The real issue is not whether centers that support instructional design are necessary, but rather whether they work as productive partners with disciplinary faculty rather than transactional course-production shops.More importantly, as higher education faces the existential challenge of artificial intelligence, CTLs also must become applied research and development hubs focused on making college teaching and learning more successful in a time when more adult education is needed and budgets are tightening. Effective teaching requires the integration of clear content goals with optimal course design, appropriate use of technology, classroom management skills, and well-designed learning spaces. Done well, a center for teaching and learning is a critical asset for a university. Partnering with disciplinary faculty, it provides a foundation for robust diagnosis of barriers to learning, solving instructional problems, and shaping the environment in which teaching happens.
Wednesday, July 15, 2026
Stop investigating, start teaching - B. Jean Madernach, Times Higher Educatioin
Trying to detect whether a student has misused AI in their work is a wasted effort, from which no one benefits, writes B. Jean Mandernach. She proposes a different approach focused on finding out what students truly understand. The detection mindset asks: did this student use AI? It’s a question about authorship, and it leads you into an investigative role most faculty are neither trained nor equipped to fill. The evidence is ambiguous, the standard of proof is high, and the outcome is usually inconclusive. The entire process is adversarial. It positions you against your student before you’ve had a single conversation. The verification mindset asks something different: does this student understand what they submitted? That question is entirely within your professional authority to answer. It doesn’t require a detector or a formal complaint. It requires a conversation with the student, and in most cases, a short one. This is not a workaround or a compromise. It is a more rigorous form of assessment than a plagiarism score.
https://www.timeshighereducation.com/campus/stop-investigating-start-teaching
Tuesday, July 14, 2026
ISTELive 26: Critical Thinking in an AI-Driven Information Ecosystem - Julia Gilban-Cohen, GovTech
During a session on news literacy at the International Society for Technology in Education (ISTE) conference Sunday, panelists posed a question to a room full of educators: Has a student ever cited ChatGPT, TikTok or any kind of social media as a legitimate source in a classroom assignment? A slew of hands rose immediately. The response underscored what panelists deemed a growing challenge for schools, as students increasingly have instant access to AI-generated information, but many lack the skills to critically evaluate what they encounter. “That is rather scary,” said Kim Zajac, a certified speech and language pathologist and audiologist who has over two decades of experience in Massachusetts schools. “[Students] are looking at AI like this is the gospel, this is truth ... [and] they are vulnerable to ... building habits that are misleading and dangerous.”
Preparing students for an AI-driven future - Kaitlin Brothers, Missouri S&T
During the four-week course, a classroom full of Kummer Vanguard Scholars learned how to create AI-powered avatars for marketing and business communication. “The goal of the course was not simply to teach students how to use AI tools, but to help them think critically about how emerging AI technologies can be used to communicate ideas, tell stories and engage audiences,” Reardon says. Reardon’s course explored how AI tools can support business communication, marketing and storytelling. “I’ve always been fascinated by the potential of AI and how that could assist us not only in higher education, but in business,” he says. “As a former small business owner, I saw a lot of possibilities.”
Monday, July 13, 2026
They built the world’s most powerful AI. They’re facing a mystery they can’t explain - Nitasha Tiku, Washington Post
Anthropic, Google and Meta have hired computer scientists, neuroscientists and philosophers to study what some in the industry think may become a moral crisis. “We keep finding things that are mysterious, even unsettling,” Olah said of Anthropic’s AI systems. “We find evidence of introspection [and] states that functionally mirror joy, satisfaction, fear, grief and unease.” (Leo took a different stance, writing that “so-called artificial intelligences do not undergo experiences.”) Meta’s chief AI officer, Alexandr Wang, recently said the company wants to be nice to its AI creations. “One of the things that we really care about is how can we develop the models and deploy the models in a way that is thoughtful about their subjective feeling,” he said on the “Core Memory” podcast. Neuroscientists and brain experts are generally skeptical that today’s AI models are or could soon be conscious.
The AI Lane to Watch - Matt Wolfe, Future Tools
Large Language Models (the ones powering ChatGPT, Claude, Gemini) are trained on text. They predict the next word in a sentence—great for writing, summarizing, and reasoning over language.
Large Quantitative Models are trained on numerical data and scientific equations from real-world lab experiments. They predict things like how strongly a molecule binds to a catalyst surface, or which drug candidates are worth testing in the lab, making them useful for non-text use cases.
LQMs are already integrated with Claude, and now they’re coming to Gemini. The first two models hitting Google Cloud Marketplace are AQCat (Q3 2026, for materials and catalyst discovery: think batteries, semiconductors, sustainable fuels) and AQPotency (later this year, for drug discovery). Researchers can prompt in plain English and have Gemini hand off the actual scientific calculations to a physics-grounded model underneath. The pattern is basically: LLMs as the interface, LQMs as the engine.
Sunday, July 12, 2026
The seven operating truths of AI-native companies - McKinsey
These are not isolated experiments. Over the past several months, we have met with the tech and business leaders at 15 AI-centric companies—spanning continents, industries, and stages of development, from four-person start-ups to established global platforms—to learn what it takes to make AI capabilities truly deliver. We expected to hear 15 different stories. Instead, this diverse group of businesses, independent of one another, seemed to converge on the same fundamental insights about what it takes to successfully place AI at the center of the organization. That convergence is the story.
Will AI in education succeed? - Brad Olsen and Jobin Thomas, Brookings
In May 1959, the first PLATO (Programmed Logic for Automated Teaching Operations) system was unveiled at the University of Illinois. This means that last month was the 67th anniversary of the birth of Computer-Assisted Instruction (CAI). Such an event merits a look at technology in education today. Many people are currently either for or against generative artificial intelligence (AI) in education—a stark binary that misses the complexity and inevitability of the current technological revolution. The success or failure of using technology for education (EdTech) is only partly about the technology itself. What matters more are the conditions underlying EdTech. EdTech is a tool, not a standalone solution, and without a proper support system in place, it will not succeed.
Saturday, July 11, 2026
I landed a Big Tech AI job. Treating my career like a science lab helped me overcome my fear of learning - As told to Charissa Cheong, Business Insider
This as-told-to essay is based on a conversation with Nitya Kumar, 25, an Adobe employee who lives in India. The following has been edited for length and clarity. I landed a product design role at Meta straight out of college in 2022. By 2024, I saw the industry pivoting toward AI and wanted to learn new AI design skills. During this process, I stopped seeing my career as a ladder with a focus on moving upward. In my view, all work and no play keeps the Big Tech offers away, so I started treating my career like a science lab, giving myself the freedom to experiment. This helped me overcome my fear of learning a new technology and land a role working with AI at Adobe.
AI Skills Gap: What Industries Are Hiring AI Talent in 2026 - Boston University
The hardest part of the AI boom is no longer building the technology. It is finding people who can put it to work. Across nearly every sector, demand for AI talent is running well ahead of supply, and the gap is reshaping who gets hired, what they are paid, and which skills are worth investing in. If you are weighing a move into AI, that imbalance is the opportunity. Here is where the demand is concentrated in 2026, what those roles pay, and how to choose a path that fits the industry you are in or the one you want to enter.
Friday, July 10, 2026
Stanford graduates rethink their futures as AI transforms tech - Lily Jamali, BBC
Stanford occupies a unique position in the American tech ecosystem. It's regarded as a hotbed of innovation and resides in the shadow of some of the most influential Big Tech companies on the planet, including many pioneers in the AI field. Its elite students enter the job market with an undeniable edge. Yet even there, the backlash was inescapable. The BBC spoke to Stanford graduates shortly after Pichai finished his address and they expressed a wide range of views on AI. Some are scared. Some are excited. But nearly everyone agrees that AI is already changing the world around them, whether they like it or not.
Teaching, AI, and the Human Core of Education : The Future Worth Defending - Armand Doucet
For teachers, their unions, and the policymakers who shape the conditions in which they work, the question is no longer whether AI will shape education, but how that shaping will be governed. The purpose of this report is to take stock of that reality: to identify what has changed, what remains essential, and what education systems must now do differently if AI is to be integrated responsibly, based on needs and governed in the public interest. Its central claim is straightforward. AI is not disrupting the purpose of education. It is disrupting the conditions under which that purpose can be realized. What follows therefore examines what has changed, what has not, and what must now be intentionally rebuilt, protected, and governed.
Thursday, July 09, 2026
International Perspectives on AI in Higher Education - University of Bonn
Artificial intelligence is rapidly becoming a key factor in higher education, opening up new possibilities for learning, teaching and examinations while also leaving universities grappling with fundamental strategic, ethical and organizational questions. Hosted by the University of Bonn from June 10 to 12, 2026, the annual summit of the Global Universities for Societal Impact (GUSI) international network focused on how higher-education institutions can shape this change responsibly. Representatives from the five partner universities debated how AI is transforming research and teaching and what answers higher-education institutions need to find to address these trends.
Examining the influence of AI in higher education - Amy Juravich, WOSU
Last year, the California State University System entered into a contract with OpenAI to provide students, faculty and staff with ChatGPT Edu. The contract was recently renewed despite many students and professor encouraging the university not to continue the deal. Just recently, here in Ohio, the University of Cincinnati did the same, offering BearcatGPT to all their students and faculty for free. Ohio State University is no exception. The AI Fluency initiative is in full swing and has recently broadened into the Arts and Humanities AI Institute. Should universities conform to AI in academic spaces? What are the potential negative consequences of AI use in higher education?
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