Reading 2026-08 Test 15

Exam month: 2026-08

In this test

About this set: compiled and lightly cleaned up from real test material that test-takers recalled. IELTS draws from a global question pool, so this material circulates worldwide. To give you a complete, sittable test, material reported around the same period is assembled together — so a set may combine content from several exam dates, not one single sitting. Any audio is a recreation for practice. Organized for study convenience. Based on test-taker recalls — not official IELTS material.

Reading Passage 1: The Spinning Jenny: A Wool Revolution

The Industrial Revolution, spanning roughly from 1760 to 1850, began in the heart of northern England and forever altered the landscape of global manufacturing and social structures. Before this era of rapid technological expansion and urbanization, the production of cloth from raw materials took place almost exclusively within a decentralized network known as "cottage industries." In these rural settings, farming was the primary mode of existence for the vast majority of the population. Textile work was regarded as a supplemental, seasonal activity conducted within the confines of the family home to bolster meager agricultural incomes. This "Domestic System" relied on a strict division of labor. Entire families were involved in the laborious process: men typically handled the heavy weaving on wooden looms, while young children assisted in the messy tasks of carding and cleaning raw wool or cotton. However, the crucial and time-consuming task of spinning these raw materials into consistent threads or yarns was almost always the domain of wives and daughters.
By the mid-18th century, however, this traditional domestic system was increasingly viewed as slow, inefficient, and incapable of meeting the demands of an expanding British Empire. As the global appetite for textiles grew, particularly in colonial markets, merchants became increasingly frustrated by the logistical gap between supply and demand. Transporting bulky raw materials to dozens of isolated, rural cottages and waiting weeks for finished goods to be painstakingly handmade was both expensive and unpredictable. The industrial imbalance reached a breaking point with the invention of the "flying shuttle" by John Kay in 1733, which allowed weavers to produce much wider fabrics at double the previous speed. While the weavers flourished, the spinners—still working by hand on a traditional wheel that produced only one thread at a time—simply could not keep up with the voracious demand for yarn.
The solution emerged from the ingenuity of James Hargreaves, a humble weaver and carpenter born near Blackburn, Lancashire, around 1720. Despite receiving no formal education and remaining unable to read or write throughout his life, Hargreaves possessed an extraordinary innate mind for mechanical engineering and spatial problem-solving. The legendary origin of his most famous invention involves a domestic accident where his daughter, Jenny, supposedly knocked over the family’s heavy spinning wheel. As the device lay sideways on the floor, Hargreaves was struck by a peculiar observation: the spindle continued to revolve rapidly in an upright, vertical position even though the drive wheel was horizontal. This observation sparked a revolutionary realization—that a single horizontal wheel could, through a series of belts, power an entire line of multiple vertical spindles simultaneously.
In 1764, after several months of experimentation, Hargreaves constructed the first working prototype of what would become known as the "Spinning Jenny." Constructed primarily of wood to keep costs low and weight manageable, the machine initially featured many vertical spindles—early models typically had eight—which were all powered by a single large wheel turned by the operator’s right hand. This invention represented a massive leap in productivity, effectively allowing one spinner to do the work of eight people. However, the path to innovation was fraught with controversy. Some historians suggest that Hargreaves did not work in total isolation but may have observed and improved upon an earlier, unpatented design created by Thomas Height (also known as Thomas Highs), a fellow inventor from the same region. A sophisticated control cord was used to connect the power from the wheel to the spindles, ensuring that all threads were spun with a relatively uniform twist.
The Jenny was not without its technical drawbacks. The thread produced by the Jenny was coarse and lacked the tensile strength required for "warp" (the longitudinal threads in a loom that must withstand high tension). Consequently, the Jenny's output was suitable only for the "weft" (the transverse threads). Despite this limitation, the machine's sheer efficiency posed an immediate and terrifying threat to the livelihoods of thousands of traditional hand-spinners. Fearing total economic ruin and permanent unemployment, a violent mob from Lancashire eventually marched on Hargreaves’ house in 1768 and destroyed his expensive equipment. This unrest forced the inventor to flee for his safety to Nottingham, a burgeoning center for the hosiery industry, where he partnered with Thomas James to establish a small, more secure spinning mill.
The legal history of the Spinning Jenny is as turbulent as its social reception. Hargreaves finally applied for a patent in 1770 to protect his intellectual property, but because he had sold several machines years prior to the application, his legal standing was weak. Others copied his designs without paying royalties, citing the fact that the technology was already in the public domain. Despite these legal setbacks and the lack of personal wealth accrued by its inventor, the technology of the Spinning Jenny spread like wildfire throughout the industrial heartlands of Britain. By the time of Hargreaves’ death in 1778, it is estimated that over 20,000 jennies were in use across Britain. The invention is now historically credited with providing the critical momentum for moving the textile industry out of the private home and into the centralized factory, a massive structural shift that transformed England from an agrarian society into the world's first industrial powerhouse.
Ultimately, a lingering linguistic mystery remains regarding the machine's famous name. While the sentimental legend of the "Daughter Jenny" persists in many modern history textbooks, parish records from the time show that James Hargreaves actually had no daughter by that specific name; his wife was named Elizabeth, and none of his children carried the name Jenny. The word "jenny" was actually a common 18th-century slang term for an engine or machine. It is highly likely that the name was simply a diminutive of the word "engine" (ginny). Nevertheless, whether named after a mythical child or a simple piece of local slang, the Spinning Jenny remains an undisputed cornerstone of the technological revolution that dismantled ancient traditions and shaped the contours of the modern industrial world.
  1. 1

    What was the main production method in Hargreaves’ village when he was young?

  2. 2

    Which members of the family were traditionally responsible for spinning in small towns?

  3. 3

    Some evidence suggests Hargreaves improved a design originally created by which individual?

  4. 4

    What was the primary material used to build the original Spinning Jenny?

  5. 5

    To which city did Hargreaves move after his house was attacked by angry competitors?

  6. 6

    According to 18th-century usage, the word "jenny" was a slang reference to what?

  7. 7

    James Hargreaves was a highly educated man who excelled in reading and writing.

    • TRUE. TRUE
    • FALSE. FALSE
    • NOT GIVEN. NOT GIVEN
  8. 8

    The Spinning Jenny was initially capable of producing high-quality thread for the warp of a cloth.

  9. 9

    Hargreaves was successful in collecting large sums of money from everyone who used his design.

  10. 10

    At the time of his death, the use of the Spinning Jenny was still limited to a few villages in Lancashire.

  11. 11

    Label the diagram below. (11: The primary power source, turned by the operator)

  12. 12

    Label the diagram below. (12: The row of vertical components holding the threads)

  13. 13

    Label the diagram below. (13: Used to transmit power from the wheel to the spinning area)

Reading Passage 2: A New Look for Talbot Park

Talbot Park, a housing project in Auckland, New Zealand, was once described as a ghetto, troubled by high rates of crime and vandalism. However, it has just been rebuilt at a cost of $48 million and the project reflects some new thinking about urban design.
A The new Talbot Park is immediately eye-catching because the buildings look quite different to other state-housing projects in Auckland. ‘There is no reason why state housing should look cheap in my view,’ says architect Neil Cotton, one of the design team. ‘In fact, I was anticipating a backlash by those who objected to the quality of what is provided with government money.’ The tidy brick and wood apartments and townhouses would not look out of place in some of the city’s most affluent suburbs, and this is a central theme of the Talbot Park philosophy.
B Talbot Park is a triangle of government-owned land, which in the early 1960s was developed for state housing built around a linear garden that ran through the middle. Initially, there was a strong sense of neighbourliness. Former residents recall how the garden played a big part in their childhoods — a place where kids came together to play softball, cricket and bullrush. ‘We had respect for our neighbours and addressed them by title — Mr and Mrs so-and-so,’ recalls Georgie Thompson, who grew up there in the 1960s.
C Exactly what went wrong with Talbot Park is unclear. The community began to change in the late 1970s as more immigrants moved in. The new arrivals didn’t always integrate with the community and a ‘them and us’ mentality developed. In the process, standards dropped and the neighbourhood began to look shabbier. The buildings themselves were also deteriorating and becoming run-down, petty crime was on the rise and the garden was considered unsafe. In 2002, Housing New Zealand decided the properties needed upgrading. The question was, how to avoid repeating the mistakes of the past?
D One controversial aspect of the upgrade is that the new development has actually made the density of housing in Talbot Park greater, putting 52 more homes on the same site. Doing this required a fresh approach that can be summed up as ‘mix and match’. The first priority was to mix up the housing by employing a variety of plans by different architects: some of the accommodation is free-standing houses, some semi-detached, some low-level, multi-apartment blocks. By doing this, the development avoids the uniform appearance of so many state-housing projects, which residents complain denies them any sense of individual identity. The next goal was to prevent overspending by using efficient designs to maximise the sense of space from minimum room sizes. There was also a no-frills, industrial approach to kitchens, bathrooms and flooring, to optimise durability and ensure the project did not go over budget. Architecturally, the buildings are relatively conservative: fairly plain houses standing in a small garden. There’s a slight reflection of the traditional Pacific beach house (a fale) but it’s not over-played. ‘It seems to us that low-cost housing is about getting as much amenity as you can for the money,’ says architect Michael Thompson. Another key aspect of the ‘mix and match’ approach is openness: one that not only lets residents see what is going on but also lets them know they are seen. The plan ensures there are no cul-de-sacs or properties hidden from view, that the gardens are not enclosed by trees and that most boundary fences are see-through — a community contained but without walls.
E The population today is c Māori, 15% Asian, 10% New Zealand European and the rest composed of immigrants from Russia, Ukraine and Iran. ‘It was important that the buildings were sufficiently flexible to cater for the needs of people from a wide variety of cultural backgrounds,’ explains designer James Lundy.
F Despite the quality of the buildings, however, there should be no doubt that Talbot Park and its surrounding suburb of Tāmaki are low socio-economic areas. Of the 5,000 houses there, 55% are state houses, 28% privately owned (compared to about 65% nationally) and 17% private rental. The area has a high density of households with incomes in the $5,000 to $15,000 range and very few with an income over $70,000. That’s in sharp contrast to the more affluent suburbs in Auckland.
G Another important part of the new development is what Housing New Zealand calls ‘intensive tenancy management’. Opponents of the project call it social control. ‘The focus is on frequent inspections and setting clear guidelines and boundaries regarding the sort of behaviour we expect from tenants,’ says Graham Bodman, Housing New Zealand’s regional manager. The result is a code of sometimes strict rules: no loud parties after 10 pm; no washing hung over balcony rails; and a requirement to mow lawns and keep the property tidy. The Tenancy Manager walks the site every day, knows everyone by name and deals with problems quickly. ‘It’s all based on the intensification,’ says project manager Stuart Bracey. ‘We acknowledge that if you are going to ask people to live in these quite tightly-packed communities, you have to actually help them to get to know each other by organising morning teas and street barbecues.’ So far it seems to be working and many involved in the project believe Talbot Park represents the way forward for state housing.
  1. 14

    Paragraph A

    • i. Some of the problems that developed at Talbot Park
    • ii. Where the residents lived while the work was being completed
    • iii. The ethnic makeup of the new Talbot Park
    • iv. The unexpectedly high standard of the housing
    • v. Financial hardship in Talbot Park and a neighbouring community
    • vi. The experiences of one family living at Talbot Park today
    • vii. How to co-ordinate and assist the people who live at Talbot Park
    • viii. Raising the money to pay for the makeover
    • ix. A close community in the original Talbot Park development
    • x. Details of the style of buildings used in the makeover
  2. 15

    Paragraph B

  3. 16

    Paragraph C

  4. 17

    Paragraph D

  5. 18

    Paragraph E

  6. 19

    Paragraph F

  7. 20

    Paragraph G

  8. 21

    James Lundy

    • A. Good tenant management involves supervision and regulation.
    • B. State housing must be built at minimum expense to the public.
    • C. Organising social events helps tenants to live close together.
    • D. Mixed-race communities require adaptable and responsive designs.
    • E. Complaints were expected about the high standard of the development.
    • F. Too many rules and regulations will cause resentment from tenants.
  9. 22

    Graham Bodman

  10. 23

    Stuart Bracey

  11. 24

    One aspect of the Talbot Park project that some critics are concerned about is that the higher _____ of accommodation would lead to the old social problems returning.

  12. 25

    To prevent this, a team of various _____ worked on the project to ensure the buildings were not uniform.

  13. 26

    Further, they created pleasant, functional interiors that could still be built within their _____.

Reading Passage 3: The Rise of Big Data

Big Data marks one of the most remarkable intellectual and technological shifts of the modern era. It does not simply refer to an enormous quantity of information, but rather to a completely new way of thinking about knowledge itself. Unlike the Internet, which connects people and enables communication, Big Data connects data to other data. It transforms scattered fragments of digital information into meaningful patterns, predictions, and insights. Today, nearly every human activity leaves a digital trace: text messages, online purchases, GPS movements, photos, voice commands, and even biometric signals. All of these pieces of information are stored, analyzed, and often combined with other data sources to create a detailed and dynamic picture of the world. Through this process, aspects of life that were once invisible, such as emotions, preferences, or social relationships, have become "datafied," meaning that they can now be measured and studied quantitatively.
This transformation has profound implications for how we understand society. In the past, researchers relied on small samples, surveys, and questionnaires to draw conclusions about human behavior. These methods were slow, expensive, and often inaccurate. With Big Data, it is possible to analyze entire populations in real time. For example, Google can track the spread of influenza by monitoring search terms related to flu symptoms, providing results that are faster and sometimes more accurate than those collected by public health agencies. Similarly, credit card companies can detect fraud within seconds by comparing a transaction against millions of others to identify patterns that deviate from the norm. In the realm of urban planning, data from mobile phones and GPS devices can reveal how people move through cities, helping planners design more efficient transport systems.
However, the rise of Big Data also raises significant ethical and philosophical questions. One of the most pressing concerns is privacy. In a world where every action is recorded and stored, the concept of personal privacy becomes increasingly difficult to maintain. Data that seems anonymous can often be re-identified when combined with other datasets. Researchers have demonstrated that it is possible to identify individuals from anonymized data using just a few data points, such as their age, gender, and zip code. This has led to fears of surveillance, manipulation, and discrimination. Companies and governments now possess more information about individuals than at any other time in history, and the potential for misuse is enormous.
Another concern is the issue of bias. Big Data is often assumed to be objective because it is based on numbers rather than human judgment. However, the data itself is shaped by human choices: what to collect, how to categorize it, and which questions to ask. If these choices reflect existing prejudices, the resulting analysis will simply reproduce those prejudices at a larger scale. For example, predictive policing algorithms that analyze crime data may reinforce racial profiling if the original data reflects biased policing practices. Similarly, hiring algorithms trained on historical data may discriminate against women or minorities if past hiring decisions were biased. The idea that data speaks for itself is a myth; data always speaks through the lens of those who collect and interpret it.
The rise of Big Data also challenges traditional notions of causality. For centuries, science has sought to understand the world by identifying cause-and-effect relationships. Big Data, by contrast, often focuses on correlation. It can tell us that two things are related, but not why. This shift from "why" to "what" has practical benefits. Businesses can use correlations to predict consumer behavior without understanding the underlying reasons. However, it also has limitations. Correlations can be spurious, leading to false conclusions. Without an understanding of causation, interventions based on correlations may fail or even backfire. The challenge for the future is to combine the power of Big Data with the rigor of traditional scientific methods.
Despite these challenges, the potential benefits of Big Data are immense. In medicine, researchers are using data from electronic health records, genetic sequencing, and wearable devices to develop personalized treatments tailored to individual patients. In education, data from online learning platforms can help identify which teaching methods are most effective for different types of students. In environmental science, satellite data and sensor networks are improving our ability to monitor deforestation, track wildlife populations, and predict natural disasters. The list of applications grows longer every day.
Ultimately, the rise of Big Data represents a fundamental shift in how we understand and interact with the world. It offers unprecedented opportunities to solve complex problems, but it also demands that we think carefully about the values we want to preserve. Privacy, fairness, transparency, and accountability are not technical issues; they are social and political ones. As Big Data becomes ever more pervasive, the decisions we make today about how to collect, analyze, and use data will shape the world for generations to come. The future will belong not just to those who can harness the power of data, but to those who can do so wisely and ethically.
  1. 27

    What does the passage suggest is the main difference between the Internet and Big Data?

    • A. The Internet is older and more established than Big Data.
    • B. The Internet connects people, while Big Data connects data to other data.
    • C. The Internet is used for communication, while Big Data is used for storage.
    • D. The Internet is global, while Big Data is limited to specific applications.
  2. 28

    According to the passage, what makes it possible to track the spread of influenza using Google?

    • A. Surveys collected by public health agencies
    • B. Monitoring search terms related to flu symptoms
    • C. Analyzing GPS movements of infected individuals
    • D. Combining data from credit card transactions
  3. 29

    What concern about privacy is raised in the passage?

    • A. Data that seems anonymous can often be re-identified.
    • B. Governments have stopped collecting personal information.
    • C. Companies no longer store data about individuals.
    • D. Privacy laws have made data analysis impossible.
  4. 30

    Why does the passage argue that Big Data is not necessarily objective?

    • A. Because numbers are always unreliable.
    • B. Because human choices shape what data is collected and how it is interpreted.
    • C. Because computers make frequent errors in analysis.
    • D. Because statistical methods are inherently biased.
  5. 31

    What limitation of focusing on correlation rather than causation is mentioned?

    • A. Correlations are always accurate and reliable.
    • B. Correlations can be spurious and lead to false conclusions.
    • C. Correlations are too difficult for computers to calculate.
    • D. Correlations require understanding of underlying reasons.
  6. 32

    Big Data has transformed how we understand society by allowing researchers to analyze entire ________ in real time, rather than relying on small samples.

  7. 33

    Credit card companies use Big Data to detect ________ within seconds by comparing transactions against millions of others.

  8. 34

    In urban planning, data from mobile phones and GPS devices helps planners design more efficient ________ systems.

  9. 35

    However, concerns about privacy arise because data that seems anonymous can often be ________ when combined with other datasets.

  10. 36

    Another issue is that algorithms trained on historical data may reproduce existing ________, such as racial profiling in policing or discrimination in hiring.

  11. 37

    Predictive policing algorithms are always fair and unbiased.

    • YES. YES
    • NO. NO
    • NOT GIVEN. NOT GIVEN
  12. 38

    Understanding causation is less important than identifying correlations.

  13. 39

    In medicine, Big Data is helping to develop treatments tailored to individual patients.

  14. 40

    The decisions made today about data use will have long-term consequences for future generations.

Answer sheet

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Answer key

  1. 1. cottage industries

    The answer is 'cottage industries' because the passage says that when Hargreaves was young, most production in his village was done in people's homes, which is what cottage industries means.

  2. 2. wives and daughters

    'Wives and daughters' is correct because the passage explains that in small towns, spinning was usually done by the women and girls in the family.

  3. 3. Thomas Height

    The answer is 'Thomas Height' because the passage mentions that some evidence suggests Hargreaves improved a design first made by Thomas Height.

  4. 4. wood

    'Wood' is correct because the passage states that the original Spinning Jenny was mainly built from wood.

  5. 5. Nottingham

    Hargreaves moved to 'Nottingham' after his house was attacked, as the passage says he left his home and settled in Nottingham.

  6. 6. engine

    The word 'jenny' was slang for 'engine' in the 18th century, as explained in the passage.

  7. 7. FALSE

    The answer is FALSE because the passage says Hargreaves was not highly educated and had little skill in reading and writing.

  8. 8. FALSE

    FALSE is correct because the passage says the early Spinning Jenny could not make strong enough thread for the warp of cloth.

  9. 9. FALSE

    The answer is FALSE because the passage says Hargreaves did not collect large sums of money from everyone who used his design.

  10. 10. FALSE

    FALSE is correct because the passage says that by the time Hargreaves died, the Spinning Jenny was used in many places, not just a few villages in Lancashire.

  11. 11. large wheel

    The 'large wheel' is the primary power source turned by the operator, as described in the diagram section of the passage.

  12. 12. vertical spindles

    'Vertical spindles' is correct because these are the row of upright parts that hold the threads, as shown in the diagram description.

  13. 13. control cord

    The 'control cord' is used to transmit power from the wheel to the spinning area, as explained in the diagram section.

  14. 14. iv

    The answer is iv because Paragraph A talks about the high standard of the new housing, which was unexpected.

  15. 15. ix

    Paragraph B is about the close community in the original Talbot Park, so the answer is ix.

  16. 16. i

    Paragraph C discusses problems that developed at Talbot Park, so the answer is i.

  17. 17. x

    Paragraph D gives details of the style of buildings used in the makeover, so the answer is x.

  18. 18. iii

    Paragraph E describes the ethnic makeup of the new Talbot Park, so the answer is iii.

  19. 19. v

    Paragraph F talks about financial hardship in Talbot Park and a neighbouring community, so the answer is v.

  20. 20. vii

    Paragraph G explains how to coordinate and assist the people who live at Talbot Park, so the answer is vii.

  21. 21. D

    The answer is D because James Lundy says that mixed-race communities need adaptable and responsive designs.

  22. 22. A

    Graham Bodman believes good tenant management involves supervision and regulation, so the answer is A.

  23. 23. C

    Stuart Bracey says that organising social events helps tenants live close together, so the answer is C.

  24. 24. density

    The answer is 'density' because the passage says some critics worry that higher density of accommodation could bring back old social problems.

  25. 25. architects

    'Architects' is correct because the passage says a team of various architects worked to make sure the buildings were not all the same.

  26. 26. budget

    The answer is 'budget' because the passage says the interiors were made pleasant and functional but still within their budget.

  27. 27. B

    B is correct because the passage says the Internet connects people, but Big Data connects data to other data. Option C is tempting but fails because both the Internet and Big Data are used for communication and storage.

  28. 28. B

    B is correct because the passage says Google tracks the spread of flu by monitoring search terms related to flu symptoms.

  29. 29. A

    A is correct because the passage raises the concern that data which seems anonymous can often be re-identified.

  30. 30. B

    B is correct because the passage says Big Data is not always objective since human choices affect what data is collected and how it is used.

  31. 31. B

    B is correct because the passage warns that focusing on correlation can lead to spurious (false) conclusions.

  32. 32. populations

    The answer is 'populations' because the passage says Big Data lets researchers study entire populations in real time instead of just small samples.

  33. 33. fraud

    'Fraud' is correct because the passage says credit card companies use Big Data to detect fraud within seconds.

  34. 34. transport

    'Transport' is correct because the passage says urban planners use data from phones and GPS to design better transport systems.

  35. 35. re-identified

    The answer is 're-identified' because the passage says data that seems anonymous can often be re-identified when combined with other data.

  36. 36. prejudices

    'Prejudices' is correct because the passage says algorithms trained on old data may repeat existing prejudices, like racial profiling or discrimination.

  37. 37. NO

    NO is correct because the passage says predictive policing algorithms can be unfair and biased.

  38. 38. NO

    NO is correct because the passage says understanding causation is still important, not less important than finding correlations.

  39. 39. YES

    YES is correct because the passage says Big Data is helping medicine develop treatments tailored to individual patients.

  40. 40. YES

    YES is correct because the passage says decisions about data use today will affect future generations.

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