Category: Educational Technology

  • Adoption Isn’t Impact: The Quiet Failure of Learning Innovation

    Adoption Isn’t Impact: The Quiet Failure of Learning Innovation

    I keep seeing the same pattern across schools, organizations, and learning platforms.

    The tools keep getting better.
    The outcomes… not so much.

    AI is more capable. XR is more immersive. Platforms are more polished than ever. And still, leaders feel it. That quiet, nagging sense that learning isn’t actually working the way it was promised.

    Engagement spikes. Pilots multiply. Dashboards fill up.
    Clarity about impact stays frustratingly out of reach.

    This isn’t a technology problem.
    It’s a design problem.

    Most learning systems were never built to absorb this level of change. New tools get layered onto old structures. Innovation gets bolted onto workflows designed for stability, not adaptability.

    The result is fragmentation.
    Good intentions. Scattered execution.

    I hear versions of this all the time:
    “We’ve adopted the platform.”
    “We’ve rolled out the tool.”

    What’s missing is the harder question:
    What is this actually changing about how people learn, think, and make decisions?

    Adoption is visible.
    Impact is not.

    Impact only shows up when there’s alignment. Between learning strategy, leadership expectations, culture, and the realities of day-to-day work. Without that, even the most advanced tools struggle to matter.

    Another common miss is over-indexing on features instead of purpose.

    Yes, AI can personalize learning paths.
    Yes, XR can simulate environments.
    Yes, analytics can surface patterns.

    None of that answers the real questions:
    What capabilities are we trying to build?
    What skills matter here?
    What should change when the tool is no longer new?

    When those questions go unanswered, technology defaults to efficiency, not meaning.

    I also see responsibility for learning outcomes get diffused. Innovation teams experiment. IT enables. Designers design. Leaders cheer from a distance.

    No one owns coherence.
    No one is accountable for the system as a system.

    Learning doesn’t break down because people aren’t trying.
    It breaks down because no one is tasked with connecting the dots.

    The organizations making real progress look different.

    They slow down before they scale.
    They clarify what learning is for before deciding what to buy.
    They treat technology as a lever, not a strategy.

    Most importantly, they treat learning as a leadership function, not a procurement decision.

    Leaders are involved early. They set priorities. They make tradeoffs. They resist the urge to pilot everything and instead commit to a few things done well.

    Learning stops being something that happens “over there.”
    It becomes part of how the organization thinks and operates.

    This shift isn’t flashy. It doesn’t generate big announcements.
    But it creates durability.

    What’s encouraging is that more leaders are starting to feel this gap. In conversations with superintendents and edtech leaders, I hear the same frustration surfaces again and again.

    Money is being spent.
    Capability isn’t always following.

    There’s a growing recognition that more tools aren’t the answer.

    The path forward isn’t about rejecting technology.
    It’s about designing systems that can actually hold it.

    That means:

    • treating learning as a connected ecosystem, not a collection of initiatives
    • aligning leadership expectations with learning goals
    • designing for judgment, adaptability, and human skill, not just completion and compliance

    When learning is designed this way, technology amplifies it.
    When it isn’t, technology just accelerates confusion.

    The future of learning won’t be decided by the next platform or algorithm.

    It will be decided by whether organizations are willing to do the harder work of design. Clarifying purpose. Creating coherence. Building systems that support how people actually learn and grow.

    The organizations that get this right aren’t chasing better tools.
    They’re designing better systems.

    Everything else follows.

  • The AI Revolution: A Wake-Up Call for Real Learning

    The AI Revolution: A Wake-Up Call for Real Learning


    The recent buzz around AI in education, exemplified by Elon Musk’s assertion that AI-assisted learning can already outperform human teachers, has sparked important conversations. However, I believe we’re focusing on the wrong question.

    We’re asking if AI will replace teachers, but we should be asking: is AI already replacing students in their own learning process?
    This question was recently raised on LinkedIn by Elena Beretta, who shared her observations of students leveraging large language models (LLMs) for everything from writing essays and solving homework to debugging code and even drafting theses. The driving force behind this widespread adoption? Increased productivity, she asserted. Students are drawn to the efficiency AI offers, allowing them to complete assignments in a fraction of the time. As Beretta points out, this isn’t necessarily about cheating – universities are addressing that – but about a fundamental shift in how students perceive learning.
    Beretta’s insights highlight a crucial trifecta of concerns: the shifting definition of learning, the delegation of “worthwhile” knowledge to AI, and the increasingly difficult role of educators. When productivity becomes the primary goal, the process of learning is devalued. If AI can instantly generate answers, what incentive do students have to grapple with critical thinking, problem-solving, and the development of structured arguments – skills that only improve through dedicated practice? This leads to AI effectively dictating what is “worth” learning, as students bypass the struggle inherent in developing these crucial skills. Consequently, educators are finding themselves in an exhausting loop, becoming less teachers and more AI-police and content verifiers. This begs the question: how can we equip students with the skills they truly need when AI makes it so easy to circumvent the learning process?
    I believe this situation underscores a pre-existing and deeply rooted problem in our educational system: the transactional view of schooling. For too long, students have been conditioned to see education as a series of tasks, points, and high-stakes tests, prioritizing metrics and data over genuine intellectual growth and the joy of learning. This transactional approach has already diminished the value of deep learning, and the advent of AI only amplifies this crisis. The “hustle” mentality, focused on efficiency and output, has become even more entrenched.
    If we don’t address this fundamental issue, we risk losing any hope of real learning taking place in schools. We need a paradigm shift, moving away from a system obsessed with productivity and embracing a performance-based model that prioritizes meaningful topics and the cultivation of essential skills. What matters most is fostering critical thinking, creativity, and a genuine love of knowledge – qualities that cannot be replicated by AI.
    Perhaps the disruption caused by AI can serve as a much-needed wake-up call. It’s time to fundamentally rethink our approach to education and ensure that learning isn’t just about completing tasks quickly, but about developing skills that are truly valuable and relevant for the future. This reality check could be precisely what we need to redefine learning for the better, shifting our focus from mere efficiency to the cultivation of human potential.

  • Learning Through Technology: AI in Education

    Learning Through Technology: AI in Education

    I recently had the privilege of being a guest on the Learning Through Technology podcast, where I engaged in a fascinating discussion about the legal and ethical implications of AI in education. Guesting with me was Gretchen Shipley from F3 Law, whose expertise in education law brought valuable insights to our conversation.

    As educators, administrators, and members of the education community, we’re all navigating the rapidly evolving landscape of AI technology in our classrooms and institutions. During the podcast, we explored critical questions about how to harness AI’s potential while ensuring we maintain ethical standards and comply with legal requirements.

    Some of the key topics we covered include:

    • The current state of AI adoption in educational settings
    • Legal considerations when implementing AI tools in the classroom
    • Ethical frameworks for decision-making around AI use
    • Practical guidelines for educators and administrators
    • The importance of maintaining academic integrity while embracing innovation

    I believe this conversation comes at a crucial time as more schools and districts are developing their AI policies and guidelines. Whether you’re an educator already using AI tools, an administrator crafting policy, or simply interested in the future of education, I encourage you to listen to the episode and share your thoughts.

    You can find the episode on the Learning Through Technology podcast platform. After listening, I’d love to hear your perspectives:

    • What has been your experience with AI?
    • What challenges have you encountered?
    • What opportunities do you see for the future?

    Let’s continue this important conversation in the comments below. Your insights and experiences can help shape how we collectively approach AI, both in education and the workforce.

    Check out the podcast episide:

    Fame Host
    Spotify
    Apple podcast


    If you found this discussion valuable, please share it with your colleagues and professional network. The more voices we have in this conversation, the better equipped we’ll be to shape the future of education.

  • Efficiency vs. Elimination: Rethinking AI Automation

    Efficiency vs. Elimination: Rethinking AI Automation

    Artificial intelligence (AI) is rapidly transforming our world, promising a future of streamlined workflows and maximized productivity. But in our rush to leverage AI’s power, are we focusing on the right outcomes? Is AI truly making us more efficient, or are we simply automating tasks that perhaps shouldn’t exist in the first place?

    Efficiency vs. Automation: A Key Distinction

    Efficiency is about doing things better, optimizing processes to achieve more with less. Automation, on the other hand, is about replacing human effort entirely. While automation can contribute to efficiency, it may not always be the preferred approach. Why?

    • AI can augment human strengths, not replace them. Tasks requiring creativity, empathy, and critical thinking still benefit from human input. AI can analyze data, identify patterns, and automate repetitive steps, but it can’t tell us the hidden story behind the data and patterns.
    • Not all tasks deserve automation. Some tasks may be inherently inefficient, and automating them simply perpetuates a broken system.

    Using AI to Ask the Right Questions

    Instead of simply automating existing processes, AI can help us ask better questions about the processes we are looking to streamline.

    • Is this task truly necessary? Could AI help us streamline processes or even eliminate unnecessary steps altogether?
    • Can AI augment human capabilities? How can AI assist us in making better decisions or perform tasks more effectively?
    • How can we ensure responsible AI implementation? Clear guidelines and human oversight are essential to mitigate bias and ensure ethical use.

    The Future of Work: A Human-AI Partnership

    There’s a lot of fear about the future of work, and whether or not the dystopian Terminator and iRobot movie society will come to be. I truly believe that it isn’t about humans vs. machines. By leveraging AI for true efficiency, we create opportunities to focus on the high-value tasks while AI handles the mundane. This not only increases productivity but also fosters a more engaging and fulfilling work environment.

  • WHY WHY WHY… Keep asking WHY.

    WHY WHY WHY… Keep asking WHY.

    In a former life I was an Ed Tech Director. One day, my boss asked me to form a committee to develop a plan for a refresh of our classroom technology. He wanted to know what new classroom technology to buy, at what cost, and and on what timeline.

    I responded. “Sure, but before I do, I have a question for you. Imagine you walk into a classroom and think to yourself, ‘Wow, THIS is the best example of teaching and learning I have ever seen. If only every teacher and student could have an engaging experience like THIS, the learning for students in our district would be off the charts fantastic.’ Can you please describe for me what it is that would make you think that?”

    Why ask that question?

    Technology is not the driver of learning. It seems ridiculous to have to say that, but I do.

    I am part of a Facebook support group for teachers that use a specific technology product. A question was posed to the group:

    A screenshot of a facebook post that reads "Question: What are your favorite virtual activities that work for engagement?" It shows 7 likes and 31 comments.

    Quickly teachers chimed in to offer ideas.

    A slide with screenshots of Facebook comments, including: Nearpod, Jamboard, Book Creator, Quizizz, Kahoot, Whiteboard.fi, Mentimeter

    Here’s the thing…

    The initial question didn’t ask what technology tools do teachers use to check for understanding or to provide for collaborative learning space. The question asked for “activities” that work for engagement. “Activities” signifies that the response should be a verb, but the responses were nouns.

    Why is that?

    Before I answer that, let’s look at Simon Sinek’s Golden Circle.

    Sinek’s Golden Circle asks people to start by defining the WHY. It’s what drives us to do what we do and how we do it. In education, people may define the WHY as standards, or high stakes testing, or maybe college and career readiness (the new buzz phrase) but it’s deeper than that. The WHY is (or should be) something along the lines of providing students with the skills, knowledge, and capacity to lead a meaningful life.

    Once we have an idea of what those skills and knowledge should be (WHY), we connect it with the standards we are told to teach (WHAT) and develop objectives and lessons (HOW) that guide progress towards achieving the WHY. Without the WHY, we’re back to the old factory model of “Open head, pour in content, move to next grade” education system.

    So what’s this have to do with that Facebook post?

    The teacher asked for ways (i.e. activities) to engage students in a virtual context. I would have expected responses like this one:

    “I post a photo of a Renaissance painting to facilitate student-led conversations using the Step Inside Thinking Routine so that students can explore the historical era through a persona perspective. I have them share their responses in breakout rooms so that they can engage in authentic conversations which my students seem to enjoy. They then share a summary of the conversation when we reconvene.”

    This type of answer engages in WHY. I can see from it that the teacher’s WHY includes: collaboration, critical thinking, creativity, open dialogue, and reflective thought. It also shows the WHAT by connecting to world history and art standards. And there’s even some HOW in the explanation of the activity steps and the use of breakout rooms.

    Technology products aren’t what create engagement or learning. People do that. Universal Design for Learning (UDL) defines engagement as the WHY of learning. It is how learners get engaged and stay motivated through challenge, excitement, or interest. Because engagement is the affective domain of the brain, “some learners are highly engaged by spontaneity and novelty while others are disengaged, even frightened, by those aspects, preferring strict routine. Some learners might like to work alone, while others prefer to work with their peers. In reality, there is not one means of engagement that will be optimal for all learners in all contexts; providing multiple options for engagement is essential” (UDL Guidelines).

    “Some learners are highly engaged by spontaneity and novelty while others are disengaged, even frightened, by those aspects, preferring strict routine. Some learners might like to work alone, while others prefer to work with their peers. In reality, there is not one means of engagement that will be optimal for all learners in all contexts; providing multiple options for engagement is essential.”

    UDL Guidelines

    For every product that was shared on that Facebook question as an engagement method, I can list ways in which that tool could also be used to disengage students from learning. The tool is just a tool. A hammer is great, but not when I need to loosen a screw.

    As teachers, we need to be careful not to get caught up in the edu-glitter of Ed Tech tools. Today it’s JamBoard. Before that it was a SmartBoard. And a white board. And way before that, a chalkboard. The tools shift, but our focus on the WHY should not.

    Oh yeah, back to my story…

    I never got a response from my boss. And so he never got a refresh plan from me.

  • Designer or Design Thinker?

    Designer or Design Thinker?

    Innovation is when something new is created and implemented that adds value. Inventions happen every day, and every year inventions find their way into our classroom. 

    It’s only when an invention adds value that they become an innovation. A lot of times we get caught up in the invention, or the idea. I call this the glitter dust syndrome. 

    Ever receive a card with glitter on it? It’s pretty and you’re excited to receive it. But after you read the card and put it out for display, you see it… glitter. It’s everywhere. It’s stuck on your clothes, your skin, your carpet.

    It added no value to the card. In fact, sometimes the message of the card gets lost because you’re too busy cleaning up the glitter. If there is no value add, there’s no innovation. Just invention. 

    So how do we determine whether something is going to be a value added innovation in our classroom or a case of glitter dust?

    Design thinking.

    We are all designers. Every lesson plan you write, every bulletin board you create, every assessment you assign, even the outfit you put together for today. But that doesn’t mean you’re a design thinker. Human-centered design requires us to step away from our own needs, our own assumptions, and look at the world through the lens of others. 

    Design Your Mask

    During my keynote presentation at SDCOE’s Learning and Innovation Summit Saturday, I asked everyone in the room to design a mask that they could wear without holding it. They also had to be able to see through it. One piece of cardstock paper was the only material provided. The timer was set for three minutes.

    Just about everyone was able to design a mask and wear it. But then I asked them to trade masks with the person sitting next to them. Quickly, they realized that their mask didn’t quite fit their colleague as well as it fit them. Maybe the eye slits were off, or the way it latched on to their face didn’t quite work. Those who used their glasses to hold it on had to also give their glasses to the colleague, which caused some blurry moments!

    Why didn’t the mask fit as nicely on the colleague as it did on the designer? What needed to happen for the mask to fit somebody else?

    Innovation in Education

    Human-centered design requires us to step away from our own needs, our own assumptions, and look at the world through the lens of others.

    When considering innovation in education, it’s important to differentiate between invention and innovation. What is the value add for our students? Is there one? Schools implement adaptive tech programs that promise to increase reading scores. Tables on wheels are placed everywhere. Social-emotional curriculum is purchased. 

    But whose face are we designing the mask for when we do so? Are we simply covering our students in glitter dust?

    When we recognize that our mask doesn’t fit everyone else like it fits us, we realize how our bias, our experiences, our beliefs, impacts student learning. And we start becoming human-centered designers. 

    This is the difference between designers and design thinkers. 

    This blog post is adapted from a keynote I gave at SDCOE’s Learning and Innovation Summit Feb 8, 2020.