Nông nghiệp thông minh đang trở thành một xu hướng toàn cầu, đặc biệt trong bối cảnh phát triển nông thôn và đảm bảo an ninh lương thực. Chủ đề “The Rise Of Smart Agriculture In Rural Development” xuất hiện thường xuyên trong các kỳ thi IELTS Reading gần đây, phản ánh tầm quan trọng của công nghệ trong việc chuyển đổi ngành nông nghiệp truyền thống.
Bài viết này cung cấp một đề thi IELTS Reading hoàn chỉnh với 3 passages từ dễ đến khó, giúp bạn:
- Làm quen với đề thi thật gồm 40 câu hỏi đa dạng
- Luyện tập các dạng câu hỏi phổ biến: Multiple Choice, True/False/Not Given, Matching, Summary Completion
- Nắm vững từ vựng chuyên ngành về nông nghiệp công nghệ cao
- Hiểu rõ chiến lược làm bài qua đáp án chi tiết
- Nâng cao kỹ năng đọc hiểu từ band 5.0 đến 9.0
Đề thi này phù hợp cho học viên đang nhắm đến band điểm từ 5.0 trở lên, với độ khó tăng dần và giải thích chi tiết giúp bạn tự đánh giá và cải thiện kỹ năng.
Hướng Dẫn Làm Bài IELTS Reading
Tổng Quan Về IELTS Reading Test
IELTS Reading Test kéo dài 60 phút với 3 passages và tổng cộng 40 câu hỏi. Mỗi câu trả lời đúng được tính 1 điểm, không bị trừ điểm khi sai.
Phân bổ thời gian khuyến nghị:
- Passage 1 (Easy): 15-17 phút – Nội dung thực tế, từ vựng phổ thông
- Passage 2 (Medium): 18-20 phút – Yêu cầu hiểu sâu hơn, nhiều paraphrase
- Passage 3 (Hard): 23-25 phút – Học thuật, trừu tượng, cần suy luận
Lưu ý dành 2-3 phút cuối để chép đáp án vào answer sheet.
Các Dạng Câu Hỏi Trong Đề Này
Đề thi mẫu này bao gồm 7 dạng câu hỏi phổ biến:
- Multiple Choice – Chọn đáp án đúng từ các lựa chọn A, B, C, D
- True/False/Not Given – Xác định thông tin đúng, sai hoặc không được đề cập
- Matching Information – Ghép thông tin với đoạn văn phù hợp
- Sentence Completion – Hoàn thành câu với từ trong bài
- Summary Completion – Điền từ vào tóm tắt
- Matching Features – Ghép đặc điểm với các yếu tố được liệt kê
- Short-answer Questions – Trả lời ngắn gọn dựa trên thông tin bài đọc
IELTS Reading Practice Test
PASSAGE 1 – Smart Farming Technologies Transform Rural Communities
Độ khó: Easy (Band 5.0-6.5)
Thời gian đề xuất: 15-17 phút
The integration of technology into agriculture has revolutionised farming practices across the world, particularly in rural areas where traditional methods have dominated for centuries. Smart agriculture, also known as precision farming, uses modern technologies such as sensors, drones, and data analytics to optimise crop production and resource management. This transformation is not merely about increasing yields; it represents a fundamental shift in how rural communities approach food production and economic development.
In many developing countries, smallholder farmers face numerous challenges including unpredictable weather patterns, limited access to markets, and insufficient knowledge about modern farming techniques. Smart agriculture addresses these issues by providing farmers with real-time data about soil conditions, weather forecasts, and crop health. For instance, soil moisture sensors can tell farmers exactly when to irrigate their fields, preventing both water waste and crop damage from over-watering. This technology is particularly valuable in regions where water scarcity is a growing concern.
The adoption of smart farming tools has proven especially beneficial in rural India, where more than 60% of the population depends on agriculture for their livelihood. The Indian government has launched several initiatives to promote digital agriculture, providing farmers with mobile applications that deliver customised advice on planting schedules, pest management, and market prices. These apps use artificial intelligence to analyse local conditions and recommend the best practices for individual farms. As a result, many farmers have reported yield increases of 20-30% while reducing their input costs.
Drone technology has emerged as another game-changing innovation in rural farming. Equipped with high-resolution cameras and sensors, drones can survey large areas of farmland quickly and efficiently, identifying problems such as pest infestations, nutrient deficiencies, or irrigation issues that might not be visible from ground level. In Kenya, a project using drones to monitor crop health has helped farmers detect problems early, enabling them to take corrective action before significant damage occurs. This proactive approach has reduced crop losses by up to 40% in participating farms.
Beyond individual farm management, smart agriculture is creating new economic opportunities in rural areas. The demand for technology maintenance, data analysis, and technical support has generated employment for young people who might otherwise migrate to cities seeking work. In Vietnam, rural technology hubs have been established to train farmers and their children in using and maintaining smart farming equipment. These centres also serve as community gathering points where farmers can share experiences and learn from each other’s successes and challenges.
However, the transition to smart agriculture is not without obstacles. The initial investment required for technology can be prohibitive for poor farmers, and many rural areas lack the infrastructure necessary to support advanced systems, such as reliable internet connectivity and electricity. Additionally, there is often a knowledge gap – older farmers may be reluctant to adopt new methods they don’t fully understand, preferring to stick with traditional practices passed down through generations.
To overcome these barriers, governments and non-governmental organisations are developing innovative financing models and training programmes. In Brazil, a cooperative system allows small farmers to pool their resources to purchase expensive equipment like GPS-guided tractors and share them among members. Microfinance institutions have also begun offering loans specifically designed for agricultural technology purchases, with repayment schedules aligned with harvest seasons. These initiatives are making smart agriculture accessible to a broader range of farmers.
The environmental benefits of smart agriculture are equally impressive. Precision application of fertilisers and pesticides means chemicals are used only where needed and in the right amounts, reducing pollution and protecting local ecosystems. In the Netherlands, smart farming practices have helped reduce nitrogen runoff into waterways by 35%, while maintaining high productivity levels. This demonstrates that sustainable intensification – producing more food on the same land while reducing environmental impact – is achievable through technology.
Looking ahead, the continued development of smart agriculture will likely play a crucial role in achieving global food security. With the world’s population expected to reach nearly 10 billion by 2050, food production must increase significantly while dealing with challenges like climate change and limited arable land. Smart agriculture offers a pathway to meet these demands sustainably, ensuring that rural communities can thrive economically while feeding the world.
Ứng dụng nông nghiệp thông minh giúp nông dân Việt Nam nâng cao năng suất cây trồng bền vững
Questions 1-5: Multiple Choice
Choose the correct letter, A, B, C, or D.
-
According to the passage, smart agriculture is mainly concerned with:
A. Replacing traditional farmers with machines
B. Optimising crop production through technology
C. Increasing the price of agricultural products
D. Reducing the rural population -
Soil moisture sensors help farmers by:
A. Predicting future weather patterns
B. Increasing crop diversity
C. Determining the optimal time for irrigation
D. Analysing market prices -
In rural India, mobile applications for farmers provide:
A. Free farming equipment
B. Loans for purchasing land
C. Customised agricultural advice
D. Transportation to markets -
The use of drones in Kenyan agriculture has resulted in:
A. A 40% reduction in crop losses
B. Complete elimination of pests
C. Doubling of farm sizes
D. Replacement of all manual labour -
According to the passage, what is one major obstacle to adopting smart agriculture?
A. Farmers preferring city life
B. Excessive government regulation
C. High initial technology costs
D. Lack of available land
Questions 6-9: True/False/Not Given
Do the following statements agree with the information given in the passage?
Write:
- TRUE if the statement agrees with the information
- FALSE if the statement contradicts the information
- NOT GIVEN if there is no information on this
- More than half of India’s population relies on agriculture for income.
- Drone technology can only be used in large-scale commercial farms.
- Young people in rural Vietnam are receiving training in smart farming technology.
- Smart agriculture has completely solved the problem of food security in developing countries.
Questions 10-13: Sentence Completion
Complete the sentences below.
Choose NO MORE THAN TWO WORDS from the passage for each answer.
- In the Netherlands, smart farming has reduced __ into waterways by 35%.
- The world’s population is expected to reach nearly __ by 2050.
- In Brazil, small farmers use a __ that allows them to share expensive equipment.
- Precision farming reduces pollution by ensuring chemicals are used only in the __ amounts.
PASSAGE 2 – The Socio-Economic Impact of Agricultural Innovation
Độ khó: Medium (Band 6.0-7.5)
Thời gian đề xuất: 18-20 phút
The advent of smart agriculture has catalysed a profound socio-economic transformation in rural regions worldwide, reshaping not only farming practices but also the very fabric of rural society. While the technological dimensions of this revolution are well-documented, the broader implications for community dynamics, gender relations, and economic stratification deserve closer examination. The interplay between technological innovation and social change presents both opportunities and challenges that policymakers must navigate carefully to ensure equitable development.
Historically, rural communities have been characterised by strong social cohesion, with knowledge transmission occurring primarily through intergenerational teaching and community networks. The introduction of digital platforms and algorithmic decision-making tools has disrupted these traditional patterns in complex ways. On one hand, younger, tech-savvy farmers can now access information previously available only to agricultural extension workers or wealthy landowners. This democratisation of knowledge has the potential to reduce historical disparities in agricultural productivity. However, it simultaneously risks creating a new digital divide, where those unable to access or utilise technology fall further behind their connected counterparts.
Research conducted across sub-Saharan Africa reveals nuanced patterns in technology adoption. A comprehensive study in Ghana found that farmers with secondary education were three times more likely to adopt smart farming tools compared to those with only primary schooling. Furthermore, the study identified significant gender disparities: female farmers faced additional barriers including limited land tenure security, restricted access to credit, and cultural norms that discouraged their participation in technology training programmes. These findings underscore the importance of addressing underlying social inequalities when promoting agricultural innovation.
The economic ramifications of smart agriculture extend far beyond farm profitability. In regions where technology adoption has reached critical mass, entirely new value chains have emerged. Agribusiness companies specialising in data analytics, equipment leasing, and technical consultancy have established operations in areas that previously offered limited employment diversity. In rural Brazil, the smart agriculture sector now employs over 50,000 people in roles ranging from drone operators to data scientists, providing lucrative alternatives to traditional farming or urban migration. Interestingly, this sector has attracted reverse migration, with young professionals returning to rural areas where they can apply their technical skills while maintaining connections to their ancestral communities.
The transformation has also influenced patterns of land ownership and farm consolidation. Paradoxically, while smart technology could theoretically benefit small-scale farmers disproportionately by helping them overcome resource constraints, evidence suggests that larger operations have been primary beneficiaries. The economies of scale inherent in technology investment create competitive advantages for bigger farms, potentially accelerating the trend toward agricultural consolidation. In the United States Midwest, the average farm size has increased by 35% since the widespread adoption of precision agriculture technologies, raising concerns about the long-term viability of family farming and rural community structures built around smaller operations.
Tương tự như tác động của công nghệ xanh đối với nông nghiệp truyền thống, smart agriculture also raises important questions about environmental sustainability and agricultural resilience. While proponents emphasise reduced chemical inputs and water conservation, critics point to potential vulnerabilities created by increased dependence on complex technological systems. The concentration of agricultural data in the hands of a few large corporations has sparked debates about data ownership, privacy, and the risk of monopolistic practices. Some observers worry that farmers could become overly reliant on proprietary systems, reducing their autonomy and traditional ecological knowledge.
The psychological dimensions of this transition should not be overlooked. For farmers whose identity is deeply intertwined with traditional practices and hard-earned experiential knowledge, the shift toward algorithm-driven decision-making can be disconcerting. Qualitative research in Japan’s rural prefectures has documented feelings of disconnection among older farmers who feel their lifetime of accumulated wisdom is being devalued in favour of sensor readings and computer models. Successful smart agriculture initiatives have recognised this dynamic, designing systems that augment rather than replace human judgment, thereby preserving farmers’ sense of agency and expertise.
Một ví dụ chi tiết về sự phát triển của nông nghiệp thông minh trong sản xuất lương thực is found in the Netherlands, where agricultural innovation has been deliberately coupled with strong cooperative structures and inclusive governance. Dutch farmers participate actively in research and development, ensuring technologies are tailored to practical needs and local conditions. This participatory approach has fostered widespread acceptance and effective implementation, with over 80% of Dutch farms now utilising some form of smart technology. The model demonstrates that technological advancement and social cohesion need not be mutually exclusive.
Moving forward, realising the full potential of smart agriculture while mitigating its risks requires holistic policies that address technological, economic, and social factors simultaneously. Investment in rural telecommunications infrastructure must be paralleled by comprehensive training programmes that reach marginalised populations. Financial mechanisms should be designed to support small-scale farmers without creating unsustainable debt burdens. Perhaps most importantly, rural communities themselves must be empowered to shape how technologies are deployed and adapted to their specific contexts, ensuring that innovation serves human flourishing rather than merely technical efficiency.
Questions 14-18: Yes/No/Not Given
Do the following statements agree with the views of the writer in the passage?
Write:
- YES if the statement agrees with the views of the writer
- NO if the statement contradicts the views of the writer
- NOT GIVEN if it is impossible to say what the writer thinks about this
- The introduction of digital platforms has completely destroyed traditional knowledge transmission in rural communities.
- Technology adoption in agriculture has the potential to reduce historical productivity disparities.
- Female farmers in Ghana face no barriers when accessing smart farming technology.
- Large farms have gained more advantages from smart agriculture than small farms.
- All farmers should immediately abandon traditional farming methods.
Questions 19-23: Matching Information
Which paragraph contains the following information?
Write the correct letter, A-I.
NB: You may use any letter more than once.
- An example of a country where cooperative structures supported technology adoption
- Statistical evidence about the relationship between education and technology use
- Information about new employment opportunities created by smart agriculture
- Discussion of psychological effects on traditional farmers
- Concerns about data ownership and farmer independence
Questions 24-26: Summary Completion
Complete the summary below.
Choose NO MORE THAN TWO WORDS from the passage for each answer.
In the United States Midwest, the average farm size has grown by 35% following the 24. __ of precision agriculture. This trend raises concerns about the sustainability of 25. __ and the rural community structures that depend on smaller farming operations. Critics worry that smart agriculture may create 26. __ on complex technological systems, potentially reducing farmer autonomy.
PASSAGE 3 – Theoretical Frameworks and Future Trajectories in Agricultural Modernisation
Độ khó: Hard (Band 7.0-9.0)
Thời gian đề xuất: 23-25 phút
The trajectory of agricultural modernisation through technological integration presents a multifaceted phenomenon that demands examination through diverse theoretical lenses. Contemporary discourse on smart agriculture frequently oscillates between techno-optimist narratives emphasising unprecedented productivity gains and critical perspectives highlighting structural inequalities and ecological risks. A rigorous analytical approach necessitates moving beyond these dichotomous framings to develop nuanced understandings of how socio-technical transitions unfold across heterogeneous rural landscapes, shaped by contingent interactions between technological affordances, institutional arrangements, economic incentives, and cultural predispositions.
The innovation diffusion theory, originally articulated by Everett Rogers, provides a foundational framework for understanding technology adoption patterns in agricultural contexts. However, its application to smart agriculture reveals significant limitations. Rogers’ model presumes relatively linear adoption processes governed primarily by individual decision-making based on perceived relative advantage, compatibility, and complexity. Contemporary smart agricultural systems, conversely, are characterised by network effects and systemic dependencies that fundamentally alter adoption dynamics. The value of precision farming technologies accrues not merely from individual use but through aggregation of data across multiple farms, creating positive externalities that traditional diffusion models struggle to accommodate. Moreover, smart agriculture frequently requires complementary investments in digital infrastructure, institutional capacity, and human capital that exceed the decisional scope of individual farmers, implicating broader governance structures in adoption outcomes.
Alternative theoretical approaches drawn from Science and Technology Studies (STS) offer valuable insights by conceptualising agricultural modernisation as co-production – a process through which technological and social orders are simultaneously constructed and reconfigured. From this perspective, smart agriculture does not simply represent the application of pre-existing technologies to agricultural problems; rather, it involves the active constitution of new understandings of what agriculture is and what it should accomplish. Algorithmic decision support systems, for instance, don’t merely optimise existing farming practices; they redefine farming as a data-driven, quantifiable enterprise, potentially marginalising experiential knowledge and holistic appreciation of agro-ecological contexts. This reconceptualisation has profound implications for agricultural education, policy frameworks, and the very ontology of farming as an occupation and way of life.
The political economy of smart agriculture warrants particular attention, especially regarding questions of value capture and distributional consequences. While productivity enhancements from technological innovation might theoretically benefit all stakeholders along agricultural value chains, empirical evidence suggests highly uneven distributions of gains. Technology providers, data analytics firms, and large-scale agribusinesses have captured disproportionate shares of value, leveraging their control over proprietary platforms and analytical capabilities. The increasing commodification of agricultural data raises fundamental questions about intellectual property regimes and collective resource governance. Farmers generate the underlying data through their daily operations, yet this information is frequently appropriated by technology companies who monetise it through subscription services or by selling aggregated insights to third parties. This asymmetric relationship recapitulates historical patterns of surplus extraction from agricultural producers, albeit through digital rather than physical mechanisms.
Đối với những ai quan tâm đến tác động của biến đổi khí hậu đối với an ninh lương thực toàn cầu, ecological considerations introduce additional complexity to assessments of smart agriculture’s sustainability. Advocates argue that precision application of inputs represents a categorical improvement over indiscriminate practices, reducing both environmental degradation and greenhouse gas emissions. Sceptics counter that this focus on micro-level efficiency obscures macro-level concerns about agricultural intensification and monoculture systems that smart technologies may inadvertently reinforce. The optimisation imperative embedded in many smart farming systems privileges yield maximisation within existing cropping systems rather than encouraging diversification or agroecological approaches that might offer greater resilience to climate variability. Furthermore, the energy requirements of data processing infrastructure and manufacturing of sophisticated sensors and equipment create carbon footprints that partially offset on-farm emissions reductions, though comprehensive life-cycle analyses remain relatively scarce.
The future trajectory of smart agriculture will likely be shaped by several converging trends. Artificial intelligence and machine learning capabilities continue advancing exponentially, promising increasingly sophisticated predictive models and autonomous farming systems. The proliferation of Internet of Things (IoT) devices and declining sensor costs are expanding technological accessibility, though infrastructure disparities between developed and developing regions persist. Regulatory frameworks are gradually evolving to address data governance, though significant jurisdictional variations and enforcement challenges remain. Perhaps most consequentially, growing recognition of the interconnections between agricultural practices, climate change, and public health may catalyse more interventionist policies that mandate or incentivise particular technological approaches.
Interdisciplinary scholarship increasingly emphasises the concept of responsible innovation as a normative framework for steering agricultural technological development toward socially desirable outcomes. This approach advocates for anticipatory governance mechanisms that proactively identify potential adverse consequences, promote inclusive deliberation about innovation priorities, and ensure reflexive adaptation of technological systems based on emerging evidence. Implementing responsible innovation in smart agriculture contexts requires institutional innovations including multi-stakeholder platforms for technology co-design, transparency requirements for algorithmic systems, and mechanisms ensuring equitable benefit distribution. Some scholars propose digital commons models where agricultural data is treated as a collectively managed resource, with farmers retaining control over information flows while enabling mutually beneficial knowledge generation.
The integration of smart agriculture into broader rural development strategies presents both opportunities and imperatives. Technology-focused interventions risk exacerbating existing vulnerabilities if deployed without attention to complementary social investments in education, healthcare, and physical infrastructure. Conversely, well-designed programmes that embed technological modernisation within holistic development frameworks can generate synergistic benefits. The challenge facing policymakers, development practitioners, and researchers is crafting pathways that harness technological potential while safeguarding against exclusionary dynamics and ecological degradation. This endeavour requires not only technical expertise but also genuine engagement with diverse farming communities as active agents shaping their own technological futures rather than passive recipients of externally-imposed innovations.
Tương lai nông nghiệp thông minh toàn cầu với công nghệ AI và IoT hiện đại
Questions 27-31: Multiple Choice
Choose the correct letter, A, B, C, or D.
-
According to the passage, Rogers’ innovation diffusion theory is limited because:
A. It was developed too long ago to be relevant
B. It assumes linear adoption and ignores network effects
C. It only applies to developed countries
D. It focuses exclusively on large-scale farming -
The Science and Technology Studies perspective suggests that smart agriculture:
A. Simply applies existing technology to farming
B. Only improves productivity without other effects
C. Simultaneously constructs new technological and social orders
D. Has no impact on how farming is understood -
The passage indicates that value from smart agriculture is mainly captured by:
A. Small-scale farmers
B. Rural communities
C. Technology companies and large agribusinesses
D. Government agencies -
According to ecological sceptics, smart agriculture’s focus on micro-level efficiency:
A. Completely solves all environmental problems
B. May obscure concerns about agricultural intensification
C. Reduces the need for climate action
D. Eliminates all carbon emissions -
The concept of “responsible innovation” advocates for:
A. Rapid technology deployment without consultation
B. Banning all agricultural technology
C. Anticipatory governance and inclusive deliberation
D. Leaving innovation entirely to market forces
Questions 32-36: Matching Features
Match each concept (32-36) with the correct description (A-H).
Write the correct letter, A-H.
Concepts:
32. Co-production
33. Value capture
34. Digital commons
35. Responsible innovation
36. Network effects
Descriptions:
A. The uneven distribution of benefits from technological innovation
B. A model where agricultural data is collectively managed
C. The simultaneous construction of technological and social orders
D. The declining cost of sensor technology
E. A framework for steering technology toward socially desirable outcomes
F. The increased value created when multiple farmers use the same technology
G. The replacement of human farmers with robots
H. Government regulation of food prices
Questions 37-40: Short-answer Questions
Answer the questions below.
Choose NO MORE THAN THREE WORDS from the passage for each answer.
- What type of knowledge might be marginalised by algorithmic decision support systems?
- What has empirical evidence shown about the distribution of gains from agricultural innovation?
- What kind of analyses are relatively scarce regarding smart agriculture’s environmental impact?
- According to the passage, farmers should be treated as active agents rather than what?
Answer Keys – Đáp Án
PASSAGE 1: Questions 1-13
- B
- C
- C
- A
- C
- TRUE
- FALSE
- TRUE
- NOT GIVEN
- nitrogen runoff
- 10 billion
- cooperative system
- right
PASSAGE 2: Questions 14-26
- NO
- YES
- NO
- YES
- NOT GIVEN
- I
- C
- D
- G
- F
- widespread adoption
- family farming
- increased dependence / overly reliant (either answer acceptable)
PASSAGE 3: Questions 27-40
- B
- C
- C
- B
- C
- C
- A
- B
- E
- F
- experiential knowledge
- highly uneven
- life-cycle analyses
- passive recipients
Giải Thích Đáp Án Chi Tiết
Passage 1 – Giải Thích
Câu 1: B
- Dạng câu hỏi: Multiple Choice
- Từ khóa: smart agriculture, mainly concerned with
- Vị trí trong bài: Đoạn 1, dòng 2-4
- Giải thích: Bài đọc nói rõ “Smart agriculture… uses modern technologies… to optimise crop production and resource management.” Đây là mục tiêu chính, không phải thay thế nông dân (A), tăng giá (C) hay giảm dân số nông thôn (D).
Câu 2: C
- Dạng câu hỏi: Multiple Choice
- Từ khóa: soil moisture sensors, help farmers
- Vị trí trong bài: Đoạn 2, dòng 5-7
- Giải thích: “Soil moisture sensors can tell farmers exactly when to irrigate their fields” – câu trả lời trực tiếp cho thấy cảm biến giúp xác định thời điểm tưới tiêu tối ưu (determining optimal time = when to irrigate).
Câu 6: TRUE
- Dạng câu hỏi: True/False/Not Given
- Từ khóa: India’s population, agriculture, income
- Vị trí trong bài: Đoạn 3, dòng 1-2
- Giải thích: “More than 60% of the population depends on agriculture for their livelihood” – “more than 60%” = “more than half”, phù hợp với câu hỏi.
Câu 7: FALSE
- Dạng câu hỏi: True/False/Not Given
- Từ khóa: drone technology, only large-scale farms
- Vị trí trong bài: Đoạn 4
- Giải thích: Bài đọc đề cập đến dự án ở Kenya giúp “farmers” (nông dân nói chung), không nói chỉ dành cho trang trại lớn. Từ “only” làm câu này sai.
Câu 10: nitrogen runoff
- Dạng câu hỏi: Sentence Completion
- Từ khóa: Netherlands, reduced, waterways, 35%
- Vị trí trong bài: Đoạn 8, dòng 3-4
- Giải thích: “Smart farming practices have helped reduce nitrogen runoff into waterways by 35%” – đáp án chính xác là “nitrogen runoff” (2 từ).
Câu 13: right
- Dạng câu hỏi: Sentence Completion
- Từ khóa: precision farming, chemicals, amounts
- Vị trí trong bài: Đoạn 8, dòng 1-2
- Giải thích: “Chemicals are used only where needed and in the right amounts” – từ cần điền là “right”, tạo thành “right amounts”.
Passage 2 – Giải Thích
Câu 14: NO
- Dạng câu hỏi: Yes/No/Not Given
- Từ khóa: digital platforms, completely destroyed, traditional knowledge transmission
- Vị trí trong bài: Đoạn B, dòng 2-5
- Giải thích: Bài viết nói digital platforms đã “disrupted these traditional patterns in complex ways” (gây gián đoạn theo cách phức tạp), không phải “completely destroyed” (hoàn toàn phá hủy). Từ “completely” quá tuyệt đối, nên đáp án là NO.
Câu 15: YES
- Dạng câu hỏi: Yes/No/Not Given
- Từ khóa: technology adoption, reduce, productivity disparities
- Vị trí trong bài: Đoạn B, dòng 6-7
- Giải thích: “This democratisation of knowledge has the potential to reduce historical disparities in agricultural productivity” – tác giả đồng ý với quan điểm này, đáp án YES.
Câu 17: YES
- Dạng câu hỏi: Yes/No/Not Given
- Từ khóa: large farms, more advantages, small farms
- Vị trí trong bài: Đoạn E, dòng 2-5
- Giải thích: “Evidence suggests that larger operations have been primary beneficiaries” và “economies of scale… create competitive advantages for bigger farms” – rõ ràng tác giả xác nhận trang trại lớn được lợi nhiều hơn.
Câu 19: I (Paragraph I)
- Dạng câu hỏi: Matching Information
- Từ khóa: cooperative structures, supported technology adoption
- Vị trí trong bài: Đoạn I (cuối đoạn về Netherlands)
- Giải thích: “Netherlands… agricultural innovation has been deliberately coupled with strong cooperative structures” – đoạn này mô tả cụ thể về cấu trúc hợp tác xã.
Câu 22: G (Paragraph G)
- Dạng câu hỏi: Matching Information
- Từ khóa: psychological effects, traditional farmers
- Vị trí trong bài: Đoạn G
- Giải thích: Đoạn G bắt đầu với “The psychological dimensions of this transition” và mô tả cảm xúc của nông dân già ở Nhật về việc tri thức truyền thống bị devalue.
Câu 24: widespread adoption
- Dạng câu hỏi: Summary Completion
- Từ khóa: United States Midwest, farm size, 35%
- Vị trí trong bài: Đoạn E, dòng cuối
- Giải thích: “Average farm size has increased by 35% since the widespread adoption of precision agriculture technologies” – cụm từ cần điền là “widespread adoption”.
Passage 3 – Giải Thích
Câu 27: B
- Dạng câu hỏi: Multiple Choice
- Từ khóa: Rogers’ theory, limited
- Vị trí trong bài: Đoạn 2, dòng 3-8
- Giải thích: Bài viết chỉ ra “Rogers’ model presumes relatively linear adoption processes… Contemporary smart agricultural systems, conversely, are characterised by network effects and systemic dependencies” – lý thuyết Rogers bị hạn chế vì giả định quá trình tuyến tính và bỏ qua hiệu ứng mạng lưới.
Câu 28: C
- Dạng câu hỏi: Multiple Choice
- Từ khóa: Science and Technology Studies, suggests
- Vị trí trong bài: Đoạn 3, dòng 1-4
- Giải thích: “Agricultural modernisation as co-production – a process through which technological and social orders are simultaneously constructed and reconfigured” – đáp án C paraphrase chính xác ý này.
Câu 29: C
- Dạng câu hỏi: Multiple Choice
- Từ khóa: value captured, mainly
- Vị trí trong bài: Đoạn 4, dòng 2-4
- Giải thích: “Technology providers, data analytics firms, and large-scale agribusinesses have captured disproportionate shares of value” – rõ ràng các công ty công nghệ và agribusiness lớn là người hưởng lợi chính.
Câu 32: C
- Dạng câu hỏi: Matching Features
- Từ khóa: Co-production
- Vị trí trong bài: Đoạn 3
- Giải thích: Co-production được định nghĩa là “a process through which technological and social orders are simultaneously constructed and reconfigured” – khớp với description C.
Câu 37: experiential knowledge
- Dạng câu hỏi: Short-answer Questions
- Từ khóa: knowledge, marginalised, algorithmic systems
- Vị trí trong bài: Đoạn 3, dòng 7-8
- Giải thích: “Potentially marginalising experiential knowledge and holistic appreciation of agro-ecological contexts” – đáp án là “experiential knowledge” (2 từ).
Câu 38: highly uneven
- Dạng câu hỏi: Short-answer Questions
- Từ khóa: empirical evidence, distribution of gains
- Vị trí trong bài: Đoạn 4, dòng 1-2
- Giải thích: “Empirical evidence suggests highly uneven distributions of gains” – đáp án chính xác là “highly uneven” (2 từ).
Câu 40: passive recipients
- Dạng câu hỏi: Short-answer Questions
- Từ khóa: farmers, active agents, rather than
- Vị trí trong bài: Đoạn 8, dòng cuối
- Giải thích: “Diverse farming communities as active agents shaping their own technological futures rather than passive recipients of externally-imposed innovations” – đáp án là “passive recipients”.
Từ Vựng Quan Trọng Theo Passage
Passage 1 – Essential Vocabulary
| Từ vựng | Loại từ | Phiên âm | Nghĩa tiếng Việt | Ví dụ từ bài | Collocation |
|---|---|---|---|---|---|
| integration | n | /ˌɪntɪˈɡreɪʃn/ | sự tích hợp, hội nhập | The integration of technology into agriculture | technology integration, social integration |
| revolutionise | v | /ˌrevəˈluːʃənaɪz/ | cách mạng hóa | has revolutionised farming practices | revolutionise industry, revolutionise thinking |
| optimise | v | /ˈɒptɪmaɪz/ | tối ưu hóa | to optimise crop production | optimise efficiency, optimise resources |
| smallholder | n | /ˈsmɔːlhəʊldə(r)/ | nông hộ nhỏ | smallholder farmers face challenges | smallholder agriculture, smallholder farming |
| real-time data | n | /ˌrɪəl taɪm ˈdeɪtə/ | dữ liệu thời gian thực | providing farmers with real-time data | real-time monitoring, real-time information |
| adoption | n | /əˈdɒpʃn/ | sự chấp nhận, áp dụng | The adoption of smart farming tools | technology adoption, widespread adoption |
| game-changing | adj | /ˈɡeɪm tʃeɪndʒɪŋ/ | làm thay đổi cuộc chơi, đột phá | game-changing innovation | game-changing technology, game-changing moment |
| proactive | adj | /prəʊˈæktɪv/ | chủ động, tiên phong | This proactive approach has reduced losses | proactive measures, proactive strategy |
| prohibitive | adj | /prəˈhɪbɪtɪv/ | cấm đoán, quá đắt | initial investment can be prohibitive | prohibitive cost, prohibitive price |
| infrastructure | n | /ˈɪnfrəstrʌktʃə(r)/ | cơ sở hạ tầng | lack the infrastructure necessary | digital infrastructure, transport infrastructure |
| sustainable | adj | /səˈsteɪnəbl/ | bền vững | producing food sustainably | sustainable development, sustainable agriculture |
| thrive | v | /θraɪv/ | phát triển mạnh, thịnh vượng | rural communities can thrive economically | thrive on, business thrives |
Passage 2 – Essential Vocabulary
| Từ vựng | Loại từ | Phiên âm | Nghĩa tiếng Việt | Ví dụ từ bài | Collocation |
|---|---|---|---|---|---|
| advent | n | /ˈædvent/ | sự xuất hiện, khởi đầu | The advent of smart agriculture | the advent of technology, the advent of change |
| catalyse | v | /ˈkætəlaɪz/ | xúc tác, thúc đẩy | has catalysed a transformation | catalyse change, catalyse growth |
| socio-economic | adj | /ˌsəʊsiəʊ iːkəˈnɒmɪk/ | kinh tế-xã hội | socio-economic transformation | socio-economic factors, socio-economic development |
| fabric | n | /ˈfæbrɪk/ | kết cấu, bản chất | the very fabric of rural society | social fabric, fabric of society |
| intergenerational | adj | /ˌɪntədʒenəˈreɪʃənl/ | liên thế hệ | intergenerational teaching | intergenerational transfer, intergenerational conflict |
| democratisation | n | /dɪˌmɒkrətaɪˈzeɪʃn/ | dân chủ hóa | democratisation of knowledge | democratisation of information, democratisation of access |
| disparities | n | /dɪˈspærətiz/ | sự chênh lệch, bất bình đẳng | reduce historical disparities | income disparities, gender disparities |
| counterparts | n | /ˈkaʊntəpɑːts/ | đối tác, đồng nghiệp | compared to their counterparts | business counterparts, male counterparts |
| nuanced | adj | /ˈnjuːɑːnst/ | tinh tế, nhiều sắc thái | nuanced patterns in adoption | nuanced understanding, nuanced approach |
| underscore | v | /ˌʌndəˈskɔː(r)/ | nhấn mạnh, làm nổi bật | findings underscore the importance | underscore the need, underscore the significance |
| ramifications | n | /ˌræmɪfɪˈkeɪʃnz/ | hệ quả, hậu quả | economic ramifications extend | serious ramifications, political ramifications |
| lucrative | adj | /ˈluːkrətɪv/ | sinh lời, béo bở | providing lucrative alternatives | lucrative business, lucrative market |
| paradoxically | adv | /ˌpærəˈdɒksɪkli/ | một cách nghịch lý | Paradoxically, while technology could benefit | paradoxically, this approach |
| proponents | n | /prəˈpəʊnənts/ | người ủng hộ | proponents emphasise reduced inputs | proponents of change, proponents argue |
| augment | v | /ɔːɡˈment/ | tăng cường, bổ sung | systems that augment human judgment | augment income, augment capabilities |
Passage 3 – Essential Vocabulary
| Từ vựng | Loại từ | Phiên âm | Nghĩa tiếng Việt | Ví dụ từ bài | Collocation |
|---|---|---|---|---|---|
| trajectory | n | /trəˈdʒektəri/ | quỹ đạo, tiến trình | the trajectory of modernisation | development trajectory, career trajectory |
| multifaceted | adj | /ˌmʌltiˈfæsɪtɪd/ | nhiều mặt, đa diện | multifaceted phenomenon | multifaceted problem, multifaceted approach |
| discourse | n | /ˈdɪskɔːs/ | diễn ngôn, thảo luận | contemporary discourse on agriculture | public discourse, academic discourse |
| dichotomous | adj | /daɪˈkɒtəməs/ | lưỡng phân, hai mặt | beyond dichotomous framings | dichotomous thinking, dichotomous division |
| contingent | adj | /kənˈtɪndʒənt/ | phụ thuộc, ngẫu nhiên | shaped by contingent interactions | contingent upon, contingent factors |
| affordances | n | /əˈfɔːdənsɪz/ | khả năng hỗ trợ (của công nghệ) | technological affordances | digital affordances, affordances of tools |
| articulated | v | /ɑːˈtɪkjuleɪtɪd/ | diễn đạt, phát biểu | originally articulated by Rogers | clearly articulated, well articulated |
| accrues | v | /əˈkruːz/ | tích lũy, gia tăng | value accrues from individual use | interest accrues, benefit accrues |
| externalities | n | /ˌekstɜːˈnælətiz/ | yếu tố bên ngoài | creating positive externalities | negative externalities, environmental externalities |
| co-production | n | /kəʊ prəˈdʌkʃn/ | đồng sản xuất | conceptualising as co-production | knowledge co-production, co-production process |
| ontology | n | /ɒnˈtɒlədʒi/ | bản thể luận | the ontology of farming | social ontology, ontology of concepts |
| disproportionate | adj | /ˌdɪsprəˈpɔːʃənət/ | không cân xứng, mất cân đối | captured disproportionate shares | disproportionate impact, disproportionate effect |
| asymmetric | adj | /ˌeɪsɪˈmetrɪk/ | bất đối xứng | asymmetric relationship | asymmetric information, asymmetric power |
| recapitulates | v | /ˌriːkəˈpɪtʃuleɪts/ | tái diễn, lặp lại | recapitulates historical patterns | recapitulates the argument, recapitulates themes |
| inadvertently | adv | /ˌɪnədˈvɜːtntli/ | vô tình, không cố ý | may inadvertently reinforce | inadvertently created, inadvertently caused |
| proliferation | n | /prəˌlɪfəˈreɪʃn/ | sự gia tăng nhanh, phổ biến | proliferation of IoT devices | nuclear proliferation, proliferation of weapons |
| catalyse | v | /ˈkætəlaɪz/ | xúc tác, kích hoạt | may catalyse interventionist policies | catalyse change, catalyse innovation |
| synergistic | adj | /ˌsɪnəˈdʒɪstɪk/ | hiệp đồng, tăng hiệu quả | generate synergistic benefits | synergistic effect, synergistic relationship |
Kết Bài
Chủ đề “The rise of smart agriculture in rural development” không chỉ phổ biến trong các kỳ thi IELTS Reading mà còn phản ánh một xu hướng toàn cầu quan trọng về chuyển đổi số trong nông nghiệp. Ba passages trong đề thi mẫu này đã cung cấp một bức tranh toàn diện từ cơ bản đến chuyên sâu về cách công nghệ thông minh đang thay đổi nông thôn.
Passage 1 giới thiệu các công nghệ cơ bản và lợi ích trực tiếp của nông nghiệp thông minh, phù hợp với học viên band 5.0-6.5. Passage 2 đi sâu vào các tác động kinh tế-xã hội phức tạp hơn, yêu cầu kỹ năng phân tích ở mức band 6.0-7.5. Passage 3 khám phá các khung lý thuyết và tranh luận học thuật, thách thức học viên ở mức band 7.0-9.0.
Các đáp án chi tiết kèm giải thích đã chỉ ra cách xác định thông tin trong bài, paraphrase giữa câu hỏi và passage, và phương pháp loại trừ đáp án sai. Bảng từ vựng phân theo passage giúp bạn xây dựng vốn từ học thuật cần thiết cho cả bài thi Reading và Writing.
Hãy làm lại đề thi này ít nhất 2-3 lần, chú ý đến thời gian và cải thiện tốc độ đọc. Phân tích kỹ những câu trả lời sai để hiểu rõ lỗi suy luận hoặc kỹ thuật làm bài. Thành công trong IELTS Reading đến từ việc luyện tập đều đặn và có phương pháp. Chúc bạn đạt band điểm như mong muốn!
