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By Sean Jeon for ETEC_V 523 64A 2025W1 Mobile Intelligence
Mobile intelligence is entering a new phase in which traditional smartphones will no longer function as the primary interface for digital interaction. Emerging trends in wearable technology—specifically AI-powered smart display glasses paired with intelligent earbuds—are rapidly redefining what a “mobile device” is and how it integrates into daily cognition. These combined systems form a single mobile intelligence platform capable of overlaying holographic information directly into the user’s visual environment while delivering adaptive, conversational support through continuous audio feedback. This forecast examines the educational implications of such a system, imagining a near-future in which these glasses function as personalized, always-present learning assistants comparable to fictional systems such as JARVIS in Iron Man, but grounded in realistic technological trajectories.
Maybe by 2035, these AI-enhanced smart glasses have become commonplace in schools, enabling students to receive real-time scaffolding, micro-feedback, emotional support, and holographic explanation overlays. Although this appears to optimize learning efficiency, early patterns observed in current mobile-phone usage suggest deeper risks related to over-reliance, reduced cognitive resilience, and weakening of foundational thinking skills. This analysis forecasts these outcomes and argues that, despite the benefits of mobile intelligence, humanized educational structures must be intentionally protected.
In a typical 2035 classroom, students begin their lessons by wearing smart display glasses linked to an AI-powered earbud. When activated, a small holographic tutor appears—an adaptive Holo-AI Learning Companion that monitors emotional cues, recognizes learning patterns, and adjusts support moment by moment.
The device transforms traditional learning:
Diagrams appear as floating holograms.
Complex readings are summarized in real time.
Step-by-step hints are whispered instantly when needed.
At first, the classroom seems dramatically improved. Students complete work efficiently, show confidence, and rarely get stuck. However, when teachers ask them to explain why their answer is correct, students hesitate. The mobile intelligence system helps them perform tasks, but reduces the mental struggle that builds real understanding. Students start demonstrating performance without depth—a smooth learning surface hiding weaker reasoning underneath.
A credible forecast must begin by analyzing present evidence. Contemporary research and documentary analyses, including AI and the Future of Education (OpenTools.ai, 2024), show that mobile-phone–driven digital environments already influence human cognition in measurable ways. Studies indicate declines in memory retention because individuals increasingly outsource information management to their phones. Social media platforms contribute to addictive usage patterns, fragmented attention, emotional dysregulation, and heightened dependency on constant digital stimulation. The result is a widespread shift from deep, sustained cognitive engagement toward rapid, surface-level interactions.
If such outcomes arise from phone-based interaction—where access to digital systems still requires intentional action—then the risks grow considerably when the system becomes a wearable, ambient mobile intelligence device. Smart display glasses with AI assistance would no longer require conscious engagement; instead, they would continuously observe, interpret, and respond. Thus, the device becomes a cognitive partner, not merely a tool.
This leads to what may be termed the Intelligence Illusion: a condition in which learners appear competent because the mobile intelligence system fills every cognitive gap, but their capacity for independent reasoning declines. The EBS Knowledge Channel e 20th-anniversary special, 상상한 학교 2045, raises precisely this concern, depicting learners who no longer read, inquire, or reflect because an AI-connected system provides instantaneous answers. The documentary warns that while AI can deliver knowledge, it cannot generate the human processes that transform knowledge into understanding or wisdom. This aligns with the educational theory of Vygotsky (1978), who argued that knowledge construction emerges from social interaction and cognitive struggle—elements technology may inadvertently suppress.
The rise of AI-powered smart glasses also introduces new equity issues. These devices require ongoing costs:
expensive hardware
subscription-based AI services
high-speed networks
cloud storage
regular updates
This creates a digital-tax, a constant financial burden that separates students into two groups.
They continue to access real experiences—labs, outdoor learning, arts programs, travel, hands-on work, and mentorship. These experiences build creativity, confidence, leadership, and emotional maturity.
They rely more on the simulations provided by the mobile intelligence device. These simulations provide knowledge, but lack the richness and unpredictability of real life.
Over time, this divide shapes cognitive, social, and emotional development. Experience becomes a privilege. Simulation becomes the default for those with fewer resources. The problem is not simply access to technology—it is access to human development.
Given this forecast, education systems must adopt strategies that preserve and strengthen forms of human learning that AI-powered smart glasses cannot replicate.
First, classrooms must intentionally create human-sense learning environments, in which students engage in discussion, debate, collaborative problem-solving, and emotional expression without reliance on their mobile intelligence device. These activities cultivate interpersonal understanding, empathy, and critical thinking.
Second, learners must practice cognitive transparency: explaining their reasoning, evaluating their own thinking, and identifying when their smart-glasses assistant influenced their answers. This aligns with research showing that meta-cognitive reflection strengthens long-term understanding (Kirschner et al., 2018).
Third, schools must promote embodied and real-world learning—hands-on laboratory work, physical movement, outdoor exploration, and community-based projects—ensuring that learning remains anchored in human experience rather than holographic simulation.
Finally, students must be educated in AI literacy, learning how to interpret, question, and ethically engage with the mobile intelligence system. Without such training, learners may blindly accept AI-generated conclusions, losing the capacity for independent judgment.
My work at UBC HIVE gives me a clear view of why this forecast matters. I create XR learning tools for healthcare students, where good judgment and careful thinking are extremely important. I also supervise students in project-based learning, where they must explore problems, test ideas, and make decisions instead of waiting for the “right answer.”
Recently, I have noticed a strong change in how students approach learning. Many turn to AI on their phones to get quick answers instead of trying to understand the problem. They often skip the deeper thinking that helps them build real judgment. In higher level education, this is dangerous, because future professionals must learn how to question information, check accuracy, and understand the limits of any AI system.
This makes me worry about what will happen when AI-powered smart display glasses become common. If students already depend on phones for instant answers, a wearable device that gives constant explanations could make this habit even stronger. Instead of developing their own reasoning skills, students might rely on the device to think for them.
These concerns are not imaginary. They come from real behaviours I see and hear from faculties in classrooms. This forecast is simply projecting those trends into a future where mobile intelligence becomes even more powerful and harder to resist.
AI-powered smart display glasses represent a significant evolution in mobile intelligence and will likely transform educational environments by providing personalized, real-time scaffolding. However, if these devices become the primary support system for learning, they may unintentionally weaken memory, diminish cognitive resilience, heighten dependence, and deepen socioeconomic inequality.
To ensure a balanced future, educators, designers, and policymakers must intentionally protect the human aspects of learning—curiosity, creativity, collaboration, ethical judgment, emotional intelligence, and the ability to think independently. Mobile intelligence should enhance learning but must never replace the fundamental processes that make learning meaningful and human.
OpenTools.ai. (2024). AI and the future of education – Full documentary (summary). https://opentools.ai/youtube-summary/ai-and-the-future-of-education-full-documentary
EBS Knowledge Channel e. (2023). 우리는 괜찮을까? | 상상한 학교 2045 [Video]. YouTube. https://youtu.be/VBZ4giZk_EM?si=a1yxOnpony0lWW7X
Kirschner, P. A., Sweller, J., & Clark, R. E. (2006). Why minimal guidance during instruction does not work: An analysis of the failure of constructivist, discovery, problem-based, experiential, and inquiry-based teaching. Educational Psychologist, 41(2), 75-86. https://doi.org/10.1207/s15326985ep4102_1
Nye, B. D. (2015). Intelligent tutoring systems by and for the developing world: A review of trends and approaches for educational technology in a global context. International Journal of Artificial Intelligence in Education, 25(2), 177-203. https://doi.org/10.1007/s40593-014-0028-6
Vygotsky, L. S. (1978). Mind in society. Harvard University Press.