The shift in educational technology culture became clear to me through our annual edtech conference here in South Dakota. To my eye, attendance has thinned over the past few years, and the people who still come tell me they miss the good old days of fast-paced app demonstrations and tool-centered sessions. They want the slide deck packed with thirty apps they can try tomorrow.
The irony is that many of the people who stopped coming did so, as far as I can tell, because they think the conference is still stuck in that era. They’re burned out on disconnected tools and looking for something more substantial. We’ve ended up in the strange position of retraining South Dakota teachers to understand that the app-dump era is over, and that this is good news.
That tension captures the larger struggle in educational technology. The era of app dumps, those endless lists of applications handed to educators with minimal pedagogical context, is dying, and I’m relieved to see it go. At the same time, artificial intelligence has positioned itself as the next technological savior, and I’m watching the same problems return in a shinier package.
The App-Dump Years
The years from roughly 2008 to 2016 were the definitive era of app-centric edtech. It grew out of real enthusiasm about what digital tools might do for learning, backed by a period of unprecedented federal investment in classroom technology. Early on, the tools promised engagement, personalization, and accessibility, and early adopters, myself included, embraced them.
What began as excitement turned into an unsustainable practice. Professional development sessions became rapid-fire showcases of dozens of applications, presented in colorful slide decks with almost no time for integration. Teachers left overwhelmed rather than equipped, holding lists of apps they barely understood how to use well. The professional learning networks of the period, vibrant as they were, mostly amplified the pattern: educators enthusiastically sharing the latest app with little critical discussion of what it was for.
Give Me Something I Can Use Tomorrow
Technology companies bear a lot of responsibility for tool-centric training, but educators helped build the cycle too. The common request in professional development, “give me something I can use tomorrow,” reflects an understandable wish for immediate classroom application, and that same wish created a demand that undermined substantive professional growth.
The preference for immediacy turns professional development into snacking. A quick app demonstration provides the momentary satisfaction of novelty and applicability, but it doesn’t nourish long-term instructional capacity. I’ve watched colleagues enthusiastically implement a newly discovered app and abandon it weeks later when its limitations surfaced or maintaining it became unsustainable. A steady diet of disconnected tools without theoretical grounding leaves educators professionally undernourished. The balanced meal of theory-informed practice doesn’t deliver the same hit as a shiny new tool, but it sustains improvement over time.
The pattern was most pronounced in the app-dump years, and it persists in current AI training. Today’s workshops on AI tools often follow the same template: rapid demonstrations of impressive capabilities with no substantive discussion of learning theory, ethics, or long-term instructional impact.
Badges, Certifications, and Digital Trinkets
One especially troubling feature of the period was the explosion of badges and certifications that prioritize tool mastery over pedagogical expertise. Nearly every technology company created its own credential, from Google Certified Educator to Apple Distinguished Educator to Microsoft Innovative Educator. These companies found a way to redirect educators’ genuine motivation to improve their practice into certification systems that conflate product proficiency with teaching excellence.
I watched colleagues, and myself, pursue these credentials with real dedication, only to find that the new status mainly equipped us to evangelize for specific products. The companies get free marketing and advocacy, while educators invest unpaid hours chasing credentials of uncertain classroom value. Professional advancement gets tied to corporate tool adoption rather than demonstrated teaching, hiring starts to favor platform expertise over pedagogical judgment, and PD budgets flow toward tool-specific training rather than instructional improvement.
The deeper cost is what happens to critical judgment. When an educator’s professional identity becomes intertwined with a product, their ability to evaluate that product diminishes. I’ve lived this. After investing significant time mastering Canvas and building a professional reputation around that expertise, I found myself reluctant to acknowledge its limitations even when they were apparent. I wrote more about that in Known as the Canvas Guy.
Nothing Is Neutral
The industry has promoted the idea that its tools are neutral instruments whose value depends entirely on how educators deploy them. That framing absolves companies of responsibility for how their products shape classrooms while placing the full burden of proper implementation on teachers.
It ignores a basic reality. Every technology embeds values and assumptions about how learning should work. Each platform makes certain interactions easy and others hard, rewards particular behaviors, and decides what counts as progress. Look closely at the most popular tools and you find a consistent lean: individual work over collaboration, quantifiable metrics over qualitative understanding, complex skills reduced to progress indicators, a faster pace of instruction without deeper learning, and large amounts of student data collected with little transparency about its use. These design choices shape classroom dynamics regardless of what the teacher intends, and pretending otherwise lets us avoid the essential conversation about whose interests these tools serve and what educational values they advance or undermine.
A Design Challenge
Here’s a useful test for any EdTech professional development session, including the ones I run. Remove every specific tool from the content. Strip out every product name, every interface walkthrough, every “here’s where you click.” What’s left?
For many sessions the honest answer is nothing, because there was no substantive foundation underneath the demonstrations. The sessions that survive the test are the ones whose value lies elsewhere: in frameworks for evaluating any technology against learning objectives, in design principles that transfer across platforms, in the critical judgment to tell when a tool is helping and when it’s getting in the way, in implementation strategies built for sustainability rather than novelty, and in ways of measuring impact on learning rather than engagement metrics.
That test also explains why the field has lost standing. When educational technology gets reduced to knowing the tools, it becomes easily dispensable, especially when the tools change every few months. EdTech specialists find their roles redefined as technical support rather than pedagogical consultants. Districts that once embraced every new digital offering have become more discerning, having learned hard lessons about tool-centered approaches, and I count that as progress even when it means fewer requests come my way.
AI, Same Problems
As app dumps fade, AI has taken their place as edtech’s salvation narrative, and the training sessions emerging around it mirror the app-dump workshops with uncomfortable precision. Facilitators, myself included on some days, demonstrate chatbots answering student questions, automated grading, and personalized learning paths at the same rapid-fire pace that characterized app demonstrations a decade ago. Teachers leave with superficial tool knowledge and no deeper sense of how these systems might reshape learning environments.
The familiar tendencies are all present: emphasis on capability rather than purpose, marketing that promises personalization while delivering standardization, corporate interests driving adoption, pressure on schools to move fast or look backward, and thin attention to privacy and ethics. The same educator request, “give me something I can use tomorrow,” now drives AI training toward flashy demonstrations rather than a real reckoning with what these tools do and undo. I’ve written elsewhere about how AI vendors have learned to frame teacher exhaustion itself as the sales pitch, in Teaching Realism. Having watched several cycles of enthusiasm followed by disappointment, I approach educational AI with the same skepticism I wish I’d brought to the app era.
What should training do instead?
The most effective educators I know aren’t the ones who master the latest tools. They refine instructional techniques that respond to student needs, and they select and adapt technology according to how well it supports those techniques rather than letting the tool dictate the teaching.
What EdTech training needs is a reorientation toward theory, practice, and strategy. That means recognizing that technology isn’t the device or the software but our understanding of how to use it for a purpose. The field needs to reclaim that definition, technology as a means of extending human capability through purposeful application, rather than letting it shrink to a list of branded products.
In practice, that looks like sessions that 1) begin with learning theory and pedagogical problems before any tool appears, 2) examine cases of implementation that worked and implementation that failed, 3) hand educators evaluation frameworks so they can make independent judgments about a tool’s value, and 4) focus on skills and concepts that outlast any particular platform. It also means inverting the usual adoption process: start with a specific educational challenge and ask whether technology offers a meaningful answer, rather than starting with an exciting tool and searching for somewhere to use it. Most of all, it means the people who run professional development should stop asking “what cool tech can we show teachers today?” and start asking “what enduring understanding about technology and learning do we want teachers to leave with?”
Effective EdTech training should model the approach it advocates. If a session can’t pass its own strip-the-tools test, it shouldn’t be on the program.
Final Thoughts (For Now)
The decline of app dumps is an opportunity to reconsider our relationship with technology in learning. Districts have become savvier consumers, less susceptible to promises without evidence. The pandemic forced many educators to confront the limits of technology-driven approaches and made it plain that no tool, however sophisticated, replaces thoughtful instructional design.
I’m still somewhat optimistic that the pendulum is swinging back. That realization may hold long enough for us to ask the essential questions about AI’s educational value before the next wave of enthusiasm carries the field somewhere it has already been. The future of edtech lies not in accumulating tools but in developing the judgment to know when technology serves learning and when it doesn’t. Sometimes the most innovative choice is to set the tools aside entirely. I’m not sure the field can break free of the corporate-driven cycle of technological solutionism, but I’m sure it can’t while it keeps calling tool demonstrations training.
If you’ve run or sat through EdTech training that would pass the strip-the-tools test, I’d like to hear about it. You can reach me at licht.education@gmail.com, and there are more tools, articles, and resources at bradylicht.com.
