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Over the past decade, school districts accumulated thousands of , often that they improved student outcomes. 

Parents and educators are now asking reasonable questions: Have the tools supported teachers in helping students learn? Or have they added distraction, cost and complexity into the school day? 

The next phase of educational technology should be defined less by adoption and more by how carefully districts choose what stays. 

As district and school leaders revisit technology policies, reconsider tools and respond to growing pressure from parents, educators and policymakers, they have an opportunity to replace reaction with rigor. Five questions should guide their decisions. 

First: What problem are we trying to solve?

Technology should not be a given in classrooms. It should earn its place by demonstrating that it can improve teaching and learning.

Too often, technology decisions begin with a product rather than a problem. A district hears about a new tool, responds to an incoming vendor pitch or feels pressure to 鈥渋nnovate鈥� to keep up with its neighbors. 

But the starting point when picking technology, or any tool, should always be instructional vision. Is the goal to help kids who are behind in math? Provide faster feedback on student writing? Expand access to tutoring in schools that lack staff? Reduce administrative burden so teachers have more time for instruction? 

A tool should be considered only if it鈥檚 tied to a clearly defined challenge, adds value and aligns with the district鈥檚 goals. Without that, districts risk adding technology on top of existing problems rather than solving them. 

Second: Is there credible evidence this tool works? 

Not all screen time is equal. There is an important difference between consumer technologies designed to maximize engagement and created to improve teaching and learning. 

Districts can start by reviewing testimonials, usage and satisfaction data, but they shouldn’t stop there. It鈥檚 important to understand whether a tool has demonstrated impact on student outcomes, in what context and for which children. This evidence should initially come through small-scale, rapid-cycle studies and then build up to more rigorous third-party research that has been .听

Artificial intelligence illustrates both the promise and peril of ed tech, and the importance of evidence. Tools that shortcut critical thinking, automate student writing or encourage dependence rather than learning should raise concerns. Technology that helps teachers personalize instruction, provide better feedback and reduce administrative burden deserve careful consideration.

The question isn鈥檛 whether a tool uses AI. It鈥檚 whether it鈥檚 proven to strengthen teaching and learning. 

Third: Does the tool support teachers or substitute for them? 

Human relationships are central to how students learn and are likely to become even more valuable in an AI-enabled world. No technology should replace the role of a skilled teacher, the value of peer debate or the importance of productive struggle.

But if technology is well designed and implemented, it can strengthen great teaching.  

aligned with classroom curricula can . High-dosage tutoring delivered in a can provide struggling students with that many districts cannot otherwise offer. can help teachers provide more timely feedback while for instruction and relationship-building. Translation and accessibility tools can expand access for multilingual learners and students with disabilities. 

These uses of technology strengthen teaching rather than replace it. That distinction should be central to every district’s decision. If a tool weakens the relationship between teachers and students, districts should be skeptical. If it helps educators better understand student needs, target instruction and free up time for interaction and connection, there may be a place for it in the classroom. 

Fourth: How will we know if the tool delivers the desired outcomes?

Districts have developed sophisticated processes for procuring technology. They need equally rigorous processes for removing tools that fail to improve outcomes. 

Before adopting a tool, school and district leaders should define what success would look like. What student outcomes do they expect will improve? Over what period of time? How will educators know whether the tool is helping? Who is responsible for reviewing the data, and how often? What happens if the expected impact does not materialize? 

This last question matters. Schools should be willing to walk away from tools that do not demonstrate value in the expected time frame. If a tool does not improve learning, help teachers or advance a clear instructional goal, it should not remain in the classroom.听

Fifth: Can we explain it clearly to families? 

At a time of rising concern about technology, transparency and specificity matter.

Families deserve to know which technologies are being used, why they were selected, what evidence justifies them, what they will and will not be used for, and how they are supporting their child鈥檚 progress. This is especially important for AI-enabled tools, as parents may reasonably worry about privacy, academic integrity and overreliance. 

A district should be able to explain in plain language how a tool accelerates learning. If this cannot be clearly communicated to families, that鈥檚 a warning sign. 

Words like 鈥減ersonalized,鈥� 鈥渋nnovative鈥� or 鈥淎I-powered鈥� raise more questions than they answer. Ultimately, parents want to know how a tool helps teachers teach and students learn. They want to understand how their children spend their day and what progress they鈥檝e made. 

The backlash against technology in schools has identified real harms. Parents are right to be concerned about tools that undermine attention, replace human interaction or encourage passive use. These don鈥檛 belong in the classroom.  

But the lesson of the past decade is not that technology is bad. It鈥檚 that schools need to be far more disciplined about what they adopt, why they adopt it, how they measure success and how they communicate those decisions. 

The future of learning should not be defined by how much technology schools use, but by how carefully they choose it and how quickly they let go of things that do not deliver.

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