Beyond Screen Time: What New Classroom Research Tells Us About Technology, AI, Learning, and Digital Self-Regulation
Caveat: We want to begin by acknowledging that we here at The White Hatter are not licensed classroom teachers, and we do not claim to be experts in classroom pedagogy. Our area of expertise and education is in digital literacy, internet safety, security, privacy, online risk, digital citizenship, and artificial intelligence, particularly as these issues intersect with youth, families, schools, and the increasingly connected world in which young people are growing up.
It is through that lens that we have written this article, drawing upon two newly released research reports from New South Wales, Australia, that examined how technology is actually being used in classrooms, as well as the experiences and perceptions of students, parents, teachers, school leaders, and future educators (1)(2). We found the research particularly interesting because it moves the conversation beyond the increasingly polarized debate of “screens are good” versus “screens are bad” and toward more practical questions about when, why, how, and under what conditions technology can support learning.
However, research findings and our perspective as digital literacy and AI educators are only part of this conversation. Classroom teachers bring something we do not, the lived experience of managing diverse groups of students, curriculum requirements, learning differences, classroom dynamics, limited instructional time, assessment, technology failures, distraction, accessibility needs, and the everyday realities of teaching. For this reason, we particularly hope that the teachers, educational assistants, school administrators, and other education professionals who follow our work will add their voices to this discussion. Do these research findings reflect what you are seeing in your classrooms? Where do they get it right? Where do they miss the mark? What has worked, what hasn’t, and what do you believe parents and caregivers need to better understand about technology and AI in today’s classrooms? We genuinely believe this conversation becomes stronger when digital literacy expertise, educational research, classroom experience, student voice, and parent and caregiver perspectives are brought together rather than discussed in isolation.
We here at The White Hatter have long believed that conversations about children, technology, and education become less useful when they are reduced to a simple debate between “screens are good” and “screens are bad.” There are absolutely legitimate concerns surrounding excessive recreational screen use, distraction, persuasive design, sleep displacement, problematic use, social media, gaming, privacy, commercial data collection, and the ability of some digital environments to capture and hold a young person’s attention. There are equally legitimate educational uses of technology that can support research, accessibility, communication, collaboration, creativity, skill development, differentiated instruction, and learning, and these realities can exist at the same time.
In fact, in our recent article, “Schools Should Be Prepared For Classroom Tech Pushback From Some Parents & Caregivers This New School Year”, we argued that some of the current pushback against classroom technology has been earned (3). Technology has sometimes been introduced because it was available rather than because it was educationally necessary. Devices and platforms have sometimes entered classrooms without sufficient pedagogical planning, teacher training, transparency, or consideration of what non-digital activity they might displace. However, we also argued that simply counting screen minutes doesn’t tell us whether a particular use of technology is educationally valuable, technology should have to earn its place in the classroom.
Two newly released Australian research reports from Macquarie University provide some timely evidence to add to this conversation. The first, “Best Practice in Screen Use for Education: Classroom Observation Findings, took researchers directly into classrooms to observe what teachers and students were actually doing with technology”. Researchers observed 68 classrooms across 20 New South Wales public schools, representing approximately 57 hours of classroom instruction (1). The second, “Best Practice in Screen Use for Education: Survey Findings, examined the experiences and perceptions of students, parents, teachers, school leaders, and future teachers”, with 4,628 responses retained for analysis (2). Together, these studies give us something particularly valuable, one tells us what people report and believe is happening around educational technology, while the other allows us to compare some of those perceptions with what researchers actually observed happening inside classrooms.
When considered together, these reports reinforce something we have been arguing for several years, the more useful question isn’t simply, “How much screen time are students getting?” it’s, “What are students doing with technology, why are they doing it, what educational purpose does it serve, what is it replacing, what developmental supports are present, and is the technology actually helping them learn?” (3)(4)(5)
Screens Were Present, But They Were Not Necessarily Dominating the Classroom
One of the first findings worth highlighting is that the presence of digital technology in a school did not mean students spent the entire school day staring at screens. During the classroom observations, students were not using screens at approximately 48% of the recorded observation points. Instead, students were handwriting, completing worksheets, listening to teachers, participating in discussions, interacting with classmates, or using physical classroom materials. What researchers generally observed was not an entirely digital classroom, but a blended environment where teachers moved between digital and non-digital activities depending upon the learning objective (1).
This distinction matters because “screen time” is often discussed as though it represents a single behaviour, it doesn’t. Thirty minutes watching entertainment videos, thirty minutes researching a history assignment, thirty minutes creating a presentation, thirty minutes coding, thirty minutes communicating with a teacher, and thirty minutes using an assistive communication application may all register as thirty minutes of “screen time,” yet developmentally, cognitively, and educationally these experiences can be significantly different (3)(5).
This is very similar to the position we recently outlined in “Schools Should Be Prepared For Classroom Tech Pushback From Some Parents & Caregivers This New School Year” (3). We used the example of two students spending exactly 45 minutes on Chromebooks. One might spend those 45 minutes passively clicking through repetitive digital worksheets while drifting into unrelated websites. Another might spend the same amount of time locating historical primary sources, comparing conflicting accounts, evaluating credibility, collaborating with classmates, and preparing to defend their conclusions. A screen time counter records exactly the same thing for both students, 45 minutes. Educationally, however, those experiences are very different.
The classroom observations reinforce this distinction. Students were using technology for research, inquiry, organization, practice, simulations, accessing learning management systems, completing assignments, and creating digital products. Researchers observed activities ranging from Python programming and historical source evaluation to stop motion production and digital photography (1).
This doesn’t mean that every digital activity was educationally necessary, and it doesn’t mean that an analogue alternative wouldn’t sometimes have been better. It does, however, demonstrate why simply counting minutes can become an incomplete measure of educational technology use. The better question remains, “What did the technology allow the student to do, and did that meaningfully improve the learning experience?”
Technology Should Have to Earn Its Place in the Classroom
We believe this should become one of the foundational principles surrounding educational technology. In our earlier articles, “First It Was The Phones, Now Some Want To Ban All Tech In The Classroom” (4) and “Contrary To What Some Say, YES, Technology In Classrooms Can Have a Positive Outcome on Learning – With An Important Caveat!” (5), we argued against both extremes. We don’t support introducing technology simply because it is new or because a school has purchased it. However, we also don’t support eliminating useful educational technology simply because other forms of technology have created legitimate problems. The educational objective should determine the tool, not the other way around. Sometimes that tool will be a laptop, sometimes it will be a pencil, sometimes it will be an AI platform, and sometimes it will be a printed book, laboratory experiment, face to face discussion, outdoor activity, musical instrument, physical model, paintbrush, or simply uninterrupted time to think. Good pedagogy is knowing the difference.
The Macquarie classroom observations support this more nuanced approach. Researchers found that screen use was selective rather than constant. They also observed a developmental progression from more teacher directed and scaffolded technology use among younger students toward increasingly independent, discipline-specific digital work among older students (1). That is much closer to regulated, purposeful use than either “technology everywhere” or “technology nowhere.”
The Transition Into Secondary School Deserves Much More Attention
Perhaps one of the most important findings from the survey report concerns what happens as students transition from primary into secondary education. Students in Stage 3, approximately ages 10 to 11, reported an average of 68 minutes of screen based learning at school on their most recent school day. By Stage 4, approximately ages 12 to 13, this increased to 131 minutes. Screen based learning outside school also increased substantially, while leisure screen use at school rose as students moved into secondary education (2).
Although these figures are based on self report and should therefore be treated as estimates rather than precise measurements, the pattern deserves attention. At approximately the same developmental period when children are being given greater technological independence, their exposure to increasingly complicated digital environments is expanding.
We think this is extremely important because entering secondary school doesn’t magically provide a young person with mature digital self regulation skills. However, this is often precisely when children receive greater device independence, increased homework responsibilities, more complicated learning management systems, greater access to messaging and social platforms, and less direct adult supervision. In other words, we may be increasing access at the same time that we are decreasing scaffolding. This is why we believe digital independence should be scaffolded rather than simply granted.
Tech Literacy Is Not Digital Literacy
There is a tendency to assume that because today’s youth have grown up surrounded by technology, they somehow intuitively understand it. We don’t believe that is true. As we discussed in “Tech Literacy vs. Digital Literacy” (8), many young people are extremely proficient at the how of technology. They can navigate apps, edit videos, troubleshoot devices, communicate across platforms, and learn new interfaces remarkably quickly. However, digital literacy requires something deeper, it requires understanding how technology influences behaviour, information, privacy, relationships, attention, decision-making, and society.
A young person can therefore be technologically fluent while remaining digitally vulnerable. They may know exactly how to use a social media platform without understanding why particular content is being placed in front of them. They may know how to prompt an AI system without understanding hallucination, bias, privacy, cognitive offloading, or how much of their intellectual work they have handed over to the machine. This is why, in “Understanding Digital Literacy: 7 Core Strategies” (9), we described digital literacy as involving skills such as evaluating information, critically navigating digital environments, understanding privacy and security, creating responsibly, and making informed decisions rather than simply knowing how to operate technology.
The Macquarie findings reinforce the need for this distinction. As students became older, their technology use became increasingly independent (1)(2). That independence needs to be accompanied by education about how to manage it.
Co-Regulation Before Self-Regulation
At The White Hatter, we often speak about moving from adult co-regulation toward youth self-regulation. When children are younger, adults appropriately provide more structure, supervision, boundaries, modelling, and guidance. As children demonstrate competence and maturity, those external controls can gradually be reduced. The goal isn’t permanent surveillance, the goal isn’t permanent parental control, instead, the goal is helping young people develop the internal skills necessary to make good decisions when adults are no longer watching.
This philosophy is also reflected in our position on cellphones in schools. In “Some Thoughts About Cellphones in Classrooms”(6), we highlighted regulated approaches where phones are generally put away but can be used when a teacher determines that they serve an educational purpose, during defined technology breaks, or where medical or individual learning accommodations require access. This recognizes both realities, personal devices can create significant distraction, but technology can also be a legitimate educational, accessibility, or self-management tool. This is very different from unrestricted access, but it is also different from assuming that prohibition itself teaches digital self-regulation.
Yes, digital distraction is real, and any balanced discussion of technology in education needs to acknowledge distraction. In the survey study, 52% of teachers reported that students were often or always distracted by unrelated content while using screens, while half reported distraction caused by other students using screens. Only 42% reported that students were often or always able to shift their attention away from screens when asked (2). These concerns shouldn’t be minimized.
However, this is where combining the two reports becomes particularly interesting. When researchers actually observed students in classrooms, participating students were recorded as being on task approximately 90% of the time across the lessons included in the engagement analysis. Researchers did observe unrelated activities, but they also noticed that disengagement frequently appeared connected to lesson pacing, transitions, waiting for assistance, unclear tasks, technical difficulties, or students finishing their work early rather than simply to the presence of a device (1).
These findings don’t mean devices aren’t distracting, because clearly, they can be. A multifunction digital device offers opportunities for distraction that a pencil simply doesn’t. YouTube, games, messaging, notifications, social media, shopping, AI chatbots, and effectively unlimited information can sit only a click or swipe away from the educational activity. However, the equation, “device present = student distracted”, is still too simplistic.
Technology can become the destination for distraction without necessarily being the original cause of disengagement. This is also why we have previously cautioned against overly simplified narratives linking educational technology, dopamine, and learning without considering context, behaviour, pedagogy, and the actual design of the digital activity. (7)
The important educational response is therefore not to pretend distraction doesn’t exist, nor to assume that eliminating every device automatically eliminates disengagement. Schools need classroom-management strategies, appropriate filtering, notification management, access controls, intentional lesson design, clear expectations, and deliberate periods where devices are closed entirely.
Teachers Matter More Than the Device
One of the strongest themes emerging from the classroom observation study is the importance of the teacher. Researchers saw teachers moving around classrooms so they could view student screens, positioning themselves near students requiring additional supervision, redirecting distracted students, setting time limits, providing technical assistance, modifying seating arrangements, and deliberately transitioning students away from screens when technology was no longer required. The researchers specifically identified teacher positioning, time constraints, timely technical support, and routines such as closing devices as useful technology-management strategies (1).
Sometimes the best educational use of a laptop is to close it. That isn’t anti-technology, it’s purposeful technology use. This also reinforces something we have repeatedly argued in our own writing, simply purchasing technology does not create good digital pedagogy. Teachers need training not only in how an application works, but in when to use it, why to use it, when not to use it, what it may replace, what risks accompany it, and whether it actually supports the educational objective (3)(5). Sadly, based on our own anecdotal experiences visiting and working with school districts, and from what teachers themselves have shared with us directly, this kind of support appears to be lacking in far too many schools.
Parents Are More Nuanced About Technology Than We Sometimes Give Them Credit For
The survey findings also challenge the idea that parents fall neatly into either “pro-screen” or “anti-screen” camps. Approximately 64% of surveyed parents agreed that digital devices were important for their child’s learning. At the same time, considerably fewer believed the advantages of technology simply outweighed the disadvantages (2).
We don’t see these positions as contradictory. Parents and caregivers can recognize legitimate educational value while simultaneously worrying about distraction, excessive use, social media, gaming, sleep, privacy, commercial surveillance, cognitive offloading, academic integrity, or what digital activities are replacing. In fact, we believe parents and caregivers have every right to ask schools difficult questions about educational technology.
What is this tool being used for?
What does it collect?
Where does the information go?
What does it allow my child to do that meaningfully improves learning?
Could the same educational objective be accomplished equally well, or better, without it?
What is this technology replacing?
These are not anti-technology questions. They are thoughtful and necessary educational questions. Asking when technology improves learning, when it may interfere with learning, what developmental stage it is appropriate for, and whether it is being used with clear pedagogical purpose is not an argument against technology. It is an argument for using technology intentionally. Good education has always required us to examine the tools we place in front of students, measure their benefits against their limitations, and ask whether they are actually helping students learn, think, create, collaborate, and develop the skills they will need beyond the classroom. Technology should be held to that same standard.
The School-Home Digital Gap Needs Attention
The survey also identified a communication gap. While many teachers reported regularly discussing appropriate technology use with students, far fewer reported frequently communicating with parents about how educational technology should be used at home (2). This matters because the boundary between “school technology” and “home technology” has largely disappeared. A student may receive an assignment through a learning management system, research it through a browser, collaborate through a cloud platform, watch an instructional video, communicate with classmates, use an AI assistant, and submit the finished assignment digitally. However, the same laptop may simultaneously contain YouTube, gaming, messaging, social media, streaming, shopping, and other entertainment as well as inappropriate content such as porn, violence, and gore.
For a parent and caregiver looking across the room, “my child is doing homework” and “my child is on their laptop” can look exactly the same. This is why schools should not simply tell families that technology is educational, they should show them. Explain what Grade 7 students are doing on their Chromebooks. Explain why Grade 10 students are using an AI system, explain when devices are intentionally put away, explain what information an educational platform collects, and explain what the learning objective is. As we have always said, transparency builds trust.
Privacy and Commercialization Need to Be Part of the Conversation
One area that deserves more attention than simply measuring screen exposure is what happens to student information inside educational technologies. In our article, “Google Classroom & The Commercial Exploitation Of Learning: What Educators Need To Know To Minimize Risks” (18), we examined concerns surrounding the increasing “datafication” of education and the collection of children’s information through digital learning environments.
We expanded upon this issue in, “Student Surveillance, Child Safety Tech, and EdTech: When Education + Protection Becomes Profiteering” (19), where we discussed the growing use of monitoring, surveillance, and data-collection technologies marketed to schools under the banners of learning and student safety. This is another reason “screen time” by itself is an inadequate measurement. A parent or caregivers should not only be asking how long their child used an educational platform, they should also be able to ask, “What did the platform learn about my child while my child was learning from the platform?”
AI introduces another dimension to this issue. Teachers and students need to understand that information entered into an AI system can include personally identifying, educational, confidential, or otherwise sensitive information. In, “What Not to Post Into ChatGPT As A Teacher: Some Thoughts for Educators and School Administrators” (20), we specifically addressed the need for educators to think carefully about what student and institutional information they enter into generative AI systems. AI literacy therefore also needs to include data literacy and privacy literacy.
The Digital Divide Is No Longer Just About Owning a Device
The New South Wales survey findings also reinforce another issue we frequently discuss at The White Hatter, the digital divide has evolved. Having a device doesn’t necessarily mean having equal digital opportunity. Students also need reliable connectivity, appropriate software, technical support, accessible resources, digital literacy education, adult guidance, and an environment where technology can actually be used productively. The Macquarie survey found meaningful differences in technical support across socioeconomic contexts and school environments (2), and this becomes even more important with AI.
We have already argued in ,“A Tale of Two Schools: What Teens Taught Us About AI Use in the Classroom” (12) that an emerging divide may not simply involve who has access to artificial intelligence, it may increasingly involve who has been taught how to use it well. In our conversations with students, we observed some young people being explicitly taught to use AI to explore opposing arguments, obtain alternative explanations, brainstorm, and refine their work, while others appeared to have received far less guidance about how AI could be incorporated into learning. These observations were anecdotal rather than representative research, but they raised an important question that remains relevant, “Could unequal AI education become another form of educational inequality?” Access to AI alone does not create AI literacy.
AI Makes “Screen Time” an Even Less Useful Measurement
Artificial intelligence complicates the traditional screen time conversation even further. Imagine two students sitting beside one another in a classroom, and both are looking at identical laptops and each using their screens for thirty minutes. The first student asks AI to explain a difficult concept differently, challenges the AI’s answer, compares it with their textbook, identifies an error, asks for another example, and then explains the concept independently. The second student asks AI to complete the assignment. Both students accumulated exactly thirty minutes of screen time, however, cognitively, these were radically different experiences.
This is precisely the issue we examined in, “Is AI Helping Students Think, or Thinking for Them? When Technology Supports Learning and When It Replaces It.” (10). AI can sometimes act as a scaffold, tutor, feedback mechanism, or co-learning tool. Under other circumstances, the same technology can perform the very cognitive work the student was supposed to practise. That is why the educational question can’t simply be, “Did the student use AI?” Instead, we need to ask, “What role did the AI play in the student’s learning?”
This same principle underlies our articles, “Artificial Intelligence, Teachers, Students, and Critical Thinking” (11), “Guiding Youth to Use Artificial Intelligence Ethically, Thoughtfully, and Creatively” (13), and, “When Educators Help Students Lead AI With Intention, They Don’t Cheat, They Grow!” (14). The educational objective should not simply be teaching students how to obtain better answers from AI, it should be teaching them how to use AI in ways that preserve and strengthen their own reasoning, judgment, creativity, curiosity, and ability to independently demonstrate what they know.
Why does this matter? Recently, we have seen some parents, educators, and technology critics pointing to findings from the newly released PISA 2025 results as evidence that artificial intelligence is harming student learning (21). One statistic in particular is being highlighted, that being students who reported using AI for certain school related tasks, such as summarizing assigned reading, tended to score lower in science than students who reported not using AI for those purposes.
For some context, PISA stands for the Programme for International Student Assessment. It is an international assessment coordinated by the Organization for Economic Co-operation and Development (OECD) that examines how effectively 15 year old students can apply their knowledge and skills to real world problems. PISA is generally conducted every three years and allows researchers and policymakers to compare educational outcomes across participating countries and economies.
However, before anyone forwards a statistic from PISA 2025 as proof that “AI is making kids less intelligent” or that students who use AI necessarily learn less, there is an extremely important distinction that needs to be made, association is not causation.
The PISA data show a relationship between certain patterns of AI use and academic performance. They do not establish that using AI caused the lower performance. In fact, there are several plausible explanations for the association. A student who is already struggling academically may be more likely to turn to an AI chatbot for help summarizing a difficult reading, researching an unfamiliar topic, drafting an assignment, or explaining something they do not understand. If struggling students use AI more frequently, we could see exactly the same statistical pattern even if AI itself did not cause their lower performance. This is sometimes described as reverse causality or self-selection, rather than AI use causing poorer performance, poorer performing students may be more likely to use AI for particular tasks.
Importantly, the OECD itself explicitly cautions readers against making the causal leap. In its discussion of student AI use, PISA 2025 states, “These relationships do not necessarily imply a negative impact of AI use on science performance, but may reflect a complex mix of who adopts AI and how they use it.” (pg 239) The OECD goes on to state that the findings suggest that, “moderate and intentional use of AI for schoolwork and learning may be positively related to student performance.”
That qualification is extremely important because the PISA results are considerably more nuanced than the simple message that “AI users score lower.” Students who used AI weekly for the broader purpose of helping them learn performed at a similar level to non-users after accounting for socioeconomic status. For specific tasks such as summarizing texts and conducting preliminary research, moderate AI users actually outperformed both limited users and frequent users. The OECD therefore describes the relationship between AI use and student performance as “complex.”
There is another finding that we believe deserves just as much attention. PISA found that students who frequently used AI for learning and who were taught at school to assess the quality of AI-generated information achieved slightly higher science performance than students who used AI infrequently or not at all. Approximately six in ten students across OECD countries reported being given opportunities at school to assess the quality of AI generated information. However, socioeconomically disadvantaged students were less likely to report receiving these opportunities, raising another important question about a developing AI literacy divide.
This is why we believe the PISA 2025 findings should not be reduced to a headline suggesting that AI is either “good” or “bad” for learning. The more useful question is how students are using AI, why they are using it, how frequently they are using it, and what educational scaffolding surrounds that use. There is an enormous difference between asking an AI chatbot to complete an assignment so that a student does not have to think, and using that same technology to explain a difficult concept, challenge an argument, generate practice questions, provide feedback, or help a student identify gaps in their own understanding.
For us here at The White Hatter, this distinction is fundamental. The educational goal should not be to ensure that students never use AI, and it shouldn’t be to allow AI to do their thinking for them. The goal should be to teach young people how to use these tools in ways that support thinking rather than replace it. Interestingly, when the PISA 2025 findings are read in their entirety rather than reduced to a single statistic, they arguably reinforce that position.
Producing a Better Assignment Isn’t Necessarily the Same as Learning More
Generative AI creates another important distinction between performance and mastery:
A student may submit an excellent essay but be unable to explain its argument.
A student may submit functioning computer code but be unable to explain why it works.
A student may produce the correct mathematical answer without understanding how to reproduce the process independently.
A student may submit a sophisticated research summary without having read or understood the underlying research.
The finished product may be impressive while the underlying learning remains uncertain. This doesn’t mean AI inevitably undermines learning. The issue is whether the AI is supporting the cognitive process or replacing it. This distinction sits at the heart of our recent work on AI and education. (10)(11)(13)(14)(16)
A useful question for educators before allowing AI in an assignment may therefore be, “What cognitive work am I trying to develop here, and will AI support that work or perform it for the student?” That question moves us away from an overly simplistic AI versus no AI debate and toward pedagogical purpose.
Assessment May Need to Change Along With the Technology
If AI can increasingly produce the final product, schools may need to place greater emphasis on assessing the process that produced it. In, “Why We Think Project Based Learning in Secondary Schools Is A Practical Way To Overcome Today’s AI Concerns Around Learning and Assessment” (15), we argued that project based approaches can make student thinking more visible. Rather than evaluating only a polished final product, educators can examine research notes, drafts, revisions, source choices, discussions, presentations, reflections, explanations, and the student’s ability to transfer their knowledge into a different context.
This becomes increasingly important in an AI rich classroom. Instead of relying upon an AI detector to guess whether a machine contributed to an assignment, educators can ask the student to demonstrate the knowledge, reasoning, and skills that the assignment was designed to develop (10)(15). The future of assessment may therefore need to focus increasingly on, “product + process + explanation + transfer.” The final product still matters, however, how the student arrived there may matter just as much.
AI Literacy Must Be More Than Prompt Literacy
In, “Artificial Intelligence, Teachers, Students, and Critical Thinking” (11), we argued that educators can help students use AI for brainstorming, personalized explanations, critical evaluation, ethical discussions, and other learning activities rather than treating it simply as an answer generator.
Similarly, in “Guiding Youth to Use Artificial Intelligence Ethically, Thoughtfully, and Creatively” (13), we emphasized that the objective should not simply be teaching young people how to use AI, but teaching them how to think with it without surrendering their own judgment. AI literacy should therefore include questions such as:
Who created this system?
What information might it have been trained on?
What information am I giving it?
Could the answer be wrong?
How would I independently verify it?
Could bias be influencing the output?
What cognitive work am I asking the AI to perform?
Could I explain this without the AI?
These are thinking skills, not simply technical skills. This is why we argued in, “AI in Schools? The Better Question Isn’t Whether We Should Use It, But When, Why, and How” (16) that the educational conversation needs to move beyond whether AI should exist in schools and toward the conditions under which its use supports the learning objective.
AI Is Also Changing From Something That Answers to Something That Acts
There is another development schools now need to consider. In our article, “AI In Schools: 2026 Is the Year Schools Need to Ask Not Just What AI Can Create, But What It Can Do?” (17), we argued that educational AI literacy now needs to expand beyond generative output. AI systems are increasingly capable of connecting to files, applications, calendars, browsers, institutional platforms, and other digital environments and acting on a user’s behalf. The educational question is therefore evolving from, “What did you ask the AI?” to, “What did you give the AI permission to access, remember, connect to, and do?”
This introduces what we believe will become another important component of AI literacy, permission literacy and AI agency. Students and educators increasingly need to understand not only how to interrogate an AI answer, but what authority they have granted the AI system itself (17)(20).
Sometimes Technology Simply Gets in the Way
Technology doesn’t automatically improve learning simply because it is labelled educational technology. The classroom observation report documented students struggling with passwords, software updates, dead batteries, device readiness, platform access, and other technical issues. Researchers specifically identified login delays, updates, device readiness, and technical support as factors that can interrupt lessons and create opportunities for attentional drift (1).
Every minute a teacher spends troubleshooting a password, reconnecting Wi-Fi, finding a charger, or helping students navigate a poorly designed platform is a minute potentially taken away from instruction. This is another reason technology should have to earn its place. The calculation isn’t simply, “Can this technology do something educational?” It should also include, “Does the educational benefit outweigh the friction, distraction, privacy implications, cost, training requirements, and whatever activity it is replacing?”
Accessibility Changes the Equation for Some Students
The classroom observation report also provides an important reminder about students with disabilities. Researchers observed technology functioning as assistive technology, helping students communicate, express emotions, make choices, anticipate transitions, regulate behaviour, and participate in classroom experiences. The researchers appropriately caution that these observations came from a limited specialized setting and should not be generalized to every student with a disability (1).
However, the finding demonstrates why blanket technology policies require flexibility. For some students, a device isn’t simply a screen, it may be their voice or their organizational support. It may provide text-to-speech, speech-to-text, magnification, translation, captions, alternative input, or another accessibility function that removes a barrier to learning. In these circumstances, increased “screen time” may actually represent increased access to education. This is another reason why we favour evidence informed, regulated technology policies rather than simplistic blanket approaches (4)(6).
What These Two Reports Do Not Prove
As interesting as these reports are, we also need to be careful not to make claims the research doesn’t support. The classroom study was observational. Students were not randomly assigned to digital and non-digital conditions and then compared for learning outcomes. Schools and teachers nominated classes in which digital technology would be used, introducing the possibility of selection bias. Researchers also acknowledge that their presence may have influenced teacher and student behaviour. The study should therefore be understood as a contextual snapshot of the observed classrooms, not a statistically representative picture of every classroom in New South Wales (1).
Similarly, the survey relies heavily on self-reported experiences, attitudes, and estimates of technology use. Participation was voluntary, and the researchers caution against treating the sample as statistically representative of every student, parent, teacher, or school. The survey was also cross-sectional rather than longitudinal (2).
Neither report proves, “Screens are good for education.” Neither proves, “Screens are bad for education.” What they provide is something considerably more useful, evidence about the conditions under which technology is currently being used, how stakeholders perceive it, where problems arise, and what appears to matter when technology is integrated into actual classrooms.
Moving Beyond “Screens Versus No Screens”
When these Macquarie University findings are placed beside the issues we have been examining through our work at The White Hatter, a more complete picture begins to emerge. (1)(2)(3)(4)(5) Technology can support research, creation, communication, accessibility, collaboration, differentiated instruction, feedback, and learning.
However, technology can also introduce distraction, surveillance, privacy concerns, commercial data collection, technical friction, cognitive offloading, inequity, and opportunities for students to avoid the intellectual work an assignment was intended to develop (7)(10)(18)(19)(20).
Both realities can exist simultaneously. This is why we don’t believe the educational conversation is particularly well served by either, “More technology is better.” or, “Less technology is better.” Instead, parents, caregivers, educators, and policymakers should be asking:
What is the student actually doing with the technology?
What educational objective does it support?
Why is this particular tool being used?
Could the learning objective be accomplished equally well or better without it?
What is the technology replacing?
Is the student creating, investigating, practising, communicating, or merely consuming?
Does the student have the developmental capacity to manage the distractions accompanying the device?
What information is the technology collecting?
Who has access to that information?
If AI is involved, is it supporting the student’s thinking or replacing it?
Can the student demonstrate the same knowledge without the AI?
What skills are we teaching that will eventually allow the student to regulate their own technology use?
When the technology stops adding educational value, are we willing to close the screen?
These questions move us toward a far more useful framework, one that shifts the conversation away from simply asking whether technology belongs in education and toward examining how it is being used, what purpose it serves, what skills it supports, and whether it is actually helping students learn rather than simply helping them complete the work.”
From Screen Management to Digital Independence
Perhaps the greatest opportunity identified across these reports is the transition from primary to secondary school. This appears to be a period when digital learning becomes more independent, screen exposure increases, recreational opportunities expand, parental involvement decreases, and students are expected to manage increasingly complicated digital environments (2).
Rather than treating this transition simply as the age when children receive more technological freedom, we believe it should become a deliberate period of digital independence education. Before increasing access, we should be increasing skills.
Students should be learning how persuasive design captures attention, how algorithms influence what they see, how notifications interrupt concentration, how to recognize credible information, how to protect privacy, how to secure accounts, how to communicate appropriately online, how to recognize manipulation, how AI can support or replace thinking, how to manage multiple digital demands, and perhaps most importantly, how to recognize when technology is no longer helping them accomplish what they originally intended to do (8)(9)(10)(11)(13)(17).
Families provide values, boundaries, modelling, conversation, and gradually increasing independence. Educators provide pedagogy, structured practice, digital literacy, AI literacy, classroom expectations, and opportunities to use technology productively. Schools and school districts provide policy, infrastructure, privacy protections, accessibility, professional development, and environments where healthy digital habits can be practised. Young people themselves increasingly become active participants in managing their own digital lives.
The goal shouldn’t be raising children who simply know how to operate technology, and the goal shouldn’t be raising children who can only manage technology because an adult has permanently restricted it for them. The goal should be raising young people who understand technology well enough to make informed decisions about when to use it, why they are using it, what it is doing for them, what it may be doing to them, what information it is collecting about them, when it is helping them think, when it is thinking for them, and when it is time to put it down.
For us here at The White Hatter, that is what meaningful digital literacy and digital independence should ultimately look like. It isn’t “Know Tech” because every piece of technology is inherently beneficial. It isn’t “No Tech” because every screen is inherently harmful. It’s understanding how to choose the right technology, for the right purpose, at the right developmental time, with the right education, boundaries, pedagogy, and scaffolding in place.
Digital Food For Thought
The White Hatter
Facts Not Fear, Facts Not Emotions, Enlighten Not Frighten, Know Tech Not No Tech
References
11/ https://www.thewhitehatter.ca/post/artificial-intelligence-teachers-students-and-critical-thinking
