Flipped Classrooms and Academic Achievement — from learningscientists.org by Megan Sumeracki

There are actually many, many ways to design a flipped classroom, and it has been fascinating to learn about the ways my colleague typically structures her hybrid, flipped-classroom courses. As a result, we’ve been able to engage in really interesting conversations about the best approach for this particular course, and why. As a result of some of these discussions, I came across a few recent meta-analyses related to the effects of flipped classrooms, the results of which I thought were worth sharing here (1, 2, 3).

 

 

Anthropic, NVIDIA Move AI Agents Deeper into Scientific Workflows — from campustechnology.com by John K. Waters

Key Takeaways

  • Anthropic’s Claude Science beta and NVIDIA’s BioNeMo Agent Toolkit show AI agents moving beyond general productivity into specialized scientific research workflows.
  • The companies are emphasizing auditability and reproducibility, including preserved code, environments, message history, reviewer agents, and integration with existing research tools.
  • For enterprises and research teams, the key test will be whether agentic AI can produce traceable, reliable results while keeping humans in control of sensitive data, compute, and scientific judgment.
 

Scan More than 60 Million Stars in the Most Detailed Photo of the Milky Way Ever Taken — from thisiscolossal.com by Kate Mothes and The European Space Agency (ESA)

In March 2025, the Euclid mission led by the The European Space Agency (ESA) enabled scientists to capture the highest resolution image ever taken of the dense, glowing center of the Milky Way galaxy.
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Stanford Online Launches Immersive Learning Studio — from campustechnology.com by Matt Jones

Key Takeaways

  • Stanford Online celebrated its 30th anniversary by launching a new immersive learning studio that combines VR, AR, and AI technologies to create more engaging and personalized educational experiences.
  • The studio provides faculty with advanced production tools — including a 4K LED wall, cinematic cameras, AI-enabled workflows, and extensive editing and storage infrastructure — to develop innovative learning content at scale.
  • University leaders see the studio as a major step toward expanding faculty-led, research-based education globally, leveraging AI and immersive technologies to reach learners in ways previously not possible.
 

3 Retrieval Games to Try in Your High School Classroom — from edutopia by Andrew Atherton
These activities make reviewing content fun, so they can really motivate students to cement their learning.

These games can start or end the lesson, and they sometimes function as a transition within the lesson between topics. I don’t need to use them any longer, but I choose to use the following three games simply because they work really well. They can be used in any class and require very little (if any) preparation. These examples are drawn from the English classroom, but they could be adapted to suit most subjects.


Focusing Attention With a Student-Led Recall Activity — from edutopia.org
By providing every student with an opportunity to actively remember yesterday’s lesson, teachers can set the stage for today’s success.

By asking students to recall information on their own and then compare ideas with classmates, Bechard creates opportunities for each of them to engage with the content.

The process has the added benefit of strengthening retention: “When we remember something we had initially forgotten,” Lee says, “it is coming back into our working memory. It is having another opportunity to go into long-term memory. And so every time that happens, we are actually creating a stronger memory trace for that information.”

By building in a brief, intentional routine at the start of class, Bechard helps students reactivate prior learning, reconnect with the text, and begin each lesson with their attention focused, ready to learn.


How Free Play Supports Attention in Elementary School — from edutopia.org by Cynthia Michelini
Taking a short break outside allows students to reconnect with the world and refocus when it’s time to go back to the classroom.

The breaks were only five to 10 minutes long, and my intention was to ensure that the time outside was never structured, apart from a few guiding principles. Rule one: No teacher instruction. I didn’t want to give my students any direction other than how to be safe outside. Rule two: I encouraged them not to organize anything. Rule three: Just simply take a break. The results of this seemingly simple target surprised me.

First of all, my students’ attention span increased significantly. While this wasn’t a formal research project, trust me when I say that after 23 years of experience, I was shocked to realize how taking kids outside for a short period of time frequently can help support their focus in the classroom.


The IKEA Effect: You Built It, You’re Invested in It — from edutopia.org by Cathleen Beachboard, Nick Brousse
People become more invested when they help shape the systems around them, and teachers and school leaders can use that to create a strong school culture.

The difference is rarely the quality of the system itself. It’s whether the people affected by it helped build it. Psychologists call this the IKEA effect: our tendency to place greater value on things we help create. In one fascinating series of studies, researchers found that even young children valued objects they built more highly than identical objects made by someone else.

This sense of value is not explained simply by ownership. Children still value their creations more, even when they cannot keep them. It’s not explained by effort alone, either—more work doesn’t automatically create more attachment.

Instead, the researchers proposed something deeper: People become emotionally connected to what they help create because it begins to feel tied to their sense of identity. That finding may explain far more about school culture than we realize.

 

Two years ago, AI broke assessment. Now, it’s helping us to reinvent it. — from linkedin.com by Dr. Philippa Hardman


Also from Dr. Hardman, see:


A new study shows AI helped deliver 1.5 years of maths progress in 8 weeks — here’s how. — from linkedin.com by Dr. Philippa Hardman

…a new study shows AI helped deliver 1.5 years of maths progress in 8 weeks — here’s how.

Google DeepMind just shared the results of a randomised trial involving 1,763 students. Half used Gemini’s “Guided Learning” to learn maths; half didn’t.

The result: the group working with AI gained the equivalent of 1.2 to 1.7 years of extra progress compared to those who didn’t.

It’s tempting to read this as “Gemini’s Guided Learning mode works!” But the key point here is that Gemini didn’t work alone….

Look closer, and what made the difference wasn’t just the tech — it was a great teacher making expert use of it.

 

Pinpoint, Explained — from wondertools.substack.com by Jeremy Caplan
A guide to Google’s free tool, now open to all


.Jeremy prompted ChatGPT to generate illustrations in his post.

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Learn about Pinpoint— from support.google.com

Pinpoint is an AI-powered research platform designed to help journalists and academics analyze large collections of documents. With Pinpoint, you can:

  • Analyze massive collections: Easily search, filter, transcribe and organize thousands of documents, including PDFs, images, and audio files.
  • Leverage generative AI: Use Gemini’s capabilities to answer research questions together with supporting evidence found in your documents.
  • Foster collaborative research: share your work with colleagues and tackle large scale projects as a team. You can also publicly share – supporting community-driven research.

For assistance with Pinpoint, please consult our Community Forum or you can contact our support team.

 

What Michigan schools reveal about reversing chronic absenteeism — from hechingerreport.org by Jill Barshay
Time-intensive home visits show promise

Absenteeism is a huge and seemingly intractable problem for the nation’s public schools. And Michigan has one of the worst attendance rates in the country.

Yet a new study released in May offers hope. Researchers found that some Michigan schools appear to be substantially better than others at getting students to show up, and identified one intervention — frequent home visits to families whose children are absent from class — that was used more often by schools making a difference.

The findings are a reminder that “best practices” recommendations often overstate what researchers actually know. Schools can make a meaningful difference in attendance, but identifying genuinely successful schools is hard, isolating why they succeed is even harder, and simple solutions rarely hold up under scrutiny.

 

Inside the latest global research on school cellphone bans — from hechingerreport.org by Jill Barshay
First wave of studies raises questions about other digital distractions and cellphones at home

But the first wave of rigorous research on those policies — including two major U.S. studies — does not point neatly in one direction. Some studies have found modest academic gains from cellphone restrictions. Others have found little to no effect on test scores, even when student phone use dropped sharply. Some studies suggest benefits for low-achieving students, others for girls, and still others for boys. In some places, attendance or student well-being improved. In others, they didn’t.

The scientific process can be messy. Cultural differences may explain why the bans are more effective in some places than others. But almost any education reform will get different results in different places, even within a single country. And the current confusion may also stem from how difficult it is to study cellphone bans in the real world.

Ideally, researchers would randomly assign some students to surrender their phones while others kept them, and then measure the effect on academic performance — the equivalent of a clinical trial for an education policy. But those experiments are difficult to enforce in schools, and so far only one study, conducted among college students in India, has attempted a randomized controlled trial. It produced a notably strong improvement in course grades for lower achieving students.

Instead, most studies rely on rougher real world comparisons that capture only partial effects of cellphone restrictions.

 

A New Era of Security: Frontier AI Defense — from paloaltonetworks.com by Sam Rubin

For the last several months, we have had early, unbounded access to the latest frontier AI models. What we’ve seen from that vantage point has made it clear that the window for organizations to get ahead of what’s coming is shorter than most leaders realize.

We have moved past the era of incremental AI improvements into a threat landscape shift. Our testing has revealed a step-change in capability that demonstrates an intuitive understanding of software vulnerabilities. This is more than faster code generation, it is a shift from AI as an assistant to AI as an autonomous agent capable of discovering and chaining flaws at a scale that most defenders aren’t prepared for.

These capabilities will not stay confined to controlled environments for long. When Mythos first launched, we predicted a six-month window before attackers gained access. We now believe that timeline has accelerated significantly.

 

 
 
 

The quest to build a better AI tutor — from hechingerreport.org by Jill Barshay
Researchers make progress with an older ed tech idea: personalized practice

One promising idea has less to do with how an AI tutor explains concepts and more with what it asks students to practice next.

A team at the University of Pennsylvania, which included some AI skeptics, recently tested this approach in a study of close to 800 Taiwanese high school students learning Python programming. All the students used the same AI tutor, which was designed not to give away answers.

But there was one key difference. Half the students were randomly assigned to a fixed sequence of practice problems, progressing from easy to hard. The other half received a personalized sequence with the AI tutor continuously adjusting the difficulty of each problem based on how the student was performing and interacting with the chatbot.

The idea is based on what educators call the “zone of proximal development.” When problems are too easy, students get bored. When they’re too hard, students get frustrated. The goal is to keep students in a sweet spot: challenged, but not overwhelmed.

The researchers found that students in the personalized group did better on a final exam than students in the fixed problem group. The difference was characterized as the equivalent of 6 to 9 months of additional schooling, an eye-catching claim for an after-school online course that lasted only five months.

To address this, Chung’s team combined a large language model with a separate machine-learning algorithm that analyzes how students interact with the online course platform — how they answer the practice questions, how many times they revise or edit their coding, and the quality of their conversations with the chatbot — and uses that information to decide which problem to serve up next.

 
 

Nvidia, Eli Lilly announce $1 billion investment in AI drug discovery lab — from finance.yahoo.com by Laura Bratton

AI chipmaker Nvidia (NVDA) and pharmaceutical giant Eli Lilly (LLY) on Monday announced that the two companies would jointly invest $1 billion to create a lab in San Francisco focused on using AI to accelerate drug discovery.

The $1 billion investment will be spent over five years on infrastructure, compute, and talent for the lab. Nvidia’s engineers will work alongside Lilly’s experts in biology, science, and medicine to generate large-scale data and build AI models to advance medicine development. The lab’s work will begin early this year, the companies said.

 
© 2025 | Daniel Christian