Laura K Spencer, Ed.D.

Category: Artificial Intelligence

  • 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.

  • AI in Leadership: A Balancing Act

    AI in Leadership: A Balancing Act

    As we all know, the world of tech is constantly evolving, and AI is no exception. It’s amazing to see how AI is changing the way we make decisions, especially for those of us in leadership roles. But with this new power comes a whole lot of responsibility.

    One of the biggest things we need to consider is the ethical side of using AI. We need to be open and honest about how AI is being used to make decisions, and what data is feeding into those decisions. For example, we need to be aware of situations where AI tools might be used to evaluate student work, and understand how those tools might have different error rates for evaluating essays written by native vs. non-native English speakers. It’s also super important to make sure everyone on the team understands how AI works and feels comfortable questioning its recommendations. After all, we’re a team, and we need to be accountable to each other.  

    Of course, we can’t forget the human side of things. We need to make sure that using AI doesn’t leave anyone out or reinforce any biases. Our goal should always be to create a more inclusive workplace. This is especially important when using AI in situations with the potential to create a hostile environment, such as when using facial recognition technology or AI-enabled content moderation tools.  

    Now, don’t get me wrong, AI can be incredibly helpful. It can help us streamline our work, personalize learning opportunities, and even give us a glimpse into the future with predictive analytics. But we need to find a balance between using AI to make things more efficient and staying connected to the human element in our organizations. For instance, if we’re using AI to identify students at risk of dropping out, we need to make sure that the tool isn’t unfairly targeting certain groups and that we’re providing support to those students in a way that is both effective and respectful.  

    As leaders, it’s up to us to set the ethical standards and make sure we’re always putting our team’s well-being first. If we can do that, we can unlock the full potential of AI without sacrificing the trust and integrity that are so important for successful leadership.

    What do you all think? I’m really interested to hear your thoughts on this!

    And for more reading on this subject, check out this memo published by the U.S. Department of Education, which inspired this post.

  • Transform Meetings with Gemini’s Live and Research Tools

    Transform Meetings with Gemini’s Live and Research Tools

    As many of you know, I’ve been on a journey to become a more effective and empathetic leader. Part of this journey has involved using Google Gemini to help me analyze my communication patterns and identify areas for improvement. I’m truly excited to share that Gemini has recently rolled out some incredible new features – “Research” and “Live” – that I believe will significantly enhance how we communicate as a team.

    Research: Fueling Our Conversations with Knowledge

    I haven’t spent a ton of time with Gemini’s Deep Research option yet, but from what I can gather, I think it will be great for real-time fact checking as well as diving deeper into topics. With Gemini Research, we can instantly verify details during meetings or presentations, ensuring our communication is always accurate and credible. It will also empower us to analyze complex data, and gather comprehensive insights, which is pretty impressive.

    Live: Dynamic Interactions for a More Connected Team

    Imagine us all jamming on ideas together, in real-time, and actually getting somewhere! With Gemini Live, brainstorming sessions become super dynamic, and everyone gets a chance to chime in and build on each other’s thoughts. Plus, we can fine-tune our messages to hit the right note with different folks, so our communication really lands. And get this – we can even get instant feedback on how we’re doing, so we can tweak our style and make sure our message is crystal clear. Pretty cool, right? I used it the other evening to better understand AB 2013, California’s new generative AI law that is set to go into effect in 2026. We had a great conversation and I left feeling enlightened.

    How Research and Live Could Transform Our Workplace:

    • More Impactful Presentations: Deliver more compelling and informative presentations with real-time data and research support.
    • More Efficient Meetings: Make our meetings more productive by quickly accessing relevant information and facilitating dynamic discussions.
    • Stronger Collaboration: Foster a culture of knowledge sharing and collaborative problem-solving with interactive tools and personalized communication.
    • More Informed Decisions: Make well-informed decisions based on accurate data and diverse perspectives.

    I’m optimistically hopeful (is that a real phrase?) about how Google Gemini’s Research and Live features can elevate our communication, strengthen our collaboration, and ultimately, help us achieve our goals more effectively. Would love to know your thoughts.