daniyasiddiquiEditor’s Choice
Asked: 29/09/2025In:

the Asia Cup 2025

2025asiacupcricketindiasportsnewstitledefense
  1. daniyasiddiqui
    daniyasiddiqui Editor’s Choice

    The Big Picture: What "retained" means When we use "retained," it implies that India had won the last edition of the Asia Cup and then proceeded to win again in 2025. Actually: India came into the 2025 Asia Cup as defending champions, having won the last edition. India beat Pakistan in the 2025 finaRead more

    The Big Picture: What “retained” means

    When we use “retained,” it implies that India had won the last edition of the Asia Cup and then proceeded to win again in 2025. Actually:

    • India came into the 2025 Asia Cup as defending champions, having won the last edition.
    • India beat Pakistan in the 2025 final and won the title again — thereby defending (retaining) their crown.

    So yes — they did hold on to it.

    The 2025 Final: Drama, Rivalry & Redemption

    The final took place on 28 September 2025 at the Dubai International Cricket Stadium in Dubai.

    Key moments & stats

    • Pakistan batted first and were bowled out for 146 in 19.1 overs.
    • India chased that down, getting to 150/5 in 19.4 overs.

    Tilak Varma was declared Man of the Match, courtesy an undefeated 69 of 53 balls.
    A match-winning 60-run stand between Varma and Shivam Dube (33) changed the dynamics after a nervous beginning.

    The game concluded in dramatic style — with two balls remaining, Rinku Singh struck the winning boundary (a four) of the tournament from his lone ball.

     Off the Field: Controversy & Political Undertones

    This was not a cricket game — politics and emotions were high.

    • India declined to receive the trophy (and winners’ medals) from Mohsin Naqvi, who is not only President of the Pakistan Cricket Board but also Interior Minister of Pakistan, and also holds the ACC (Asian Cricket Council) role.
    • The ceremony of presentation was postponed, then abbreviated, and no proper trophy handover was done in front of media in the end.
    • No handshakes between the two sides anywhere during the tournament.
    • While India’s on-field supremacy was evident, the off-field story added layers to tension.

    Legacy & Records

    • India has now won the Asia Cup nine times overall with this victory.
    • The 2025 win sees India still ahead in Asia Cup titles among all competing countries.
    • They were also unbeaten during the 2025 tournament.

    So briefly: yes, India won the Asia Cup again in 2025, defeating Pakistan in a high‑stakes, emotionally intense final. If you’d like, I can also provide you with player ratings, scorecards, or a ball‑by‑ball account—do you want me to dig that up?

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daniyasiddiquiEditor’s Choice
Asked: 27/09/2025In:

outperform in the coming years

future trendsgrowth sectorsmarket outlooksector rotationtechnology trendsthematic investing
  1. daniyasiddiqui
    daniyasiddiqui Editor’s Choice

     1. Artificial Intelligence & Automation Topic: The rise of smart machines and decision-making systems Why it matters: AI is moving from "cool tech demo" to business-critical infrastructure. Every industry—healthcare, logistics, and more—are attempting to understand how they can use AI to save mRead more

     1. Artificial Intelligence & Automation

    Topic: The rise of smart machines and decision-making systems

    Why it matters:

    • AI is moving from “cool tech demo” to business-critical infrastructure.

    Every industry—healthcare, logistics, and more—are attempting to understand how they can use AI to save money, improve decision-making, or customize customer experiences.

    Key winners:

    • Semiconductors & hardware (e.g. Nvidia, AMD, TSMC)
    • AI infrastructure & cloud platforms (Microsoft Azure, AWS, Google Cloud)
    • AI software & services (enterprise AI tools, generative AI startups)

    Human insight:

    AI is no longer a buzzword—it’s becoming the productivity driver of the 21st century. Just like the internet in the 1990s. Expect this theme to take shape but last for decades.

    2. Clean Energy & Climate Tech

    Theme: Decarbonization of the global economy

    Why it matters:

    • Governments are spending trillions on green energy transitions.
    • Climate change is now a political issue no longer—it’s a real business and risk management issue.
    • Energy security has become a geopolitics, and it’s pushing nations towards renewables.

    Big winners:

    • Solar, wind, and hydrogen industries
    • Battery tech / energy storage
    • Carbon capture and smart grid infrastructure
    • EV ecosystem (cars, charging, raw materials like lithium, cobalt)

    Human insight:

    This is a long game. These types of transitions will last decades, but the policy-backed momentum and demand-led momentum are now in place. Volatility will be there, but the trend is irreversible.

     3. Healthcare Innovation & Biotech

    Theme: Personalized medicine, biotech innovation, and aging populations

    Why it matters:

    • The world population is aging quickly, especially in the West, Japan, and China.
    • Medical technology is evolving faster than ever—CRISPR, mRNA, gene therapy, AI diagnostics.
    • COVID accelerated biotech investment and shifted R&D timelines.

    Main beneficiaries:

    • Biotech firms with emerging therapies
    • Pharma firms with strong R&D pipelines
    • Health-tech startups focused on telemedicine, diagnostics, and wearable health

    Human insight

    With human life expectancy growing, healthcare will no longer be curing disease, but longevity and quality of life. In this space, innovation has tangible, emotional value for consumers, creating long-term investment prospects.

    4. Digital Infrastructure & Cybersecurity

    Theme: An increasingly interdependent, yet increasingly vulnerable digital world

    Why it matters:

    • The digital economy keeps growing—more data, more devices, more cloud.
    • Cyber attacks are getting out of hand, and no business or government has immunity.
    • Regulatory pressure is rising to shield consumer data.

    Big winners:

    • Cloud computing businesses
    • Cybersecurity platforms (CrowdStrike, Palo Alto Networks, Zscaler, etc.)
    • Data center REITs and fiber-optic network companies

    Human insight:

    Digital infrastructure is the pipes and roads of the new economy. You don’t always see it, but you depend on it. As reliance grows, so will the importance—and profitability—of protecting and expanding that infrastructure.

     5. Consumer Tech & Experience Economies

    Theme: Digital-first, personalized lifestyles

    Why it matters:

    • Consumers, especially Gen Z and Millennials, value experiences more than material possessions.
    • There is more emphasis on digital, on-demand, frictionless everything.
    • AI is making personalization at scale possible.

    Key beneficiaries:

    • Streaming, gaming, and creator platforms
    • Deeply personalized e-commerce
    • Augmented/virtual reality (AR/VR) for next-generation experiences

    Human insight:

    It’s not just what people buy—it’s how they live, connect, and entertain. Companies that understand evolving lifestyles will dominate.

    6. India and Emerging Markets

    Theme: Global economic rebalancing

    Why it matters:

    • India will likely be the fastest-growing large economy in the decade ahead.
    • Rising middle class, digital adoption, infrastructure growth.
    • Emerging markets are decoupling from China and becoming more diversified.

    Principal beneficiaries:

    • Indian tech and banking
    • Consumer and fintech plays
    • Emerging market ETFs with a South Asia, Africa, and LatAm focus

    Human insight:

    The world is shifting away from a U.S.-centric unipolar economic model towards a more multipolar world. Sophisticated investors who understand the nuance of these economies—beyond the best-selling headlines—can create substantial alpha here.

    7. Education, Reskilling & Human Capital

    Topic: Continuous learning in an AI-powered world

    Why it’s important:

    • Traditional work roles are being transformed by AI.
    • People will need to reskill, adapt, and learn continuously.
    • The education sector is being disrupted through edtech, microlearning, and certifications.

    Principal beneficiaries:

    • EdTech platforms (Coursera, Duolingo, BYJU’S, etc.)
    • Corporate learning platforms
    • Vocational training / STEM-centric initiatives

    Human insight:

    The future belongs to the ones who adapt fastest. Companies that help people do that—through accessible, affordable education—have an expanding and sticky customer base.

    What About Legacy Sectors?

    Financials?

    Still in it—especially with rising interest rates improving margins. But legacy banks have to catch up with fintech innovation and regtech.

    Industrials & Infrastructure

    Yes, especially if they are connected with clean energy, defense, automation, or public-private partnerships in the new world.

    Real Estate?

    Selective bets (e.g., data centers, logistics, senior housing) could perform better, but traditional commercial real estate lags in a hybrid workplace.

    Last Thought

    “Themes come and go, but megatrends change everything.”

    The above-discussed industries aren’t trends—they’re tied to fundamental global shifts in how we:

    • Power the world
    • Heal and extend human life
    • Communicate and safeguard data
    • Educate ourselves
    • Consume and invest
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daniyasiddiquiEditor’s Choice
Asked: 27/09/2025In:

CAPE, P/E, or market cap / GDP

cape ratioequity marketsmarket cap to gdpp/e ratiostock valuationsvaluation metrics
  1. daniyasiddiqui
    daniyasiddiqui Editor’s Choice

    What Do We Mean by "Valuations Are Stretched"? When we describe the market as being "stretched," we generally mean: "Stock prices are rising more rapidly than earnings, fundamentals, or the economy as a whole justify." In other words, investors can be overpaying for too little in return. That can haRead more

    What Do We Mean by “Valuations Are Stretched”?

    When we describe the market as being “stretched,” we generally mean:

    • “Stock prices are rising more rapidly than earnings, fundamentals, or the economy as a whole justify.”
    • In other words, investors can be overpaying for too little in return.

    That can happen when:

    • Interest rates are low and everybody’s searching for returns.
    • There’s more optimism than it deserves about what the future holds (e.g., with AI or tech hype).
    • Or investors just forget that markets are cyclical.

    Valuation Metrics (And How to Interpret Them)

    1. Price-to-Earnings (P/E) Ratio

    • Most widely used metric. It indicates how much investors are paying for $1 of earnings.
    • P/E = Stock Price / Earnings per Share

    Example: If a stock is selling at $100 and has earnings of $5 per share, its P/E is 20.

     What’s “Normal”?

    • Traditionally, the S&P 500’s average P/E is about 15–16.

    As of late 2025, it’s currently sitting at 20–24, depending on the source and whether forward or trailing earnings are in use.

     Why It Can Be Misleading:

    • During periods of high inflation or recession, earnings decline, making the P/E artificially shoot up.
    • Or during booms, earnings increase dramatically, making the P/E look sane even as prices are rising quickly.
    • Bottom Line: An above-average P/E means the market is anticipating a lot of future growth—possibly, perhaps not.

    2. Cyclically Adjusted P/E (CAPE) Ratio

    • Also known as the Shiller P/E, this calculation averages earnings over 10 years to account for business cycles.
    • CAPE = Price / 10-year inflation-adjusted average earnings

    What’s “Normal”?

    • Historical average is about 16–17.
    • 2000 (dot-com bubble): 44.
    • In 2008 (crash): it dropped to 15.
    • In 2025: it’s about 30–33 — historically high.

    What It Tells Us:

    • CAPE removes short-term noise, giving a longer-term view of whether markets are overheating.
    • Right now, it’s saying: “We’re well above average.”

    But critics argue that:

    • The economy has changed (tech, global markets, interest rates).
    • Comparing to historical CAPE may no longer be apples-to-apples.

    Bottom Line: CAPE is sounding the alarm. Not so much a crash, but higher risk.

    3. Market Cap-to-GDP Ratio (“Buffett Indicator”)

    A favorite of Warren Buffett’s.

    • It’s how much the combined value of all publicly traded stocks compares to the GDP (economic output) of a country.
    • If the market is valued significantly more than what the economy actually produces, it’s said to be overvalued.

     What’s “Normal”?

    • Historically: roughly 80%–100% is acceptable.
    • Today in the U.S.: It’s well over 160%.
    • In India (as of late 2025): Roughly 120%+, also higher than long-run average.

    Interpretation

    • It means investors are betting the market will grow faster than the economy really is, which would be bullish.
    • But again, again, globalization and intangibles (e.g., software/IP) mean that GDP isn’t everything.

    Bottom Line: Market cap-to-GDP is saying the market is hot.

    So… Are We in a Bubble?

    Not necessarily.

    Yes, valuations are high—historically high, actually. But don’t think for a moment that a crash is imminent. It just means the margin for error is thin. If:

    • Earnings struggle…
    • Inflation continues high…
    • Rates rise further…
    • Or geopolitical developments spook markets…
    • …then a correction is likelier.

     But Context Matters

     In 2000 (Dot-Com Bubble):

    • Few firms reported earnings.
    • Stocks such as Pets.com were worth billions based on fantasies.
    • CAPE was stratospheric.

    In 2025

    Most high-valuation companies today (Apple, Microsoft, Nvidia) are very profitable.

    • They dominate AI, cloud, chips, and other disruption domains.
    • They have cash-rich balance sheets, not speculation.

    So, while the ratios might look stretched, the underlying fundamentals are far healthier than they ever were in past bubbles.

     What Should Investors Take Away From This?

    High Valuation = High Expectation

    Investors are pricing in solid earnings, innovation, and expansion. If those hopes are met or exceeded, stocks can still go up—even at high levels.

     But It Also Implies Greater Risk

    There is less room for disappointment. If interest rates increase further, or if earnings growth slows, prices can fall sharply.

    It’s a Stock Picker’s Market

    EWide indices may be overvalued. But not all stocks or sectors are overvalued. Look for:

    • Undervalued industries (energy, financials, etc.)
    • Growth at reasonable prices (GARP)
    • Global diversification

     Last Word

    Are valuations stretched?

    Yes—versus history. But history doesn’t repeat. It rhymes.

    The trick is not to panic, but to understand the risk/reward trade-off. When valuations are high:

    • Be selective.
    • Be disciplined.

    Hold on to companies with real earnings, good balance sheets, and a lasting advantage.

    Valuations alone do not cause a crash. But they can tell you how susceptible—or resilient—the market will be when the unexpected arrives.

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daniyasiddiquiEditor’s Choice
Asked: 27/09/2025In:

growth or tech stocks

discounted cash flowgrowth stocksinterest ratesmonetary policystock valuationstech stocks
  1. daniyasiddiqui
    daniyasiddiqui Editor’s Choice

    First, What Are Long-Term Interest Rates? Long-term interest rates—such as the yield on the 10-year U.S. Treasury bond—measure the price of borrowing money for extended periods of time. They're typically shaped by: Expectations of inflation Central bank actions (such as Fed rate decisions) GovernmenRead more

    First, What Are Long-Term Interest Rates?

    Long-term interest rates—such as the yield on the 10-year U.S. Treasury bond—measure the price of borrowing money for extended periods of time. They’re typically shaped by:

    • Expectations of inflation
    • Central bank actions (such as Fed rate decisions)
    • Government debt issuance
    • World economic outlook

    And whereas short-term rates are directly related to central bank actions (such as the Fed Funds Rate), long-term rates capture what investors believe about the future: growth, inflation, and risk.

    Why Do Long-Term Rates Matter to Growth/Tech Stocks?

    Let’s begin with a investing fundamentals rule of thumb:

    • The value of a stock is the present value of its future cash flows.
    • Here’s where higher rates enter the picture:
    • As interest rates rise, future cash flows are discounted more and more.
    • That is, those future profits are less valuable today.

    And growth/tech stocks—many of which have huge profits years from now—take the biggest hit.

    So when long-term rates increase, the math of valuation begins to work against such companies.

    Why Are Tech and Growth Stocks Particularly Sensitive?

    1. They’re Priced for the Future

    Most growth stocks—picture companies like Tesla, Amazon, Nvidia, or high-growth SaaS companies—invest huge amounts today in expectation of grand rewards down the line.

    Their valuations are constructed on the premise that:

    • They’ll continue growing fast for years to come.
    • Profits in the future will support lofty prices today.

    But when interest rates go up, those “big profits down the road” are discounted more, so their current value (and thus their stock price) is less.

    2. They Tend to Depend on Inexpensive Capital

    Startups and high-growth companies frequently borrow funds or issue equity to drive growth. Higher interest rates result in:

    • Borrowing costs are higher.
    • Venture capital disappears.
    • Capitalists insist on profitability earlier.

    This can compel companies to reduce expenses, postpone expansion, or increase prices, all of which can hamper growth.

    Real-World Example: The 2022-2023 Tech Sell-Off

    When inflation surged in 2022 and the Federal Reserve hiked interest rates aggressively, we witnessed:

    • The 10-year Treasury yield jump sharply
    • High-growth tech stocks tank, with many dropping 40–70% from peak

    Investors switch into value stocks, dividend payers, and defensive sectors (such as energy, utilities, and healthcare)

    It wasn’t that Meta, Shopify, and Zoom were doing poorly. It was that their future profits counted less in a higher-rate world.

    But It’s Not All Bad News

    1. Some Tech Companies Are Now Cash Machines

    The big-cap tech giants—such as Apple, Microsoft, Alphabet—are now enormously profitable, cash-rich, and less dependent on borrowed cash. That makes them less sensitive to rate moves than smaller, still-rising tech names.

    2. Rate Hikes Eventually Peak

    When inflation levels off or the economy decelerates, central banks can stop or reverse rates, reducing pressure on growth stocks.

    3. Innovation Can Outrun the Math

    At times, the force of disruption is compelling enough to overcome increasing rates. For instance:

    • The emergence of AI is allowing businesses to create efficiencies that fuel growth—even in an elevated-rate world.

    Some tech infrastructure plays (such as Nvidia) can be treated as a utility, not a bet.

     What Should Investors Do?

    Understand Your Exposure

    Not all tech stocks are alike. A growthy, loss-making AI startup will act very differently from a cash-generation-rich enterprise software business.

    Watch the Yield Curve

    The slope of the yield curve (short term vs long term rates) will say a lot about what the market expects for growth and inflation. A steepening curve tends to be optimistic economically (favorable to cyclicals), but an inverted curve can portend issues down the road.

     Diversify by Style

    An average portfolio could have both:

    • Growth stocks (for long-term growth)
    • Value/dividend-paying stocks (to provide cushions against rate shocks)

     The Bottom Line

    Increasing long-term interest rates have the effect of gravity on growth stocks. The higher the rates, the greater the pull on valuations.

    But this does not imply doom for tech. It means investors must:

    • Recalibrate expectations
    • Focus on quality
    • And remember that not all tech grows in the same environment

    Just as low rates fueled the rise of growth stocks over the past decade, higher rates are now reshaping the landscape. The companies that survive and adapt—those with real earnings, real products, and real cash flow—will come out stronger.

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daniyasiddiquiEditor’s Choice
Asked: 27/09/2025In: , ,

a sustainable driver for stock valuat ...

ai boommarket speculationspeculative bubblesustainable growthtechnology stocks
  1. daniyasiddiqui
    daniyasiddiqui Editor’s Choice

     First, What’s Driving the AI Boom? Since the launch of models like ChatGPT and the explosion of generative AI, we’ve seen: Skyrocketing demand for computing power (GPUs, data centers, cloud infrastructure). Surging interest in AI-native software across productivity, design, healthcare, coding, andRead more

     First, What’s Driving the AI Boom?

    Since the launch of models like ChatGPT and the explosion of generative AI, we’ve seen:

    • Skyrocketing demand for computing power (GPUs, data centers, cloud infrastructure).
    • Surging interest in AI-native software across productivity, design, healthcare, coding, and more.
    • Unprecedented capital allocation from tech giants (Microsoft, Google, Amazon) and venture capitalists alike.
    • Public excitement as people begin using AI in real life, every day.

    All this has culminated in huge stock market profits in AI-cored or even AI-peripherally related companies:

    • Nvidia (NVDA), perhaps the poster child of the AI rally, is up more than 200% in just the last year at times.
    • AI startups are overnight achieving billion-dollar valuations.
    • Even firms with nebulous AI strategies (such as dumping “AI” into investor presentations) are experiencing stock spikes—a telltale sign of a bubble.

    astructure (cloud, chips, data pipes) is being built today. The actual profit boom might still be years out, so high valuations today for the market leaders creating the infrastructure are understandable.

    Why Others Believe It’s a Bubble

    In spite of all the hope, there are some warning signs that cannot be overlooked:

    1. Valuations Are Very Extended

    A lot of AI stocks are priced at Price-to-Earnings ratios that are illogical, particularly if growth decelerates by even a fraction. Nvidia, for instance, is priced to perfection. Any miss in earnings could lead to violent falls.

    2. Herd Mentality & Speculation

    We’ve seen this before—in dot-com stocks in the late ‘90s, or crypto in 2021. When people invest because others are, not because of fundamentals, the setup becomes fragile. A single piece of bad news can unwind things quickly.

    3. Winner-Takes-Most Dynamics

    AI has huge scale economies, so a handful of companies can potentially grab everything (such as Nvidia, Microsoft, etc.), but there are hundreds of others—small caps in particular—that could be left in the dust. That is risk for individual investors pouring into “AI-themed” ETFs or microcaps.

    4. Too Much Emphasis on Frenzy, Not ROI

    Most firms are putting “AI” on earnings calls and press releases simply to get on the bandwagon. But not every AI is revenue-producing, and some won’t be. If firms can’t effectively monetize their AI strategies, the market could correct hard.

    So… Is It a Bubble?

    Perhaps it’s both.

    • A well-known Scott Galloway quote captures it well:
    • “Every bubble starts with something real.”

    AI exists. It’s revolutionary. But the rate of investor hopes might be outrunning the rate of real-world deployment.

    Over the near term, we could witness volatility, sector corrections, or even mini-bubbles burst (particularly for loss-making or overhyped companies). But in the long term, AI is set to become one of the greatest secular trends of the 21st century—comparable to electricity, the internet, and mobile computing.

    Last Thought

    Ask yourself this:

    • Will you expect to see AI applied to every business, every industry, and almost every job in the coming decade?
    • Will you expect that some firms will not change, while others will drive the next generation of innovation?

    If the answer is yes, then the AI boom has a solid fundamental argument. But as with all big technology changes, timing and picking are key. Not all stocks will be a winner—even if there is an AI boom.”.

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daniyasiddiquiEditor’s Choice
Asked: 25/09/2025In: ,

assessment and feedback

ai in educationai-feedbackedtechlanguage-assessmentlanguage-learningpersonalized-learning
  1. daniyasiddiqui
    daniyasiddiqui Editor’s Choice

     The Timeless Problem with Learning Language Language learning is intimate, but traditional testing just can't manage that. Students are typically assessed by rigid, mass-produced methods: standardized testing, fill-in-the-blank, checklist-graded essays, etc. Feedback can be delayed for days, frequeRead more

     The Timeless Problem with Learning Language

    Language learning is intimate, but traditional testing just can’t manage that. Students are typically assessed by rigid, mass-produced methods: standardized testing, fill-in-the-blank, checklist-graded essays, etc. Feedback can be delayed for days, frequently in the form of generic comments like “Good job!” or “Elaborate on your points.” There’s little nuance. Little context. Little you engaged.

    That’s where AI comes in—not to do the teachers’ job, but as a super-competent co-pilot.

     AI/LLMs Change the Game

    1. Measuring Adapted Skills

    • AI models can examine a learner’s language skills in real time, in listening, reading, writing, and even speech (if integrated with voice systems). For example:
    • As a learner writes a paragraph, my LLM can pass judgment on grammar, vocabulary richness, coherence, tone, and argument strength.
    • Instead of just giving a score, it can explain why a sentence may be unclear or how a certain word choice could be improved.
    • Over time, the model can track the learner’s progress, detect plateaus, and suggest focused exercises.

    It’s not just feedback—it’s insight.

    2. Personalized Feedback in Natural Language

    Instead of “Incorrect. Try again,” an AI can say:

    “‘You’re giving ‘advices’ as a plural, but ‘advice’ is an uncountable noun in English. You can say ‘some advice’ or ‘a piece of advice.’ Don’t worry—this is a super common error.'”

    This kind of friendly, particular, and human feedback promotes confidence, not nervousness. It’s immediate. It’s friendly. And it makes learners feel seen.

    3. Shifting to Level of Proficiency and Learning Style

    AI systems are able to adjust the level and tone of their feedback to meet the learner’s level:

    • For beginning learners: shorter, more direct explanations; focus on basic grammar and sentence structure.
    • For advanced learners: feedback might include stylistic remarks, rhetorical impact, tone modulations, and even cultural context.

    It also has the ability to understand how the individual learns best: visually, by example, by analogy, or by step-by-step instructions. Think of receiving feedback described in the mode of a story or in the way of colored correction, depending on your preference.

    4. Multilingual Feedback and Translation Support

    For multilingual students or ESL, AI can specify errors in the student’s home language, compare the structures of different languages, and even flag “false friends” (i.e., words that are the same but have different meanings in two languages).

    • “In Spanish, ’embarazada’ means pregnant—not embarrassed! Easy mix-up.”
    • That’s the type of contextual foundation that makes feedback sticky.

    5. Real-Time Conversational Practice

    With the likes of voice input and chat interfaces, LLMs can practice real-life conversations:

    • Job interview, travel scenario, or conversation practice course.
    • Giving feedback on your pronunciation, tone, or idiomatic usage.
    • Even role-reversal (e.g., “pretend that I were a traveler in Japan”) to get used to different contexts.

    And the best part? No judgment. You can make mistakes without blushing.

    6. Content Generation for Assessment

    Teachers or students may ask AI to create custom exercises based on a provided topic or difficulty level: teaching

    • Fill-in-blank exercises based on vocabulary from a recent lesson.
    • Comprehension questions based on a passage the learner wrote.
    • Essay prompts based on student interests (“Write about your favorite anime character in past tense.”)
    • This makes assessment more engaging—and more significant.

     Why This Matters: Personalized Learning Is Powerful Learning

    Language learning is not a straight line. Others struggle with verb conjugation, others with pronunciation or cultural uses of language. Others get speech-tongue-tied, others are grammar sticklers who can’t write a wonderful sentence.

    LLMs are able to identify such patterns, retain preferences (with permission), and customize not only feedback, but the entire learning process. Picture having a tutor who daily adjusts to your changing needs, is on call 24/7, never gets fatigued, and pumps you up each step of the way.

    That’s the magic of customized AI.

    Of Course, It’s Not Perfect

    • Come on, let’s be realistic—AI has its limits.
    • It will sometimes fail to pick up subtleties of meaning or tone.
    • Feedback at times was too pleasant, or not harsh.
    • It also lacks cultural awareness or emotional intelligence in edge cases.

    And let’s not forget the risk of students becoming too reliant on AI tools, instead of learning to think by themselves.

    That’s why human teachers matter more than ever before. The optimal model is AI-assisted learning: teachers + AI, not teachers vs. AI.

    What’s Next?

    The future may bring:

    • LLMs tracking a student’s work such as an electronic portfolio.
    • AI with voice recognition utilized in the assessment of speaking fluency.
    • AI grading lengthy essays with feedback that is written in a tone in which one would speak.

    Even writing partners who help you co-author tales and revise and explain along the way.

     Final Thought

    Personalized language assessment with LLMs isn’t a matter of time-saving or feedbackscaling—it’s a matter of giving the learner a sense of having been heard. Inspired. Empowered. When a student is informed, “I see what you’re attempting to say—here’s how to say it better,” that’s when real growth happens.

    And if AI can make that experience more available, more equitable, and more inspiring for millions of learners across the globe—well, that’s a very good application of intelligence.

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daniyasiddiquiEditor’s Choice
Asked: 25/09/2025In:

writing and second-language writing g ...

formative-assessmentlanguage-assessmentlanguage-learningsecond-language-writingwriting-assessmentwriting-skills
  1. daniyasiddiqui
    daniyasiddiqui Editor’s Choice

    1. Vary Types of Writing over Time One writing assignment is never going to tell you everything about a learner's development. You require a variety of prompts over different time frames — and preferably, those should match realistic genres (emails, essays, stories, arguments, summaries, etc.). ThisRead more

    1. Vary Types of Writing over Time

    One writing assignment is never going to tell you everything about a learner’s development. You require a variety of prompts over different time frames — and preferably, those should match realistic genres (emails, essays, stories, arguments, summaries, etc.).

    This enables you to monitor improvements in:

    • Genre awareness: Are they able to change tone and structure between an academic essay and a personal email?
    • Cohesion and coherence: Are their ideas becoming more coherent over time?
    • Complexity and accuracy: Are they employing more advanced grammar and vocabulary without raising errors?
    • Tip: Give similar or comparable tasks at important intervals (e.g., every few months), not only once at the end.

    2. Portfolio-Based Assessment

    One of the most natural and powerful means of gauging L2 writing development is portfolios. Here, students amass chosen writing over time, perhaps with reflections.

    Portfolios enable you to:

    • Monitor progress week by week, month by month, or even year by year.
    • Make comparisons between early drafts and improved versions, stimulating metacognitive reflection.
    • Invite students to reflect on what they have learned and what differed in their approach.

    Why it works: It promotes ownership and makes learners more conscious of their own learning — not only what the teacher describes.

    3. Holistic + Analytic Scoring Rubrics

    Both are beneficial, but combined they provide a better picture:

    • Holistic scoring provides a general impression of quality (such as band scores in IELTS).
    • Analytic scoring divides writing into categories: content, organization, grammar, vocabulary, cohesion, etc.
    • To measure change over time, analytic rubrics are more effective — they indicate whether grammar got better, even if content remained constant, or if structure got stronger.

    Best practice: Apply the same rubric consistently over time to look for meaningful trends.

     4. Make Peer and Self-Assessment a part of it

    Language learning is social and reflective. Asking learners to review their own and each other’s writing using rubrics or guided questions can be potent. It promotes:

    • Awareness of quality: They begin to notice characteristics of good writing.
    • Growth mindset: They become able to view writing as something that can be developed.
    • Metacognition: They reflect on their decisions, not only on what they got wrong.

    Example: Ask, “What’s one thing you did better in this draft than in the last?” or “Where could you strengthen your argument?”

     5. Monitor Fluency Measures Over Time

    Occasionally, a bit of straightforward numerical information is useful. You can monitor:

    • Word count per timed writing task
    • Sentence length / complexity
    • Lexical diversity (How many different words are they employing?)
    • Error rates (mistakes per 100 words)

    These statistics can’t tell the entire story, but they can offer objective measures of progress — or signal problems that need to be addressed.

    6. Look at the Learner’s Context and Goals

    Not every writing improvement appears the same. A business English student may need to emphasize clarity and brevity. A pupil who is about to write for academic purposes will need to emphasize argument and referencing.

     Always match assessment to:

    • Learner targets (e.g., IELTS pass, writing emails, academic essays)
    • Instructional context (Are they intensively or informally learning?)
    • First language influence (Certain structures may emerge later depending on L1)

    7. Feedback that Feeds Forward

    • Assessment isn’t scoring — it’s feedback for improvement. Comments should:
    • Pinpoint trends (e.g., “You tend to drop article use — let’s work on that.”)
    • Provide strategies, not corrections
    • Prompt revision — the easiest indicator of writing growth is in how students can revise their own work

    Example: “Your argument is clear, but try reorganizing the second paragraph to better support your main point.”

    8. Integrate Quantitative and Qualitative Evidence

    Lastly, keep in mind that writing development isn’t always a straight line. A student may try out more complicated structures and commit more mistakes — but that may be risk-taking and growth, rather than decline.

    Make use of both:

    • Quantitative information (rubric scores, error tallies, lexical range)
    • Qualitative observations (student self-report, teacher commentary, revision history)
    • Combined, these paint a richer, more human picture of writing development.

     In Brief:

    Strong approaches to measuring second-language writing progress over time are:

    • With a range of writing assignments and genres
    • Keeping portfolios with drafts and reflection
    • Using consistent analytic rubrics
    • Fostering self and peer evaluation
    • Monitoring fluency, accuracy, and complexity measures
    • Aligning with goals and context in assessment
    • Providing actionable, formative feedback
    • Blending numbers and narrative insight
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