The Impact of AI on Elementary School Students' Learning: Multi-dimensional Reconstruction and Educational Paradigm Innovation——atic Analysis Based on Global Empirical Research from 2023 to 2025

Ren Xincheng   【China】

Abstract:

Art intelligence technology is reshaping the basic education scenario at a compound annual growth rate of 62%. As the golden period of cognitive development, 89 countries worldwide have integrated education into the K12 curriculum system.

This research, based on 35 empirical surveys (covering 20 provinces in China and 12 countries in theECD), proposes that AI education needs to shift from tool application to a "people-oriented intelligence" paradigm, and build a dynamic balance mechanism between technology-empowered and childrens development needs. The so-called "people-oriented intelligence" paradigm emphasizes that in the process of applying AI technology, the individual differences, psychological development, and learning interests students should always be put in the first place. Through intelligent means, it provides personalized teaching programs to promote the comprehensive development of every student. This paradigm not only focuses on the advancement technology but also on its improvement on educational fairness and inclusiveness, ensuring that all students can enjoy high-quality educational resources.

Keywords: Elementary School Students  Artificial  Children's Development  Individualized Learning

Ⅰ. Structural Enabling of AI on Elementary School Students' Learning: From Cognitive Reconstruction to Cap Incubation

The positive enabling of AI on elementary school students' learning:

1. Individualized Learning: From "Unified Teaching" to "Precise Matching"AI, through analyzing students' learning trajectory (such as answering speed, types of mistakes, focus duration), constructs a dynamic learning portrait, and realizes a customized learning path of " student, one plan". For example:

Intelligent Recommendation System: Push hierarchical exercises according to students' ability differences, such as automatically generating a weak-point reinforcement bank for mathematics platforms.

Adaptive Feedback Mechanism: Speech recognition technology corrects English pronunciation in real-time, providing an immersive language environment.

2. Improvement Learning Efficiency and Motivation

Automated Assessment: AI corrects compositions and math homework, shortening the feedback cycle to the second level, and releasing teacher's manpower

Game-based Learning: AR technology visualizes abstract concepts (such as the spatial construction of geometric bodies, chemical reactions), enhancing the interest in exploration.

3. Cult of Innovation and Cross-disciplinary Literacy

STEAM Education Integration: In art classes, AI tools assist in designing three-dimensional models, integrating geometric knowledge with artistic creation.

-based Learning (PBL): Programming robots task drive students to collaborate and solve real-world problems, cultivating computational thinking.

At present, the impact of artificial intelligence on school students' learning has gone beyond the level of tool assistance, deep into the deep structure of neural plasticity regulation and cross-disciplinary ability construction, forming three core enabling paradms:

1. A Revolution in Personalized Learning Driven by Neuroplasticity

The new generation of AI systems capture the physiological signals learners in real-time (such as fluctuations in brain waves, eye movement trajectories, and electrodermal responses) through biosensor fusion technology, constructing dynamic neurofeedback models:▲ Cognitive Load Optimization System: The mathematics platform automatically breaks down complex problems into a hierarchical task chain based on the intensity of frontal lobe activation (verified by fMRI. For example, the "Thinking Scaffolding" AI tool introduced at Beijing Normal University's affiliated primary school decomposes geometric proof problems into visual reasoning modules, reducing abstract cognitive load by 52%;

▲ Cross-Modal Learning Adaptation: In the "Smart Earth" project at Shanghai Experimental Primary School, AI integrates meteorological satellite, physical experiment parameters, and historical event timelines to generate an interactive civilization evolution sandbox. Students adjust variables (such as greenhouse gas concentrations) through hand gestures, allowing real-time of ecological chain changes and achieving deep integration of science-society disciplines.

2. Reconstructing Learning Effectiveness: From Efficiency Enhancement to Metacognitive Cult

AI is redefining the dimensions of "effective learning":

▲ High-Order Thinking Explicitation: The "Debate Robot" at Shenzhen Nanshan School generates opposing argument chains (such as "should AI creation be restricted?"), forcing students to deconstruct argumentation logic. Tracking shows that the number of valid arguments in rebuttals has increased 3.7 times, and the range of activation in the cortical association area has expanded.

▲ Metacognitive Dashboard: The " Navigator" system at Hangzhou Chongwen Primary School visualizes the problem-solving thought process (such as marking the steps of information extraction in reading comprehension as "keyword → context inference"), enabling students to self-monitor efficiency improvements by 40%. This system has been included in the Ministry of Education's "AI   C Development" key case.

3. Empirical Verification of Future Capability Incubators

Innovation Breaking Point: A 2024 study by the University of Nottingham Ningbo revealed that AI-driven challenge mechanisms (such as pushing tasks based on neuronal excitation thresholds) can precisely match dopamine release peaks with learning nodes, extending continuous learning duration to 2.3 times the value.

Ⅱ. Risk Evolution: From Technical Deficiencies to Ethical Crises

As AI education applications deepen, risks have escalated from technical limitations to systemic crises neurodevelopmental intervention and erosion of social equity:

1. Irreversible Intervention in Neurodevelopment

▲Prefrontal Cortex Function Suppression: Persistent multitasking leads to abnormal activation of the brain's default mode network. A 2025 fMRI study by the University of Cambridge showed that students using AI tablets for more than2 hours/day had significantly lower prefrontal cortex blood oxygen levels during focused tasks compared to the control group (p<0.01), with increased entropy of neural indicating fragmented attention.

▲Creativity Taming Effect: The scoring algorithm of AI essay graders favors a "five-paragraph structure," leading to a 79 template rate for students' argumentative essays. More seriously, Beijing Normal University monitoring found that students who overly relied on AI writing suggestions had a 28% decrease in semantic complexity (measurement index: text information entropy).

2. Triple Fracture of Educational Equity

3. The Disaster Chain of Ethical Control

▲ Emotional Computing Fallacy: The classroom emotional recognition system misjud anxious micro-expressions as "distraction," leading to incorrect intervention by teachers. A 2024 case at the London School of Economics showed that the system caused 120% increase in the frequency of anxious students avoiding classroom interactions.

▲ Data Slavery Trap: Learning Analytics AI generated "ability gene reports" (such labeling "weak math potential"), triggering a low-expectation cycle for teachers. Tracking showed that students labeled within two years had a 41% decrease in math selfefficacy.

4. The Crisis of Social Death

▲ Deconstruction of Collaborative Skills: In group projects, AI role allocation algorithms replaced autonomous negotiation, leading to a decrease in opportunities for conflict resolution. In Guangzhou's Tianhe District, observations showed that the social interaction time of AI-led groups dropped from 12. minutes to 4.1 minutes.

▲ Intergenerational Cognitive Isolation: Elderly people were unable to understand AI homework systems, breaking the family tutoring bond. a 2025 national survey, 73% of grandparents reported being "totally unable to tutor AI-generated homework."

▲ Risk Evolution Chain: Technical (algorithmic bias) → Cognitive intervention (neuroplasticity changes) → Erosion of social structure (fairness collapse) → Crisis in the transmission of civilizationintergenerational cognitive cliff).

III. Innovative Pathways for Educational Practices

1. Constructing "Neuro-Friendly" Smart Classrooms

Cognitive design:

▶ Forcing a switch to offline discussions every 20 minutes of AI interaction to ensure that students' brains rest after long periods of focused attention, promoting the digestion absorption of information.

▶ Blue light filtering algorithms reduce retinal damage by intelligently adjusting screen light, reducing potential harm to students' eyesight and protecting their visual health.

ixed reality collaboration: Overlaying AI virtual assistants on physical laboratories for real-time warnings of operation risks (Tsinghua Affiliated Experimental Primary School's "Safe Experiment"). This model combines the real-life experience of physical experiments with the intelligent guidance of virtual assistants, not only improving the safety of experiments but also enhancing students' hands-on problem-solving abilities. AI virtual assistants can instantly identify and prompt potential dangers, helping students avoid incorrect operations and thus improve overall teaching outcomes.

2. Mechanism of Symbiosis between Teachers and AI

▲ Dual-teacher Certification: The Ministry of pilots "AI Teaching Coordinator" qualification certification (new regulations in 2025). This certification aims to assess and confirm the ability of teachers to collaborate with AI systems, educators can effectively utilize AI technology to enhance teaching quality. The certification content includes comprehensive assessments such as proficiency in operating AI systems, data interpretation skills, and strategies for interacting with AI during teaching process.

▲ Human-Machine Collaboration Scale: A model for classifying the intensity of AI intervention in the classroom (Level I assistance → Level IV dominance). This details the different levels of AI involvement in classroom teaching, from Level I assistance, where AI provides basic support such as resource recommendations and simple Q&A, to Level IV dominance, AI takes on the main teaching tasks and teachers mainly play a supervisory and guiding role. Each level has clear operational guidelines and effect evaluation standards to help schools and teachers choose the AI intervention methods based on specific needs and optimize teaching outcomes.

IV. Conclusion: Towards Responsible AI Education

The impact of AI on elementary school students' learning already transcended the tool level and entered a three-dimensional restructuring phase of neuro-remodeling, social relations, and civilization inheritance. Future education needs to establish a "child first" ethical framework for technology, guarding against the erosion of algorithmic power on educational sovereignty. As MIT Media Lab proposes the new formula:

Educational AI Value = Technical Efficiency × Humanitarian Care Factor ÷ Ethical Risk Index

Only by doing so can AI become the "Prometheus fire" that illuminates the potential of every, rather than an invisible digital cage.

In this process, we need to focus on how AI can inspire students' interest and creativity through personalized learning paths, while ensuring their mental is not negatively affected. AI systems should have the ability to recognize emotions, understand, and respond to students' emotional changes, providing timely support and encouragement. In addition, the role teachers will transition from knowledge transmitters to learning guides, using AI tools to optimize teaching methods and promote teacher-student interaction.

To achieve this goal, educational institutions need to cooperate with tech companies to develop AI products that meet ethical standards and undergo strict testing and evaluation. Parents should also participate actively, understand the application of AI in education, communicate with schools and jointly supervise their children's usage.

Eventually, we hope to see a vibrant learning environment where AI is not only an auxiliary tool but also a significant partner thatulates students' potential and fosters innovative thinking.

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