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When AI training wheels help and hinder learning

Kim Eun-mi The author is a professor of communications at Seoul National University. Discussions about artificial intelligence are everywhere in Korea. Seminars and lectures on how to use AI are multiplying. Some expert assessments suggest that current AI systems operate at an equivalent of an IQ of 120 to 130, well above average human intelligence. With such powerful tools in hand, the opportunity cost of spending time acquiring and processing information independently has risen sharply. An official from the Ministry of Science and ICT delivers the opening speech at the “2025 Korea AI Education Festival” at KINTEX Exhibition Center II in Ilsan, Goyang, Gyeonggi, on Nov. 21, 2025. [NEWS1] Korea’s rapid embrace of AI reflects its longstanding dynamism. Much like the swift expansion of high-speed internet in the late 1990s, there is now a sense of urgency to integrate AI across all sectors. Yet the question remains whether education should follow the same pace. Unlike other fields, mistakes in education cannot easily be undone. A recent experiment by Anthropic, which developed the AI model Claude, offers a useful insight. Participants were divided into two groups and given coding tasks, with only one group allowed to use AI. As expected, the AI-assisted group completed the tasks more quickly. The more revealing result came in a follow-up experiment. When both groups were later allowed to use AI, the group that had initially worked without assistance outperformed the other. The explanation is simple. Those who struggled through the first task without technological help developed stronger problem-solving skills. Their independent efforts enhanced their capacity to think and adapt. The result suggests that prolonged reliance on AI can hinder learning, much like trying to learn to ride a bicycle while depending too long on training wheels. Related Article Gov't discusses adopting AI education programs in elementary, middle schools Cost of education jumps 2.3% in 2025 as universities hike tuition Education Ministry to roll out mandatory AI courses at universities Education reform for the AI era cannot wait Acting President Choi set to veto opposition bills on AI education and school subsidies These findings highlight the need for a careful approach to introducing AI in education. Unlike in other sectors, speed alone should not be the priority. Policymakers and educators must strike a balance between encouraging AI proficiency and preserving motivation and intellectual curiosity. True AI literacy includes knowing when not to use AI. Another concern is that rapid adoption of AI in education could deepen existing inequalities. Korea once led the world in high-speed internet access and there was widespread belief that computer education was essential to prevent students from falling behind. At the same time, the experience revealed unintended consequences. Without proper guidance or digital literacy, some children became overly dependent on online games or developed unhealthy usage patterns. This history offers a clear lesson. The impact of technology depends less on its adoption than on how it is used. The same principle applies to AI. Simply introducing the technology into classrooms does not guarantee better learning outcomes. A company representative demonstrates humanoid robot movements at the “2026 Seoul National University AI Summit” at the Global Engineering Education Center of Seoul National University in Seoul on April 2. [YONHAP] There is also concern about how AI’s instant-answer model may interact with Korea’s exam-driven education system. Students are expected to develop persistence and critical thinking by solving problems and learning from mistakes. Yet if assignments produced with minimal input through AI receive higher evaluations, students will feel compelled to use such tools. Parents face a similar dilemma. Even if they worry about the long-term effects of AI on their children’s cognitive development, they may feel pressured to subscribe to expensive AI services to keep their children competitive. The structure of the education system, which emphasizes test performance and college entrance exams, leaves little room for individual choice. If AI is layered onto a system already criticized for rote learning, excessive memorization and an obsession with correct answers, the result could be a further narrowing of thinking and a decline in overall intellectual diversity. Efforts to train AI talent, establish specialized schools and develop teacher capacity are all necessary. However, public resources are limited and priorities must be carefully set. It is worth asking whether adding AI-related initiatives on top of an already strained education system truly benefits future generations. When policies are driven by ambitious targets and timelines, there is a risk that schools focus on meeting measurable indicators rather than fostering meaningful learning. For AI to function as a constructive “training wheel” in education, certain conditions must be met. Qualified teachers must guide its use, parents need education on its impact and evaluation systems must be reformed. The ability to quickly find correct answers should no longer be considered valuable in itself. Instead, education should aim to preserve curiosity — the impulse to question what lies beyond the polished answers generated by AI. This article was originally written in Korean and translated by a bilingual reporter with the help of generative AI tools. It was then edited by a native English-speaking editor. All AI-assisted translations are reviewed and refined by our newsroom.

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XRP Longs Keep Getting Crushed On Binance – Here Is What That Imbalance Signals

XRP is trading around a critical price level. The market is showing signs of life — driven by reports of potential US-Iran negotiations that have lifted risk sentiment across financial markets. But the derivatives data on Binance is telling a more cautious story about what those signs are actually worth. Related Reading: A Key Bitcoin Signal Is Quietly Building While The Price Stays Flat: Here Is What to Watch Next A CryptoQuant report tracking XRP’s leverage structure has identified an asymmetry that cuts directly against the bullish surface reading. Over the past 30 days, long position liquidations on Binance reached approximately $39.8 million — more than double the $19.7 million in short position liquidations recorded over the same period. The market has been punishing buyers at twice the rate it has been punishing sellers. That ratio matters because it describes the current market’s relationship with optimism. Every time XRP traders have positioned for upside, the market has extracted a disproportionate cost from those positions. The geopolitical catalyst may be shifting sentiment. The leverage structure is not yet reflecting a market that has earned the right to move higher — it is reflecting one that has been repeatedly burned for trying. The bullish signs are real. The foundation beneath them is still being tested. Caution Is Winning. It Has Not Won Yet The report adds a behavioral layer that confirms what the liquidation asymmetry implies. The 30-day cumulative funding rate has registered a slightly negative value of approximately -0.000007, a modest reading, but one that has held in negative territory consistently. In derivatives markets, persistent negative funding means traders are paying to maintain short positions rather than long ones. That is not neutral positioning. It is a market that is leaning against recovery, not toward it. The combined picture — long liquidations at double the rate of short liquidations, funding tilted negative, leverage usage declining from previous periods — describes a derivatives market that has been systematically reducing its bullish exposure. That process of overextension removal is, paradoxically, the most constructive development visible in the data. When leveraged longs are cleared from a market and positioning becomes lighter and more two-sided, the mechanical risk of cascading liquidations in either direction diminishes. What remains is a market that has shed its excess but not yet found its conviction. The simultaneous decline in both long and short liquidations confirms the overextension is being resolved. The continued dominance of long liquidations confirms the resolution is not yet complete. The leverage reset is underway. It is not finished. When it is — and when liquidity returns alongside it — the conditions for a larger move will exist in a way they currently do not. The direction of that move will depend on which catalyst arrives first Related Reading: XRP Spot Buying Hits $520M While Futures Stay Negative. Here Is the Signal To Watch For A Real Move XRP Consolidates Below Resistance as Downtrend Structure Persists XRP continues to trade in a compressed range near $1.38 after a prolonged downtrend that began following its late-2025 peak. The chart shows a clear sequence of lower highs and lower lows, with price consistently rejected below the 50-day (blue) and 100-day (green) moving averages. Both indicators are sloping downward, reinforcing the broader bearish structure. The 200-day moving average (red), now positioned well above the current price, confirms that XRP remains in a macro corrective phase. The February capitulation event stands out as a structural reset, marked by a sharp spike in volume and a rapid move below $1.20 before reclaiming higher levels. Since then, XRP has stabilized, but the recovery lacks momentum. Volume has declined steadily, suggesting reduced participation rather than strong accumulation. Related Reading: Ethereum Trading on Binance Has Gone Quiet, Discover What Happens When That Changes Price is now compressing just below short-term resistance, with repeated failures to break above the descending 50-day moving average. This type of consolidation often precedes expansion, but the direction remains unclear. A reclaim of the $1.50–$1.60 zone would be required to challenge the current downtrend. Until then, XRP remains structurally weak, with consolidation reflecting equilibrium—not strength. Featured image from ChatGPT, chart from TradingView.com

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