Your Next Job Interview Could Be With a Bot. Here’s How to Prepare. — from builtin.com by Jeff Rumage
More employers are using AI to screen candidates before they ever speak with a recruiter. Here’s what to expect from an AI interview and how to put your best foot forward.

Summary: AI-led interviews are becoming a common early-stage hiring screen as employers use conversational AI to evaluate applicants at scale. Candidates can prepare by practicing aloud, keeping answers concise, using mock AI interview platforms and avoiding scripted responses.

 

How to Improve Your AI Skills — from wondertools.substack.com by Frank Andrade and Jeremy Caplan
What to learn next, from prompts to workflows
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Today I’m sharing a guest post on how to strengthen your AI skills. It’s by Frank Andrade, an AI instructor who has helped thousands of people on Substack master ChatGPT and Claude with beginner-friendly guides and in-depth tutorials.

 

How to Reduce Cognitive Load in Digital Lessons — from educationtechnologysolutions.com by etsmagazine

A digital lesson can be beautifully designed and still make learning unnecessarily hard.

Students may be asked to watch a video, remember an instruction, find a link, switch tabs, interpret unfamiliar icons and submit a response—all before they have dealt with the idea the lesson was meant to teach.

That friction is often mistaken for rigour. It is not. Productive difficulty comes from thinking about the content. Avoidable difficulty comes from navigating the lesson.

The goal is not to make learning effortless. It is to spend students’ limited attention on the knowledge and skill that matter.


The above article links to:

 

Risks and Rewards of IoT in Higher Education — from edtechmagazine.com by Akeya Dickson
Shadow IT is flooding college and university networks as students move back to campus. Here’s how higher ed IT leaders can secure their networks without impacting the student experience.

Connected minifridges, smart speakers and internet-based gaming consoles are among the devices students are bringing to college that IT departments may not have accounted for — or even know are connected to the campus network. These devices may run on default passwords and have little to no security configuration, making them an attractive and vulnerable entry point for a cyberattack.

For higher ed IT, the stakes couldn’t be higher. According to the Zscaler ThreatLabz 2025 Mobile, IoT and OT Threat Report, the education sector saw an 861% rise in malware attacks from Internet of Things devices between 2024 and 2025.

 

The Checklist That Didn’t Exist: A Field Guide to Cutting Extraneous Load — from learningguild.com by Cally Mervine Kiser

If the content is fine, what else could be getting in the way?

The answer, it turns out, has been sitting in educational psychology research for decades. Working memory is finite. When learners engage with training, they are managing three competing cognitive demands simultaneously:

  • The complexity of the subject matter
  • The effortful processing that builds understanding
  • The mental effort generated by how the content is presented, independent of the content itself

That third one is called extraneous cognitive load, and it is the one we almost never explicitly design against. We design for accuracy. We design for alignment. We design for engagement, or at least what we hope will feel like engagement. We almost never sit down and ask, “How much unnecessary mental effort is this design generating, and how do we reduce it?”

 

MIT’s Ad Hoc Committee on AI Use in Teaching, Learning, and Research Training — from aiandeducation.mit.edu

However, what we learned as a group quickly convinced us that the Institute community, particularly the faculty, must tackle a set of deeper questions about the structure, meaning, and value of an MIT education in an era in which AI is one of several factors complicating the Institute’s mission.
…

In this report, we:

  • Highlight key aspects of the current educational landscape at MIT.
  • Share eight principles we relied on and that we hope will guide the Institute in the work ahead.
  • Recommend immediate and long-term actions for both instructors and the administration.

On somewhat related notes:

 

Course design for a new age — from timeshighereducation.com by Campus contributors , Laura Duckett
Learn how to design courses that respond to the evolving needs of both students and employers

At a time when the value of a degree is being called into question, many argue that teaching subject knowledge is no longer enough. University courses must be flexible and embed work training and skills development to serve today’s students. This collection of resources is a guide to designing courses that respond to the evolving needs of both students and employers.


Teaching is a verb: what sets good teachers apart — from timeshighereducation.com by William J. Owen
Reflection is what moves teaching beyond performance and towards continuous improvement, writes William Owen

What sets good teachers apart is their willingness to continually reflect, learn and grow alongside their students. Great teaching is not a destination, it is an ongoing practice of curiosity, humility and intentionality. And perhaps that is what makes it so challenging and so rewarding.


How to set your students up to write compelling op-eds — from timeshighereducation.com by Arafat Reza and Shahariar Sadat
Help students develop their writing and refine their arguments by publishing opinion pieces. Find advice for supporting student writers here

Academics are ideally placed to bridge this gap. Beyond teaching disciplinary knowledge, they can help students develop the confidence and practical skills needed to engage in public discourse. Here, we discuss practical ways in which academics can encourage students to write op-eds that inform people, influence law and policymaking, and inspire positive change in society. Plus, find five tips for teaching students to write compelling arguments.


Rethinking course design to enliven student engagement — from timeshighereducation.com by
To foster students’ meaningful learning, educators should be using class time to maximise the benefits of the in-person experience, as Nasreen Sultana explains

We landed on four practical strategies to make learning more interactive, relevant and student-centred. Although developed in a management classroom, these tips can be adapted across disciplines.

 

Exceptional Videos of Authors Reading Their Books Aloud for Young Students — from edutopia.org by Kristin Rydholm
These 14 books can help teachers celebrate student writing by weaving literacy and social and emotional learning into the school day.

This classroom scenario is an example of how finishing a piece of writing is a dual celebration—an ending and a beginning. A published piece of writing means crossing a finish line as the culminating event within the writing process, but it is also a starting line, where a story begins a journey of its own—being read, seen, heard, and shared by others.

Who better to assist with modeling these transitional and celebratory moments than 14 professional authors of picture books?

Where to start
Featured below are links to exceptional authors and author/illustrators reading their picture books. Watching these videos, a child can see and hear the diverse faces and voices of authors who have prioritized stories about kids like them.


4 Ways to Encourage Great Questions in the Science Classroom — from edutopia.org by Katie Budrow
Here’s how a middle school teacher guides students to proactively ask and answer questions like ‘why does that happen?’

Narrow, prescribed tasks are known as convergent tasks. Define the parts of a cell has a specific answer. Sometimes, convergent tasks make the most sense. But whenever possible, I prefer to use broader divergent tasks, which allow for multiple ways to approach the learning. Describe the different ways that cell parts can work together to form a system is an example of a divergent task.

Divergent tasks inherently drive more student questions, since the answers aren’t just one-and-done. Divergence promotes “deep thinking, requiring students to analyze and evaluate concepts,” according to a study on the subject. Students are not just trying to find the “best” answer—they’re working toward a more complex concept.


A First-Week Routine That Gets Middle School Students Thinking Like Scientists — from edutopia.org by Bexaida Buzzie
Here’s a day-by-day plan for guiding your students to start the year by asking questions. Just resist the urge to answer them.

I realized I was spending so much of my time going over my classroom rules that I forgot that the students were there to learn how to learn.

Once I took the pressure off myself, everything changed. Instead of focusing on perfection, I started to focus on curiosity and fun. Instead of cramming information and reaping frustration, I slowed down.

Here’s what my first five days look like, and how they build a foundation for scientific thinking.


15 Effective Ways to Manage Dysregulated Students — from edutopia.org by Andrew Boryga
Teachers are seeing more big emotions and disruptive behavior in early elementary classrooms. These practical strategies can help youngsters reflect, reset, and repair.

While many experts cite the pandemic’s role in creating skill deficiencies, it’s only a part of the story. Educators also point to major changes in the culture around child rearing, pointing to issues like rising screen time, less play, and fewer opportunities for face-to-face interaction—“developmental needs that no digital program, however sophisticated, can fully replicate,” writes elementary school teacher Cara Zelas.

Serious behavioral issues and developmental concerns require broad support from administrators, specialists, and families. But for everyday moments that derail lessons—a child melting down, refusing directions, or struggling to rejoin the group—many teachers find that simple practices, consistently applied, can help turn big feelings into moments of growth instead of lost instructional time.

 

Using AI to create the practice opportunities online students need— from timeshighereducation.com by Kathy Miller Perkins
For disciplines that depend on interpersonal skills such as communication, leadership, negotiation and mediation, AI can provide elusive experiential learning, particularly in asynchronous environments

What if AI’s greatest educational value lies not in generating answers but in generating experiences?

The result surprised me. Students did not simply interact with the AI, they meaningfully engaged with it. Many reported that the experience felt valuable precisely because the simulated conversation partner pushed back. Unlike classmates who sometimes hesitate to challenge one another, the AI consistently maintained its position. Students had to work harder, listen more carefully and apply the communication strategies they had spent weeks learning. And, importantly, they practised.

Here’s how to show students what responsible AI use looks like — from timeshighereducation.com by Andrew Firr and Alex Fenton
Well-designed assessments can highlight generative AI’s limitations, where it can provide support and what responsible practice looks like. Andrew Firr and Alex Fenton offer strategies

We have been exploring ways to offer this in our Level 7 module for MSc engineering management students, many of whom come from the Global South. Assessment is built around a practical design problem: students examine how a real campus process operates, where delays occur, evidence they observe and how a feasible redesign might improve the system – in a 3,000-word essay.

They can use AI for planning and providing clarity, but not for generating the evidence on which the analysis rests. Invented observations, measurements, screenshots or unverifiable citations are prohibited. The assessment design reinforces this through a case study, diagram, fact-checking exercise and a short AI use statement.

Requiring an AI use statement encourages students to reflect on their processes. We ask which tool they used, how they used it, how they checked the output and which parts of the work depended on their own evidence and judgement. It reminds them that evidence must be theirs and that citations must be manually verified.


Slow math: Kids may learn more when AI makes them review mistakes — from hechingerreport.org by Jill Barshay and Kristin Fasiang
A randomized experiment involved more than 6,000 Tennessee middle school students learning fractions

In an experiment involving more than 6,000 middle schoolers in Tennessee, students learned slightly more math when an AI tutor walked them through their mistakes and then required them to demonstrate the same skill correctly three times in a row before moving on.
…
The winning combination wasn’t the addition of AI tutoring alone, but AI tutoring plus repetition, with the idea that students needed to stick with the skill to demonstrate some level of mastery. The students who practiced math with this AI-enhanced “mastery learning” approach scored about 3 percentage points higher than students receiving conventional computerized instruction. The advantage was small.


I Built a Team of AI Bots That Write Feedback Better than Me. Here’s How.  — from drphilippahardman.substack.com by Dr Philippa Hardman
Aka, how to make learners love AI-assisted feedback, rather than loathe it.

This wasn’t hidden from the cohort. For reasons I’ll come to below, I always tell my cohorts at the very start that an AI assistant will be helping me draft their feedback. The aim wasn’t to remove me from the process, but to find out whether AI could help me to deliver feedback at a volume and quality that I simply couldn’t maintain without AI.

Spoiler: the experiment worked — but not for the reason I expected. In this post, I’ll share exactly what I built, tell you how to build a version for your course and reveal the three conditions that decide whether learners trust AI-assisted feedback or quietly stop reading it.

TL;DR: the spec for my feedback assistant is long not because the model needs persuading, but because it’s where my judgement lives. Every rule in it is a decision AI would otherwise make by itself, with limited expertise. A spec doesn’t make the model smarter — it makes expertise and judgement legible enough for the model to follow.


Of the five stages of AI grief, some managers are stuck in denial— from timeshighereducation.com by Shadi Mohamed
Acceptance is not surrender. It is about getting beyond a policing obsession and rethinking what assessment aims to measure, says Shadi Mohamed

In that moment of institutional blindness, it struck me: universities are not merely struggling with a technological adoption curve. They are grieving the demise of the modern university’s economic and institutional logic.

To understand the scale of this threat posed by AI, consider what the internet did to journalism. Newspapers thrived by bundling together classified advertising with quick news hits, sports scores and opinion columns, using that reliable revenue to fund the expensive social necessity of investigative reporting. The rise of internet advertising did not kill journalism outright but it shattered the bundle, leaving the expensive core product without its historical financial engine.

Universities operate on a similar logic, bundling content delivery, assessment, credentialling, research and professional formation. But generative AI is now commodifying the most visible parts of that package. When AI can deliver personalised explanations instantly and generate the essays and reports we use to measure student capability, the traditional degree loses its role in the labour market as a proxy for understanding. If the bundle breaks, the economic model that funds our deeper purposes is in peril.


 

How to Design Around Cognitive Offloading — from drphilippahardman.substack.com by Dr Philippa Hardman
Three new studies shed light on when offloading to AI harms learning, when it helps — and how to design for the difference

A cluster of new studies — most published in the last few weeks in the International Journal of Educational Technology in Higher Education — lets us answer two questions with more precision than ever before:

  1. When does cognitive offloading actually happen?
  2. When does using AI improve cognition?

The answers in turn help us to start to design learning which intentionally uses AI to drive – rather than diminish – learning.
.

 

15 Best Instructional Design Conferences To Attend — from elearningindustry.com by Christopher Pappas

Overview: Looking for the best Instructional Design conference in 2026? Explore 15 leading learning, L&D, eLearning, and training conferences worldwide to build skills, discover learning technology, and expand your professional network.

 

Will this new company be the largest company on the Internet by 2030? [Christian]

From DSC:
The vision that I’ve been tracking for well over a decade begins with this graphic:
.


Could LearnVector be this next-generation company/platform? Perhaps. Time will tell.


Per Matt Tower via The EdSheet Vol. 38 dated 7/31/26:

  • Coursera bets $100M on its own co-founder: Andrew Ng’s new venture LearnVector lands one of the largest single checks in edtech this year — from Coursera, the company he founded 14 years ago.
    .


LearnVector.ai

 

How Explainer Video Production Turns Ideas Into Clear Stories — from bitrebels.com by Lauren Williamson

Ideas rarely arrive in a neat order. They show up as notes, claims, diagrams, feature lists, and customer questions. Explainer video production turns that raw material into a story people can process quickly. It clarifies the problem, frames the change, and shows why the answer matters. When the script, visuals, voice, and pacing work together, viewers spend less energy decoding the message and more attention on absorbing it.

Explainer video production works because it gives ideas a usable order. It turns scattered information into a story with purpose, pace, and visual evidence. The strongest results come from careful message decisions before animation starts. When script, design, voice, and timing support one central point, viewers can follow with less effort. That clarity helps organizations teach, persuade, and make it easier to remember.

 

From DSC:
Below is an item on futures thinking. Don’t blow this off. This topic — and skill/strategy — is important not only to traditional institutions of higher education, but also to businesses and organizations of all sizes. In fact, even students can practice developing a list of potential scenarios and implement their plans of action if one of those scenarios occurs.


Chris Mayer’s posting on LinkedIn.com

 

What’s the Story Your Syllabus Tells?: Setting the Stage for Learning — from facultyfocus.com by Dr. Daniel Andrés Rivera Rosado

But as I was reading Everyday Christian Teaching by Dr. David Smith, in the chapter titled Speaking, Hearing, Hospitality, in just the first paragraph he writes: “Teachers do not simply list course content for learners. They sequence it in ways that imply a story about what fits together and where it is headed.” (2025, p.73). Automatically I asked myself, what is the story my syllabus is telling students? To be completely honest, is it even telling a story at all?

“Is your syllabus helping your students at all?”

From DSC:
To that last sentence, I might add the words engaging, raising curiosity or wonder, or is it interesting to your students at all? Is there a “hook” that gets them interested? It might be a central question or two — and/or use some beneficial and relevant graphics. I’ve heard faculty use digital/interactive syllabi as well to engage their students.

 
© 2025 | Daniel Christian