Reading Lab

IELTS Academic Reading Practice Pack 55

A full 60-minute Academic Reading mock with three source-grounded passages, 40 questions, answer key coverage, and doctrine QA traceability.

Question count

Time allowed

60 min

Passages

Academic ReadingFull MockIELTS PracticeQA Approved

Exam panel

You have 60 minutes including answer transfer time. Submit once at the end or let the timer finish the exam automatically.

Time remaining

60:00

0 / 40 answers filled

Write only what the question requires. One extra word can still lose the mark.

After submission, you will see your raw score, estimated Academic Reading band, and the correct answers for every question.

What this reading pack trains

This set is built around algorithm registers and public trust, building with less clinker, working trees on productive farms with 8 official IELTS Reading task types spread across three passages.

IELTS Academic Reading Practice Pack 55 is designed as a full Academic Reading simulation, not just a passage archive. The three texts move from a more accessible opener into denser, more inference-heavy material so the burden rises in the same direction students expect in a real test.

Across this pack, you work through roughly 2,303 words on Working Trees on Productive Farms; Building with Less Clinker; Algorithm Registers and Public Trust. That mix matters because IELTS Reading rewards candidates who can adjust between topic vocabulary, paraphrase recognition, and question-discipline rather than relying on one search habit.

Use this pack when you want one serious timed session, then review every wrong answer against the exact trap type. A strong post-test habit is to check whether the miss came from rushing, weak paraphrase tracking, unstable Not Given logic, or ignoring the word-limit instruction.

Inside the pack

Use the pack as one timed attempt, then return for deliberate review.

Domains

algorithm registers and public trust · building with less clinker · working trees on productive farms

Question types

Matching Features · Matching Headings · Matching Sentence Endings · Multiple Choice · Note Completion · Table Completion · True/False/Not Given · Yes/No/Not Given

If you want more full mocks after this one, go back to the Reading pack library. If you need a broader exam routine, pair one reading session with Listening practice or IELTS Writing repair work.

Passage 1

Working Trees on Productive Farms

An academic IELTS passage on working trees on productive farms, opening with agroforestry is the planned use of trees or shrubs within land that also produces crops or supports animals.

A.A. Agroforestry is the planned use of trees or shrubs within land that also produces crops or supports animals. It is not a single technique, and it is not a recent invention dressed in environmental language. Farmers in many regions have long protected useful trees in fields, planted shelterbelts around farms or allowed animals to graze under scattered woodland. What makes the modern version different is the deliberate design: the tree component is chosen, spaced and managed so that it works with the agricultural enterprise rather than simply occupying unused ground. A shelterbelt, for example, may be valued not for timber but for the steadier microclimate it gives to crops behind it. In other cases, the tree crop is a commercial product, but it still has to be planned around field access and seasonal labour.

B.B. One common design is alley cropping, in which rows of trees are planted with strips of annual or perennial crops between them. The trees can slow wind, reduce water loss from exposed soil and create a more varied habitat for insects and birds. However, the system is not automatically beneficial. If the rows are too close, the tree roots may compete with crops for moisture, and the crowns may cast more shade than the crop can tolerate. Farmers therefore need to match spacing, pruning and species choice to the local climate and to the value of the crop grown between the rows. The design also has to leave turning space for machinery, otherwise a theoretically productive layout can slow ordinary field work.

C.C. A related practice, silvopasture, combines trees with livestock. During hot periods, shade can reduce heat stress in animals, while deep-rooted trees may draw nutrients from layers of soil that grasses cannot reach. The method can also protect young animals from strong wind. Yet silvopasture is more than releasing stock into woodland. Fencing, water points and grazing schedules have to be planned so that animals do not damage young trees or compact soil around roots. For this reason, the system usually needs active management and may still require artificial shelter in exposed places. The balance changes with the age of the trees, since young trees provide little shade while mature trees may alter the pasture beneath them.

D.D. Trees can also be placed beside streams as riparian buffers. These strips of vegetation slow surface runoff, trap sediment and take up some nutrients before they enter waterways. Their value is often indirect: a farmer may not receive an immediate cash return from the buffer itself, but the farm can lose less soil, and downstream water may need less treatment. Buffers can also lower bank erosion by binding soil with roots. They do not replace irrigation or drainage planning, but they can reduce the damage caused when heavy rain carries soil and fertilizer off a field. Their effects are usually measured across seasons, so a buffer that appears unproductive in one month may be protecting the farm's long-term soil capital.

E.E. Successful agroforestry depends on patient design. A farmer must ask whether the soil can support the chosen trees, how much shade the crop can tolerate, where machinery needs to pass and whether markets exist for fruit, nuts, timber or other products. The first years can be unattractive because trees are small but still require protection from weeds, animals and drought. Later benefits may include shelter, extra products, carbon storage and better habitat, but those gains arrive unevenly and are rarely captured by one simple measure.

F.F. The most careful supporters of agroforestry do not present it as a universal solution. On some farms, rented land, narrow margins or existing drainage systems make tree planting difficult. On others, the problem is cultural rather than technical: the farmer may have learned to treat fields and woodland as separate businesses. Agroforestry asks for a different habit of thought. It views trees as part of production, not as decoration or as land taken out of use. Where that view is matched with good design, the result can be a farm that is more diverse, more buffered against weather and less dependent on a single annual output. For this reason, assessment should look at the whole farm plan rather than asking whether each tree is profitable on its own.

True/False/Not Given

Questions 1-6

Do the following statements agree with the information given in Reading Passage 1?

Write TRUE if the statement agrees with the information. Write FALSE if the statement contradicts the information. Write NOT GIVEN if there is no information on this.

1. Agroforestry involves deliberately combining trees or shrubs with crop or animal production.

2. The passage states that agroforestry was first invented in recent temperate farming systems.

3. In alley cropping, trees can compete with crops if the system is badly spaced.

4. Silvopasture always removes the need for artificial shelter.

5. Riparian buffers generate more immediate income than alley-cropping systems.

6. The writer argues that agroforestry should be used on every field.

Note Completion

Questions 7-10

Complete the notes below. Choose ONE WORD ONLY from the passage for each answer.

Design questions in agroforestry

7. - Choose trees that suit the soil and local 7. ________.

8. - Check how much 8. ________ the crop can tolerate.

9. - Leave space for farm 9. ________ to pass.

10. - Consider whether 10. ________ exist for future tree products.

Multiple Choice

Questions 11-13

Choose the correct letter, A, B, C or D.

11. What is the main purpose of the passage?

12. What does the passage suggest about riparian buffers?

13. What point is made about silvopasture?

Passage 2

Building with Less Clinker

An academic IELTS passage on building with less clinker, opening with concrete is often discussed as if its environmental problem begins only when trucks carry it to a building site.

A.A. Concrete is often discussed as if its environmental problem begins only when trucks carry it to a building site. In fact, much of the carbon burden is created earlier, during the manufacture of cement. The key ingredient in ordinary Portland cement is clinker, a hard nodular material made by heating limestone and other minerals to very high temperatures. Fuel is needed to reach those temperatures, but another source of emissions is chemical: when limestone is transformed, carbon dioxide is released from the stone itself. This is why simply changing the fuel cannot remove the sector's full climate impact. A kiln powered by cleaner energy can still release process carbon if it continues to make the same amount of clinker from limestone. This distinction explains why cement is often described as hard to decarbonise: the problem is embedded in both the heat system and the raw material itself.

B.B. One near-term route is to reduce the share of clinker in cement. Producers can blend clinker with supplementary cementitious materials, often called SCMs. Some SCMs, such as slag from steel production and fly ash from coal-fired power stations, are by-products of other industrial processes. Others, such as calcined clay and finely ground limestone, are obtained or processed more directly for cement use. These materials do not behave identically. Some react with water and calcium compounds over time, while others mainly improve packing density or workability. A blend that works well in one climate, supply chain or construction method may be unsuitable elsewhere, so substitution is a technical decision rather than a simple act of adding waste to cement.

C.C. The main barrier is not only chemistry. Construction is a risk-averse industry because failures can be dangerous and expensive. Engineers, insurers and building authorities need confidence that a cement mix will perform over decades, not just in a laboratory sample. For that reason, many specialists argue for performance-based standards. Instead of approving a cement because it follows an old recipe, standards can test whether the final material reaches required strength, durability and setting behaviour. This approach can open space for lower-clinker mixes while still protecting safety. It also prevents regulation from freezing a single historical formula at the moment when material science is changing.

D.D. Supply is another complication. Fly ash and slag have been useful because they are already produced in large quantities, but their availability depends on coal power and steelmaking routes that are themselves changing. A country closing coal plants may reduce the future supply of fly ash. Calcined clay is often described as more widely available, yet not every clay has the right chemistry, and calcination still requires controlled heat. Transport also matters: a promising material can lose some advantage if it must be moved a long distance before it reaches a batching plant. Regional planning is therefore important, because the lowest-carbon option on paper may not be the lowest-carbon option for a specific project.

E.E. Lower-carbon cement also depends on demand. A producer may hesitate to invest in new equipment or certification if builders continue to buy only the cheapest familiar mix. Public procurement can alter that calculation because governments purchase large volumes of concrete for roads, schools, hospitals and flood defences. When tenders reward verified lower-carbon products, suppliers receive a clearer signal that innovation has a market. Private developers can add to this effect when they ask for embodied-carbon data rather than only asking for the lowest initial price. The request must be credible, however; vague green preference is weaker than a tender that specifies verification and rewards proven reductions. Designers can also reduce demand by avoiding over-specification, since using a smaller volume of appropriate concrete may save more carbon than changing the binder alone.

F.F. Clinker substitution is therefore important but incomplete. Some emissions remain even in efficient plants, and other strategies may be needed, including better structural design, reuse of materials, improved energy systems and, in some cases, carbon capture. The most practical lesson is that cement decarbonisation is not a single invention waiting to be scaled. It is a chain of changes: raw materials, standards, testing, procurement, design and verification. If one link is weak, a technically promising cement can remain stuck outside ordinary construction practice. The challenge is institutional as much as chemical, because buildings are approved through shared rules, professional habits and liability systems. For that reason, progress tends to come through coordinated adjustments rather than a sudden replacement of one cement with another.

Matching Headings

Questions 14-19

Reading Passage 2 has six paragraphs, A-F. Choose the correct heading for each paragraph from the list of headings below.

Why buyers can shape the market

A carbon source built into the material

iii

Why technical proof still matters

Uneven availability of replacement materials

A partial solution rather than a complete answer

Ancient origins of cement use

vii

Replacing clinker with other ingredients

viii

How concrete buildings are demolished

14. Paragraph A

15. Paragraph B

16. Paragraph C

17. Paragraph D

18. Paragraph E

19. Paragraph F

Table Completion

Questions 20-23

Complete the table below. Choose ONE WORD ONLY from the passage for each answer.

Aspect of lower-clinker cement

Detail from the passage

Fly ash and slag

20. Often come from other 20. ________ processes.

21. Requires suitable 21. ________ and controlled heat.

22. Should test material 22. ________ instead of only following an old recipe.

23. Can create clearer 23. ________ for verified lower-carbon products.

Matching Sentence Endings

Questions 24-26

Complete each sentence with the correct ending, A-F, below.

24. Lowering clinker content can reduce emissions because

25. Performance-based standards are useful because

26. Procurement policies can help because

A. they remove the need to check durability.
B. they prove that old cement should never be used.
C. clinker is responsible for process emissions as well as energy use.
D. they allow different mixes to be judged by strength and durability.
E. they give producers a clearer market for verified low-carbon concrete.
F. they make all supplementary materials locally available.
A. Public agencies increasingly use algorithmic tools to sort applications, flag possible fraud, estimate risk or decide which case should be reviewed first. These systems may be built with machine-learning methods, but many are less dramatic: scoring rules, automated matching and statistical models also shape decisions. Because their effects can be serious, governments have begun to publish algorithm registers, databases that list where such tools are used. A register can make a hidden administrative practice easier to discover, but discovery is only the beginning of accountability. The public may learn that a tool exists without learning enough to judge whether it is proportionate, accurate or open to correction.
B. A useful entry in a register does more than name a tool. It explains the public service involved, the purpose of the system, the type of data considered, who is affected and whether the tool recommends action or makes a decision. It should also describe human oversight, risk controls and routes for challenge. Without these elements, a register may create the appearance of openness while leaving citizens unable to understand how a system could matter to them. The writer's central point is therefore cautious: transparency is valuable only when it is meaningful to those outside the agency. A form that satisfies internal reporting can still fail ordinary readers if it hides the practical decision behind administrative language.
C. Meaningful transparency is not the same as publishing every technical detail. A security official may reasonably object to releasing exact detection rules if that would help organised fraud. Privacy law may also prevent agencies from revealing sensitive personal data or the full contents of training records. Even model code can be misleading when separated from the data, organisational setting and staff instructions that give it force. The harder question is not whether some limits are justified, but whether the remaining information is clear enough for public scrutiny. This requires judgement, because secrecy can be used both responsibly and conveniently.
D. Quality is a persistent weakness. Some records are written in vague language, using phrases such as 'data-driven improvement' or 'risk prioritisation' without explaining the decision point. Others are not updated when a pilot becomes routine or when a model is withdrawn. A data scientist would ask whether the record includes the provenance of data, known gaps, error rates and tests for unequal performance across groups. These details do not make the system fair by themselves, but they help outsiders see where fairness claims should be examined. They also show whether the agency has treated performance as a continuing obligation rather than a one-time launch requirement.
E. For a civil-rights lawyer, the essential issue is contestability. A person affected by an automated recommendation may not need to read source code, but they need to know that a tool was used, what broad information it relied on and how to challenge an outcome. Human oversight is not automatically protective. If staff are under pressure to process cases quickly, a recommendation can become a rubber stamp even when the official policy says that people remain in control. A register should therefore distinguish between formal oversight and practical oversight. It should also say whether people are told about algorithmic involvement at the moment when they can still respond.
F. Accountability must also begin before purchase. A procurement manager should ask potential suppliers for evidence about performance, bias testing, maintenance duties and the right to audit. Contract terms matter because public agencies can otherwise become dependent on vendors who claim that crucial information is commercially confidential. The existence of a proprietary product does not relieve the agency of responsibility. If a government body cannot explain enough about a tool to justify its public use, the problem belongs to the government body as much as to the vendor. Public legitimacy cannot be outsourced with the software contract.
G. Registers sit alongside law rather than replacing it. Recent regulatory frameworks for high-risk artificial intelligence emphasise risk management, documentation, traceability, human oversight and data quality. A register can support these duties by giving the public a map of where systems are operating, but it cannot perform an audit, test a dataset or compensate someone harmed by an unlawful decision. In this sense, a register is a doorway into governance, not the whole building. Treating publication as the final step would turn transparency into a box-ticking exercise. A public list can point investigators in the right direction, but it cannot decide whether the underlying use is lawful, necessary or fair.
H. The best algorithm registers are maintained as civic infrastructure. They use plain language, record changes over time and connect the entry to complaints, impact assessments or independent reviews. They also admit uncertainty, because a model's behaviour can shift when data, policy or staffing changes. Registers will not remove every risk from automated administration. They can, however, make it harder for agencies to hide behind technical complexity and easier for the public to ask precise questions about tools used in their name. That is a modest aim, but in administrative systems that depend on routine decisions, modest visibility can still matter.

Passage 3

Algorithm Registers and Public Trust

An academic IELTS passage on algorithm registers and public trust, opening with public agencies increasingly use algorithmic tools to sort applications, flag possible fraud, estimate risk or decide which case should be rev....

A.A. Public agencies increasingly use algorithmic tools to sort applications, flag possible fraud, estimate risk or decide which case should be reviewed first. These systems may be built with machine-learning methods, but many are less dramatic: scoring rules, automated matching and statistical models also shape decisions. Because their effects can be serious, governments have begun to publish algorithm registers, databases that list where such tools are used. A register can make a hidden administrative practice easier to discover, but discovery is only the beginning of accountability. The public may learn that a tool exists without learning enough to judge whether it is proportionate, accurate or open to correction.

B.B. A useful entry in a register does more than name a tool. It explains the public service involved, the purpose of the system, the type of data considered, who is affected and whether the tool recommends action or makes a decision. It should also describe human oversight, risk controls and routes for challenge. Without these elements, a register may create the appearance of openness while leaving citizens unable to understand how a system could matter to them. The writer's central point is therefore cautious: transparency is valuable only when it is meaningful to those outside the agency. A form that satisfies internal reporting can still fail ordinary readers if it hides the practical decision behind administrative language.

C.C. Meaningful transparency is not the same as publishing every technical detail. A security official may reasonably object to releasing exact detection rules if that would help organised fraud. Privacy law may also prevent agencies from revealing sensitive personal data or the full contents of training records. Even model code can be misleading when separated from the data, organisational setting and staff instructions that give it force. The harder question is not whether some limits are justified, but whether the remaining information is clear enough for public scrutiny. This requires judgement, because secrecy can be used both responsibly and conveniently.

D.D. Quality is a persistent weakness. Some records are written in vague language, using phrases such as 'data-driven improvement' or 'risk prioritisation' without explaining the decision point. Others are not updated when a pilot becomes routine or when a model is withdrawn. A data scientist would ask whether the record includes the provenance of data, known gaps, error rates and tests for unequal performance across groups. These details do not make the system fair by themselves, but they help outsiders see where fairness claims should be examined. They also show whether the agency has treated performance as a continuing obligation rather than a one-time launch requirement.

E.E. For a civil-rights lawyer, the essential issue is contestability. A person affected by an automated recommendation may not need to read source code, but they need to know that a tool was used, what broad information it relied on and how to challenge an outcome. Human oversight is not automatically protective. If staff are under pressure to process cases quickly, a recommendation can become a rubber stamp even when the official policy says that people remain in control. A register should therefore distinguish between formal oversight and practical oversight. It should also say whether people are told about algorithmic involvement at the moment when they can still respond.

F.F. Accountability must also begin before purchase. A procurement manager should ask potential suppliers for evidence about performance, bias testing, maintenance duties and the right to audit. Contract terms matter because public agencies can otherwise become dependent on vendors who claim that crucial information is commercially confidential. The existence of a proprietary product does not relieve the agency of responsibility. If a government body cannot explain enough about a tool to justify its public use, the problem belongs to the government body as much as to the vendor. Public legitimacy cannot be outsourced with the software contract.

G.G. Registers sit alongside law rather than replacing it. Recent regulatory frameworks for high-risk artificial intelligence emphasise risk management, documentation, traceability, human oversight and data quality. A register can support these duties by giving the public a map of where systems are operating, but it cannot perform an audit, test a dataset or compensate someone harmed by an unlawful decision. In this sense, a register is a doorway into governance, not the whole building. Treating publication as the final step would turn transparency into a box-ticking exercise. A public list can point investigators in the right direction, but it cannot decide whether the underlying use is lawful, necessary or fair.

H.H. The best algorithm registers are maintained as civic infrastructure. They use plain language, record changes over time and connect the entry to complaints, impact assessments or independent reviews. They also admit uncertainty, because a model's behaviour can shift when data, policy or staffing changes. Registers will not remove every risk from automated administration. They can, however, make it harder for agencies to hide behind technical complexity and easier for the public to ask precise questions about tools used in their name. That is a modest aim, but in administrative systems that depend on routine decisions, modest visibility can still matter.

Yes/No/Not Given

Questions 27-33

Do the following statements agree with the claims of the writer in Reading Passage 3?

Write YES if the statement agrees with the claims of the writer. Write NO if the statement contradicts the claims of the writer. Write NOT GIVEN if it is impossible to say what the writer thinks about this.

27. Publishing an algorithm register automatically makes an algorithm fair.

28. Registers can make public-sector algorithm use easier to discover.

29. Every technical detail of an algorithmic tool should be released publicly.

30. Most members of the public who read algorithm registers are professional software engineers.

31. Human oversight may be weak if staff simply follow machine recommendations.

32. Vendor secrecy should prevent public agencies from explaining automated tools.

33. Legal rules are unnecessary once a public register exists.

Matching Features

Questions 34-37

Look at the following concerns and the list of roles below. Match each concern with the correct role, A-D.

civil-rights lawyer

procurement manager

data scientist

security official

34. People need a route to challenge an outcome affected by an automated tool.

35. Records should show data provenance and tests for unequal performance.

36. Contract terms should require evidence, maintenance duties and audit rights before purchase.

37. Some exact detection rules may need to be withheld to prevent gaming.

Multiple Choice

Questions 38-40

Choose the correct letter, A, B, C or D.

38. What is the writer's main argument about algorithm registers?

39. Why can long technical descriptions still fail as transparency?

40. Which phrase best describes the writer's attitude towards algorithm registers?