal and professional growth and development. This year’s report compiled responses from over 3,400 prospective, current, and recently graduated online learners.
Key findings from this year’s Voice of the Online Learner report include:
Decision Factors for Online Students: When evaluating online programs, the key decision for students is cost, with 86% saying it’s extremely or very important. After cost, 84% said accreditation is most important, 75% said program concentrations, followed by 68% of respondents who said it was the time it took to achieve a degree. 38% selected the lowest cost program they evaluated (up from 29% in 2023).
Perception of Online Programs: Students see online programs as equally valid or better at meeting their needs than on-campus degree programs. 83% of respondents prefer the flexibility of online programs over hybrid or on-campus options, while 90% feel online programs are comparable to or better than an on-campus degree. 83% (up from 71% last year) want no on campus requirement.
Degree ROI: 92% of students who graduated from online degree programs reported tangible benefits to their career, including 44% who received a salary increase.
Value of the Degree: Career outcomes continue to be very important for students pursuing their degree.86% felt their degrees were important in achieving their career goals, and 61% of online undergraduates are likely to enroll in additional online degree programs to stay competitive.
Importance of Local Programs: Attending a university or college in the state where the student lives and works is also an important decision factor, with 70% enrolled at a higher education institution in the state where they live and/or work. These students say that local proximity creates greater trust, and that they also want to ensure the programs meet local licensing or accreditation requirements, when relevant.
Demographics: The average age for online students enrolled in undergraduate programs is 36 years old, while the average age for students enrolled in graduate programs is 38 years old. Of the students enrolled in undergraduate programs, 40% are first-generation college students.
Upskilling is lifelong: 86% of graduated and currently enrolled students are likely to do another online program in the future to upskill.
Generative AI is a concern: Students want guidance on generative AI, but 75% reported they have received none. 40% of students think it will affect their career positively and 40% believe it will impact them negatively. Nearly half (48%) have used it to help them study.
AI can help educators focus more on human interaction and critical thinking by automating tasks that consume time but don’t require human empathy or creativity.
Encouraging students to use AI as a tool for learning and creativity can significantly boost their engagement and self-confidence, as seen in examples from student experiences shared in the discussion.
The speakers discuss various aspects of AI, including its potential to augment human intelligence and the need to focus on uniquely human competencies in the face of technological advancements. They also emphasize the significance of student agency, with examples of student-led initiatives and feedback sessions that reveal how young learners are already engaging with AI in innovative ways. The episode underscores the necessity for educators and administrators to stay informed and actively participate in the ongoing dialogue about AI to ensure its effective and equitable implementation in schools.
AI can be a powerful tool to break down language, interest, and accessibility barriers in the classroom, making learning more inclusive and engaging.
Incorporating AI tools in educational settings can help build essential skills that AI can’t replace, such as creativity and problem-solving, preparing students for future job markets.
86% of students globally are regularly using AI in their studies, with 54% of them using AI on a weekly basis, the recent Digital Education Council Global AI Student Survey found.
ChatGPT was found to be the most widely used AI tool, with 66% of students using it, and over 2 in 3 students reported using AI for information searching.
Despite their high rates of AI usage, 1 in 2 students do not feel AI ready. 58% reported that they do not feel that they had sufficient AI knowledge and skills, and 48% do not feel adequately prepared for an AI-enabled workplace.
The Post-AI Instructional Designer— from drphilippahardman.substack.com by Dr. Philippa Hardman How the ID role is changing, and what this means for your key skills, roles & responsibilities
Specifically, the study revealed that teachers who reported most productivity gains were those who used AI not just for creating outputs (like quizzes or worksheets) but also for seeking input on their ideas, decisions and strategies.
Those who engaged with AI as a thought partner throughout their workflow, using it to generate ideas, define problems, refine approaches, develop strategies and gain confidence in their decisions gained significantly more from their collaboration with AI than those who only delegated functional tasks to AI.
Leveraging Generative AI for Inclusive Excellence in Higher Education — from er.educause.edu by Lorna Gonzalez, Kristi O’Neil-Gonzalez, Megan Eberhardt-Alstot, Michael McGarry and Georgia Van Tyne Drawing from three lenses of inclusion, this article considers how to leverage generative AI as part of a constellation of mission-centered inclusive practices in higher education.
The hype and hesitation about generative artificial intelligence (AI) diffusion have led some colleges and universities to take a wait-and-see approach.Footnote1 However, AI integration does not need to be an either/or proposition where its use is either embraced or restricted or its adoption aimed at replacing or outright rejecting existing institutional functions and practices. Educators, educational leaders, and others considering academic applications for emerging technologies should consider ways in which generative AI can complement or augment mission-focused practices, such as those aimed at accessibility, diversity, equity, and inclusion. Drawing from three lenses of inclusion—accessibility, identity, and epistemology—this article offers practical suggestions and considerations that educators can deploy now. It also presents an imperative for higher education leaders to partner toward an infrastructure that enables inclusive practices in light of AI diffusion.
An example way to leverage AI:
How to Leverage AI for Identity Inclusion Educators can use the following strategies to intentionally design instructional content with identity inclusion in mind.
Provide a GPT or AI assistant with upcoming lesson content (e.g., lecture materials or assignment instructions) and ask it to provide feedback (e.g., troublesome vocabulary, difficult concepts, or complementary activities) from certain perspectives. Begin with a single perspective (e.g., first-time, first-year student), but layer in more to build complexity as you interact with the GPT output.
Gen AI’s next inflection point: From employee experimentation to organizational transformation — from mckinsey.com by Charlotte Relyea, Dana Maor, and Sandra Durth with Jan Bouly As many employees adopt generative AI at work, companies struggle to follow suit. To capture value from current momentum, businesses must transform their processes, structures, and approach to talent.
To harness employees’ enthusiasm and stay ahead, companies need a holistic approach to transforming how the whole organization works with gen AI; the technology alone won’t create value.
Our research shows that early adopters prioritize talent and the human side of gen AI more than other companies (Exhibit 3). Our survey shows that nearly two-thirds of them have a clear view of their talent gaps and a strategy to close them, compared with just 25 percent of the experimenters. Early adopters focus heavily on upskilling and reskilling as a critical part of their talent strategies, as hiring alone isn’t enough to close gaps and outsourcing can hinder strategic-skills development.Finally, 40 percent of early-adopter respondents say their organizations provide extensive support to encourage employee adoption, versus 9 percent of experimenter respondents.
Change blindness — from oneusefulthing.org by Ethan Mollick 21 months later
I don’t think anyone is completely certain about where AI is going, but we do know that things have changed very quickly, as the examples in this post have hopefully demonstrated. If this rate of change continues, the world will look very different in another 21 months. The only way to know is to live through it.
Over the subsequent weeks, I’ve made other adjustments, but that first one was the one I asked myself:
What are you doing?
Why are you doing it that way?
How could you change that workflow with AI?
Applying the AI to the workflow, then asking, “Is this what I was aiming for? How can I improve the prompt to get closer?”
Documenting what worked (or didn’t). Re-doing the work with AI to see what happened, and asking again, “Did this work?”
So, something that took me WEEKS of hard work, and in some cases I found impossible, was made easy. Like, instead of weeks, it takes 10 minutes. The hard part? Building the prompt to do what I want, fine-tuning it to get the result. But that doesn’t take as long now.
Using generative artificial intelligence (GenAI) tools such as ChatGPT, Gemini, or CoPilot as intelligent assistants in instructional design can significantly enhance the scalability of course development. GenAI can significantly improve the efficiency with which institutions develop content that is closely aligned with the curriculum and course objectives. As a result, institutions can more effectively meet the rising demand for flexible and high-quality education, preparing a new generation of future professionals equipped with the knowledge and skills to excel in their chosen fields.1 In this article, we illustrate the uses of AI in instructional design in terms of content creation, media development, and faculty support. We also provide some suggestions on the effective and ethical uses of AI in course design and development. Our perspectives are rooted in medical education, but the principles can be applied to any learning context.
… Table 1 summarizes a few low-hanging fruits in AI usage in course development. .
Table 1. Types of Use of GenAI in Course Development
Practical Use of AI
Use Scenarios and Examples
Inspiration
Exploring ideas for instructional strategies
Exploring ideas for assessment
Course mapping
Lesson or unit content planning
Supplementation
Text to audio
Transcription for audio
Alt text auto-generation
Design optimization (e.g., using Microsoft PPT Design)
10 Ways Artificial Intelligence Is Transforming Instructional Design — from er.educause.edu by Rob Gibson Artificial intelligence (AI) is providing instructors and course designers with an incredible array of new tools and techniques to improve the course design and development process. However, the intersection of AI and content creation is not new.
I have been telling my graduate instructional design students that AI technology is not likely to replace them any time soon because learning and instruction are still highly personalized and humanistic experiences. However, as these students embark on their careers, they will need to understand how to appropriately identify, select, and utilize AI when developing course content. Examples abound of how instructional designers are experimenting with AI to generate and align student learning outcomes with highly individualized course activities and assessments. Instructional designers are also using AI technology to create and continuously adapt the custom code and power scripts embedded into the learning management system to execute specific learning activities.Footnote1 Other useful examples include scripting and editing videos and podcasts.
Here are a few interesting examples of how AI is shaping and influencing instructional design. Some of the tools and resources can be used to satisfy a variety of course design activities, while others are very specific.
The world of a medieval stone cutter and a modern instructional designer (ID) may seem separated by a great distance, but I wager any ID who upon hearing the story I just shared would experience an uneasy sense of déjà vu. Take away the outward details, and the ID would recognize many elements of the situation: the days spent in projects that fail to realize the full potential of their craft, the painful awareness that greater things can be built, but are unlikely to occur due to a poverty of imagination and lack of vision among those empowered to make decisions.
Finally, there is the issue of resources. No stone cutter could ever hope to undertake a large-scale enterprise without a multitude of skilled collaborators and abundant materials. Similarly, instructional designers are often departments of one, working in scarcity environments, with limited ability to acquire resources for ambitious projects and — just as importantly — lacking the authority or political capital needed to launch significant initiatives. For these reasons, instructional design has long been a profession caught in an uncomfortable stasis, unable to grow, evolve and achieve its full potential.
That is until generative AI appeared on the scene. While the discourse around AI in education has been almost entirely about its impact on teaching and assessment, there has been a dearth of critical analysis regarding AI’s potential for impacting instructional design.
We are at a critical juncture for AI-augmented learning. We can either stagnate, missing opportunities to support learners while educators continue to debate whether the use of generative AI tools is a good thing, or we can move forward, building a transformative model for learning akin to the industrial revolution’s impact.
Too many professional educators remain bound by traditional methods. The past two years suggest that leaders of this new learning paradigm will not emerge from conventional educational circles. This vacuum of leadership can be filled, in part, by instructional designers, who are prepared by training and experience to begin building in this new learning space.
Staying current and relevant is essential for institutions in today’s rapidly evolving higher education landscape. However, innovative work cannot be accomplished in isolation.
On this episode, Bryan Benjamin, Executive Director of The Ivey Academy and Amrit Ahluwalia, Executive Director of Continuing Studies at Western University, discusses the importance of institutional collaboration and creating a scalable lifelong learning ecosystem.
Colleges Race to Ready Students for the AI Workplace — from wsj.com by Milla Surjadi (behind a paywall) Non-techie students are learning basic generative-AI skills as schools revamp their course offerings to be more job-friendly
College students are desperate to add a new skill to their résumés: artificial intelligence.
The rise of generative AI in the workplace and students’ demands for more hirable talents are driving schools to revamp courses and add specialized degrees at speeds rarely seen in higher education. Schools are even going so far as to emphasize that all undergraduates get a taste of the tech, teaching them how to use AI in a given field—as well as its failings and unethical applications.
The Skills Of The Future Are Clear: Ability To Drive Change I had an interesting set of meetings today with a group of HR leaders we talk with every few weeks. Every single one of the CHROs and other leaders told us they are investing in “change management” and “business transformation” skills in their people. What does that mean?
It means just this. While we all want more engineers, manufacturing gurus, scientists, and sales and marketing experts in our companies, the biggest set of “skills” we need is the “ability to drive change.” That particular skill is quite complex, learned over time, and massively important at the moment. And that led me to my final point.
Some of the nation’s biggest tech companies have announced efforts to reskill people to avoid job losses caused by artificial intelligence, even as they work to perfect the technology that could eliminate millions of those jobs.
It’s fair to ask, however: What should college students and prospective students, weighing their choices and possible time and financial expenses, think of this?
The news this spring was encouraging for people seeking to reinvent their careers to grab middle-class jobs and a shot at economic security.
For too long, students with learning disabilities have struggled to navigate a traditional education system that often fails to meet their unique needs. But what if technology could help bridge the gap, offering personalized support and unlocking the full potential of every learner?
Artificial intelligence (AI) is emerging as a powerful ally in special education, offering many opportunities to create more inclusive and effective learning experiences for students with diverse learning profiles.
*SearchGPT
*Smaller & on-device (phones, glasses) AI models
*AI TAs
*Access barriers decline, equity barriers grow
*Claude Artifacts and Projects
*Agents, and Agent Teams of a million+
*Humanoid robots & self-driving cars
*AI Curricular integration
*Huge video and video-segmentation gains
*Writing Detectors — The final blow
*AI Unemployment, Student AI anxiety, and forward-thinking approaches
*Alternative assessments
Since then, two more pieces have been widely shared including this piece from Inside Higher Ed by Kathryn Palmer (and to which I was interviewed and mentioned in) and this piece from Chronicle of Higher Ed by Christa Dutton. Both pieces try to cover the different sides talking to authors, scanning the commentary online, finding some experts to consult and talking to the publishers. It’s one of those things that can feel like really important and also probably only to a very small amount of folks that find themselves thinking about academic publishing, scholarly communication, and generative AI.
In one respect, we already have a partial answer. Over the last thirty years, there has been a dramatic shift from a teaching-centered to a learning-centered education model. High-impact practices, such as service learning, undergraduate research, and living-learning communities, are common and embraced because they help students see the real-world connections of what they are learning and make learning personal.11
Therefore, I believe we must double down on a learning-centered model in the age of AI.
The first step is to fully and enthusiastically embrace AI.
…
The second step is to find the “jagged technological frontier” of using AI in the college classroom.
Gig Work, College Skills — from the-job.beehiiv.com by Paul Fain New partnership lets college students use classroom learning for freelance roles.
Bringing Freelancing to College Education
A new partnership between Podium Education, an experiential learning company, and the freelance platform Upwork aims to let more students use the skills they’ve learned in class—and to make money now for doing so.
The Big Idea: The partnership, announced today, is an extension of the work that Podium already does with more than 70 universities. Through their Global Career Accelerator, students learn marketing, data analytics, or coding skills for credit and get the chance to work on a specific project with companies like Intel and the nonprofit charity: water. With the new partnership, students who complete the coursework will get customized access to and onboarding with Upwork, as well as coaching on how to be successful in freelancing.
As the needs of the modern workforce evolve at an unprecedented rate, durable, or “soft,” skills are often eclipsing demand for sought-after technical skills in high-demand jobs across industry sectors, geography, and educational level.
Through research, collaboration, and feedback from more than 800 educators, workforce professionals, industry leaders, and policymakers, America Succeeds—a leading educational policy and advocacy group—has developed Durable Skills and the Durable Skills Advantage Framework to provide a common language for the most in-demand durable skills. With 85% of career success being dependent on durable skills, this framework bridges the gap between the skills students are taught in school and evolving workforce needs.
Over the last few years, we’ve been covering New Pathways, which we think of as a framework for school leaders and community members to create supports and systems that set students up for success in what’s next. This might be career exploration, client-connected projects, internships, or entrepreneurial experiences.
But what it really comes down to is connecting learners to real-world experiences and people and helping them articulate the skills that they gain in the process. Along the way, we began to talk a lot about green jobs. Many of the pre-existing pathways in secondary schools point towards CTE programs and trades, which are more in demand than they’ve been in decades.
This coincides with a pivotal moment in the arc of infrastructure redesign and development, one that heavily emphasizes clean energy trajectories and transferable skills. Many of these jobs we refer to as green pathways or requiring some of these green skills.
One leading organization in this space is the Interstate Renewable Energy Council or IREC. I got to sit down with Cynthia Finley, the Vice President of Workforce Strategy at IREC to talk about green pathways and what IREC is doing to increase awareness and exposure of green jobs and skills.
We’re starting to roll out advanced Voice Mode to a small group of ChatGPT Plus users. Advanced Voice Mode offers more natural, real-time conversations, allows you to interrupt anytime, and senses and responds to your emotions. pic.twitter.com/64O94EhhXK
Why it matters: AI is slowly shifting from a tool we text/prompt with, to an intelligence that we collaborate, learn, and grow with. Advanced Voice Mode’s ability to understand and respond to emotions in real-time convos could also have huge use cases in everything from customer service to mental health support.
“Every single restaurant, every single website will probably, in the future, have these AIs …” Huang said.
“…just like every business has an email address and a website and a social media account, I think, in the future, every business is going to have an AI,” Zuckerberg responded.
…
More broadly, the advancement of AI across a broad ecosystem promises to supercharge human productivity, for example, by giving every human on earth a digital assistant — or assistants — allowing people to live richer lives that they can interact with quickly and fluidly.
DC: Nvidia continues 2get rocked as I think people are taking their gains & getting nervous about AI’s ability 2deliver healthy ROI’s. But I think co’s will let many people go as a result of various AI’s impacts. They WILL get their ROI. But it may be at a great cost to some pple
From DSC: Today was a MUCH better day for Nvidia however (up 12.81%). But it’s been very volatile in the last several weeks — as people and institutions ask where the ROI’s are going to come from.
DC: What do you think about this? What about if this occurred at *your* place of employment? https://t.co/CWc09Cm7n1
This last wave of AI releases is truly making us more capable than ever.
Here are 10 amazing examples of my favorite new tool ?
This is Claude 3.5 Sonnet with Artifacts, a new feature that allows people to go from a super simple prompt to immediate previews of games, code… pic.twitter.com/w4kkT25fch
9 compelling reasons to learn how to use AI Chatbots — from interestingengineering.com by Atharva Gosavi AI Chatbots are conversational agents that can act on your behalf and converse with humans – a futuristic novelty that is already getting people excited about its usage in improving efficiency.
7. Accessibility and inclusivity
Chatbots can be designed to support multiple languages and accessibility needs, making services more inclusive. They can cater to users with disabilities by providing voice interaction capabilities and simplifying access to information. Understanding how to develop inclusive chatbots can help you contribute to making technology more accessible to everyone, a crucial aspect in today’s diverse society.
8. Future-proofing your skills
AI and automation are the future of work. Having the skills of building AI chatbots is a great way to future-proof your skills, and given the rising trajectory of AI, it’ll be a demanding skill in the market in the years to come. Staying ahead of technological trends is a great way to ensure you remain relevant and competitive in the job market.
Top 7 generative AI use cases for business— from cio.com by Grant Gross Advanced chatbots, digital assistants, and coding helpers seem to be some of the sweet spots for gen AI use so far in business.
Many AI experts say the current use cases for generative AI are just the tip of the iceberg. More uses cases will present themselves as gen AIs get more powerful and users get more creative with their experiments.
However, a handful of gen AI use cases are already bubbling up. Here’s a look at the most popular and promising.
The landscape of education is on the brink of a profound transformation, driven by rapid advancements in artificial intelligence. This shift was highlighted recently by Andrej Karpathy’s announcement of Eureka Labs, a venture aimed at creating an “AI-native” school. As we look ahead, it’s clear that the integration of AI in education will reshape how we learn, teach, and think about schooling altogether.
…
Traditional textbooks will begin to be replaced by interactive, AI-powered learning materials that adapt in real-time to a student’s progress.
…
As we approach 2029, the line between physical and virtual learning environments will blur significantly.
Curriculum design will become more flexible and personalized, with AI systems suggesting learning pathways based on each student’s interests, strengths, and career aspirations. … The boundaries between formal education and professional development will blur, creating a continuous learning ecosystem.
.
Solving chronic absenteeism involves tackling big structural problems like transportation and infrastructure. But we also have to make our schools places where young people want to learn. Too many teens, in particular, had negative feelings about school even before the pandemic. Yale researchers conducting a national survey of high school students found most teens spent their days “tired,” “stressed,” and “bored.” Fewer than 3 in 100 reported feeling interested while in school.
Decades of research prove that students learn more when they experience high levels of academic engagement and social belonging in school.
Students at all four schools experience internships, work-based learning and partnerships with community organizations, which they said make classwork feel more relevant.
