Mở bài
Chủ đề “The Rise Of Automation In The Travel Industry” (Sự phát triển của tự động hóa trong ngành du lịch) đang trở thành một xu hướng nổi bật trong các kỳ thi IELTS Reading gần đây. Với sự phát triển vượt bậc của công nghệ và trí tuệ nhân tạo, ngành du lịch đang trải qua những thay đổi cách mạng, từ quy trình đặt vé máy bay tự động đến robot phục vụ tại khách sạn. Chủ đề này thường xuất hiện trong các đề thi IELTS Academic với tần suất khá cao, đặc biệt từ năm 2020 trở lại đây.
Bài viết này cung cấp cho bạn một bộ đề thi IELTS Reading hoàn chỉnh với 3 passages có độ khó tăng dần từ Easy đến Hard, bao gồm 40 câu hỏi đa dạng giống như trong kỳ thi thật. Bạn sẽ được học cách làm bài với các dạng câu hỏi phổ biến như True/False/Not Given, Matching Headings, Multiple Choice và Summary Completion. Đặc biệt, đáp án chi tiết kèm giải thích sẽ giúp bạn hiểu rõ cách paraphrase và xác định thông tin trong bài đọc. Ngoài ra, bộ từ vựng chuyên ngành được tổng hợp từ các passages sẽ giúp bạn nâng cao vốn từ vựng về chủ đề công nghệ và du lịch.
Đề thi này phù hợp cho học viên có trình độ từ band 5.0 trở lên và mong muốn cải thiện kỹ năng đọc hiểu học thuật. Cũng giống như How does the rise of automation affect the service industry?, chủ đề này yêu cầu bạn hiểu sâu về tác động của công nghệ đến các ngành dịch vụ, một trong những nội dung quan trọng trong IELTS Reading.
Hướng Dẫn Làm Bài IELTS Reading
Tổng Quan Về IELTS Reading Test
IELTS Reading Test là phần thi kéo dài 60 phút với 3 passages và tổng cộng 40 câu hỏi. Đây là phần thi kiểm tra khả năng đọc hiểu, phân tích thông tin và tư duy logic của thí sinh. Mỗi passage có độ dài khoảng 700-900 từ và độ khó tăng dần.
Phân bổ thời gian khuyến nghị:
- Passage 1: 15-17 phút (độ khó Easy, band 5.0-6.5)
- Passage 2: 18-20 phút (độ khó Medium, band 6.0-7.5)
- Passage 3: 23-25 phút (độ khó Hard, band 7.0-9.0)
Với chủ đề về tự động hóa trong ngành du lịch, bạn cần đặc biệt chú ý đến các từ vựng chuyên ngành liên quan đến công nghệ, du lịch và kinh doanh. Việc nhận biết paraphrase của các thuật ngữ kỹ thuật là chìa khóa để trả lời chính xác các câu hỏi.
Các Dạng Câu Hỏi Trong Đề Này
Đề thi mẫu này bao gồm 7 dạng câu hỏi phổ biến trong IELTS Reading:
- Multiple Choice – Câu hỏi trắc nghiệm với nhiều lựa chọn
- True/False/Not Given – Xác định tính đúng sai của thông tin
- Yes/No/Not Given – Xác định quan điểm của tác giả
- Matching Headings – Ghép tiêu đề với đoạn văn
- Sentence Completion – Hoàn thành câu
- Summary Completion – Hoàn thành đoạn tóm tắt
- Short-answer Questions – Câu hỏi trả lời ngắn
Mỗi dạng câu hỏi yêu cầu kỹ năng đọc hiểu khác nhau, từ skimming (đọc lướt) đến scanning (đọc tìm kiếm thông tin cụ thể).
Đề thi IELTS Reading về tự động hóa trong ngành du lịch với các dạng câu hỏi đa dạng
IELTS Reading Practice Test
PASSAGE 1 – The Digital Revolution in Travel Booking
Độ khó: Easy (Band 5.0-6.5)
Thời gian đề xuất: 15-17 phút
The way people book their holidays has changed dramatically over the past two decades. Gone are the days when travellers had to visit traditional travel agencies to arrange their trips. Today, the rise of automation in the travel industry has made it possible for anyone with an internet connection to plan and book an entire vacation within minutes, often without speaking to a single human being.
Online booking platforms such as Expedia, Booking.com, and Airbnb have revolutionised the travel industry by offering instant access to millions of hotels, flights, and holiday packages. These platforms use sophisticated algorithms to search through thousands of options and present users with the best deals tailored to their preferences. The automation of this process means that what once took travel agents hours or even days to research can now be completed in seconds.
One of the most significant advantages of automated booking systems is the ability to compare prices across multiple providers simultaneously. In the past, travellers might have had to call several airlines or visit different travel agencies to find the best deal. Now, comparison websites do this work automatically, displaying results in an easy-to-read format that highlights the cheapest or most convenient options. This transparency has not only saved consumers time but has also driven down prices as companies compete more directly for customers.
Mobile technology has taken this convenience even further. Travel apps allow users to book flights, accommodation, and activities while on the move. Many of these apps incorporate artificial intelligence (AI) features that learn from users’ previous bookings and can make personalised recommendations. For instance, if you frequently book budget hotels in city centres, the app will prioritise similar options in your search results. Some apps even send automated notifications about price drops or special offers for destinations you’ve shown interest in.
The check-in process has also been transformed by automation. Airlines now offer online check-in services that open 24 hours before departure, allowing passengers to select seats and obtain digital boarding passes without queuing at an airport counter. Many airports have installed self-service kiosks where travellers can print boarding passes, check luggage, and even change their seats. This streamlined process reduces waiting times and allows airline staff to focus on passengers who need additional assistance.
However, the shift towards automation is not without its challenges. Some travellers, particularly older generations who are less comfortable with technology, find these systems confusing and impersonal. When problems arise, such as flight cancellations or booking errors, dealing with automated customer service systems can be frustrating. Many companies rely on chatbots for initial customer queries, but these AI-powered assistants cannot always handle complex issues that require human judgment and empathy.
Despite these concerns, the trend towards automation in travel booking shows no signs of slowing down. Industry experts predict that future developments will include more sophisticated voice-activated booking systems, virtual reality tours of hotels before booking, and even more predictive technology that anticipates travellers’ needs before they express them. The challenge for the travel industry will be to balance the efficiency gains from automation with the human touch that many travellers still value.
Questions 1-6: Multiple Choice
Choose the correct letter, A, B, C, or D.
1. According to the passage, how has travel booking changed in the past twenty years?
A. It has become more expensive
B. It requires more human interaction
C. It can be done much faster
D. It is only available through travel agencies
2. What do online booking platforms use to find travel options?
A. Human travel agents
B. Complex computer programs
C. Customer feedback
D. Traditional methods
3. Comparison websites have helped consumers by:
A. increasing the number of travel agencies
B. making prices more competitive
C. requiring them to make phone calls
D. limiting their choices
4. Mobile travel apps with AI can:
A. replace all human travel agents
B. only book flights
C. suggest options based on past behaviour
D. work without internet connection
5. Self-service kiosks at airports allow passengers to:
A. board the plane automatically
B. avoid all contact with airline staff
C. check in their luggage themselves
D. change their flight destination
6. What is mentioned as a disadvantage of automated systems?
A. They are too expensive for airlines
B. They work too slowly
C. Older travellers may struggle to use them
D. They require too much training
Questions 7-13: 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
7. Traditional travel agencies have completely disappeared from the market.
8. Automated booking systems can search through thousands of options in a very short time.
9. Price comparison websites always show the absolute cheapest option available.
10. Travel apps can send alerts about reduced prices for destinations users are interested in.
11. Online check-in is available one day before the flight departs.
12. Chatbots can solve all customer service problems effectively.
13. Future travel technology may include virtual reality hotel tours.
PASSAGE 2 – Automation in Hospitality Services
Độ khó: Medium (Band 6.0-7.5)
Thời gian đề xuất: 18-20 phút
The hospitality sector has emerged as one of the most enthusiastic adopters of automation technology, with hotels, resorts, and restaurants deploying a wide range of automated solutions to enhance operational efficiency and improve the guest experience. This transformation, driven by advances in robotics, artificial intelligence, and the Internet of Things (IoT), is reshaping not only how these businesses operate but also the very nature of customer service in the travel industry.
At the forefront of this revolution are automated check-in systems. Many hotel chains have replaced traditional reception desks with digital kiosks or smartphone-based check-in applications. The Hilton Hotel chain, for instance, has implemented a system called Digital Key, which allows guests to bypass the front desk entirely. Travellers can select their room, check in, and unlock their door using only their mobile device. This technology not only reduces waiting times during peak hours but also allows hotels to reallocate staff to other areas where human interaction adds more value, such as concierge services or guest relations.
Robotic assistants have made particularly striking appearances in Asian hotels. Japan’s Henn-na Hotel, which translates to “Strange Hotel,” opened in 2015 with a staff composed predominantly of robots. These mechanical workers perform various tasks, from greeting guests at reception to delivering luggage to rooms and even providing in-room assistance. The hotel’s multilingual robot receptionists, resembling both humanoid figures and dinosaurs, can interact with guests in multiple languages, demonstrating the potential for automation to overcome language barriers that often challenge the international travel industry.
However, the Henn-na Hotel’s experience also illustrates the limitations of current automation technology. In 2019, the hotel announced it had “dismissed” more than half of its 243 robots after they created more work for human staff rather than reducing it. The voice-activated in-room assistants frequently misunderstood commands, waking guests with unnecessary responses. This high-profile setback serves as a reminder that automation technology, while advancing rapidly, is not yet capable of fully replacing the nuanced understanding and problem-solving abilities that human staff bring to hospitality services.
Food service automation represents another significant trend in the travel industry. Airport restaurants and hotel dining areas are increasingly adopting tablet-based ordering systems and automated food delivery. At Singapore’s Changi Airport, restaurants use a central kitchen automation system that coordinates orders from multiple outlets, employing robotic cooking equipment and automated delivery tracks to transport meals. These systems can maintain consistent quality, reduce food waste, and serve customers more quickly during rush periods. Moreover, touchscreen menus with photographs and detailed descriptions help overcome language difficulties and allow customers to customise orders with greater precision than traditional menu systems permit.
The back-end operations of hospitality businesses have also been transformed by automation. Smart hotel rooms equipped with IoT sensors can automatically adjust lighting, temperature, and entertainment systems based on occupancy and guest preferences. These systems learn from guests’ behaviour patterns, creating a more comfortable environment while simultaneously reducing energy consumption. Predictive maintenance systems use data from these sensors to identify equipment that may soon fail, allowing preventive repairs before guests are affected. Hotels report that such systems have significantly reduced complaints about room temperature, lighting, and equipment malfunctions.
Revenue management, a crucial aspect of hospitality business, has been revolutionised by automated pricing algorithms. These sophisticated systems analyse vast amounts of data—including historical booking patterns, local events, competitor pricing, and even weather forecasts—to dynamically adjust room rates in real-time. This algorithmic pricing ensures hotels maximise occupancy while optimising revenue, achieving a balance that would be impossible for humans to maintain manually. Airlines have used similar systems for years, but their adoption in hotels represents a significant shift in how accommodation providers approach pricing strategy.
Despite the numerous advantages automation brings to hospitality, the industry faces an important challenge: maintaining the personal touch that many travellers value. Luxury hotels, in particular, have built their reputations on providing personalised, attentive service that anticipates guests’ needs. While automation can handle routine transactions efficiently, it cannot yet replicate the genuine warmth, intuition, and emotional intelligence that characterise exceptional human service. The most successful hospitality businesses are those that use automation to eliminate tedious tasks, allowing staff to focus on creating memorable personal interactions that distinguish their brand and foster customer loyalty.
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
14. Digital Key technology has been universally successful in all hotel chains.
15. The use of robots in hotels can help solve communication problems with international guests.
16. The Henn-na Hotel experience proves that current robot technology has some important limitations.
17. Automated food ordering systems are cheaper to install than traditional systems.
18. The most effective approach combines automation with meaningful human interaction.
Questions 19-23: Matching Headings
The passage has eight paragraphs. Choose the correct heading for paragraphs C-G from the list of headings below.
List of Headings:
i. The financial benefits of automated pricing
ii. Lessons learned from robot failures
iii. Mobile technology replacing traditional check-in
iv. The future of robotic staff in hotels
v. Automated restaurants and dining services
vi. Smart room technology and energy savings
vii. The importance of human service in luxury hotels
viii. Training staff to work with automation
ix. Guest reactions to automated systems
19. Paragraph C (starting with “Robotic assistants…”)
20. Paragraph D (starting with “However, the Henn-na…”)
21. Paragraph E (starting with “Food service automation…”)
22. Paragraph F (starting with “The back-end operations…”)
23. Paragraph G (starting with “Revenue management…”)
Questions 24-26: Sentence Completion
Complete the sentences below. Choose NO MORE THAN TWO WORDS from the passage for each answer.
24. Hotels can use automation to move employees to departments where __ is more important.
25. IoT sensors in hotel rooms can learn from guests’ __ to provide better comfort.
26. Automated pricing systems consider many factors, including __, to set optimal room prices.
PASSAGE 3 – The Socioeconomic Implications of Travel Industry Automation
Độ khó: Hard (Band 7.0-9.0)
Thời gian đề xuất: 23-25 phút
The inexorable march of automation through the travel industry represents far more than a mere technological upgrade; it constitutes a fundamental restructuring of one of the world’s largest employment sectors, with profound implications for labour markets, skill requirements, and socioeconomic inequality. As machine learning algorithms, robotics, and artificial intelligence increasingly supplant human workers in roles ranging from reservation agents to baggage handlers, policymakers, industry leaders, and workers themselves must grapple with the complex ramifications of this unprecedented transformation.
The scale of potential displacement is staggering. The travel and tourism sector employs approximately 330 million people globally, accounting for roughly one in ten jobs worldwide. A 2019 study by the McKinsey Global Institute estimated that up to 30% of tasks currently performed by human workers in the travel industry could be automated using existing technology. While this does not necessarily translate to equivalent job losses—as workers may be redeployed to other responsibilities—the research suggests that between 40 and 75 million workers globally may need to transition to new occupations or acquire new skills by 2030. The distributional impact of this transition will be far from uniform, with lower-skilled positions facing disproportionate vulnerability.
Economic theory offers competing perspectives on automation’s ultimate impact on employment. Optimists invoke historical precedent, noting that previous waves of technological change, from the Industrial Revolution to the computer age, ultimately created more jobs than they destroyed, albeit often in entirely new sectors. They argue that automation in travel will follow a similar pattern: while routine, repetitive tasks are automated, new positions will emerge requiring distinctly human capabilities such as creative problem-solving, emotional intelligence, and complex interpersonal communication. Moreover, by reducing costs and improving service efficiency, automation may stimulate demand for travel, thereby expanding the industry and creating employment opportunities that offset losses elsewhere.
Pessimists, however, contend that contemporary automation differs fundamentally from previous technological revolutions in both scope and speed. Unlike earlier innovations that primarily augmented human capabilities, modern AI systems can independently perform cognitive tasks once thought to require human judgment. The travel industry’s customer-facing roles—traditionally considered relatively immune to automation due to their interpersonal nature—are increasingly vulnerable as natural language processing and affective computing enable machines to engage in increasingly sophisticated interactions. Furthermore, the rapid pace of current technological change may outstrip the capacity of educational systems and labour markets to adapt, potentially creating a protracted period of structural unemployment and social dislocation.
The empirical evidence thus far presents a nuanced picture. Research conducted by Oxford University economists Carl Benedikt Frey and Michael Osborne suggests that approximately 47% of US employment is in occupations at high risk of automation within the next two decades. Within the travel industry specifically, positions such as reservation and booking agents face automation probabilities exceeding 90%, while roles such as tour guides and travel counsellors are deemed considerably less susceptible, with automation probabilities below 25%. Critically, the study found a strong negative correlation between automation risk and both wage levels and educational requirements, suggesting that automation may exacerbate existing inequalities by disproportionately affecting lower-income workers.
However, longitudinal data from early adopters of travel automation reveal outcomes more complex than simple substitution models would predict. Airlines that implemented automated check-in systems did reduce front-desk staffing by approximately 30%, but many reallocated these workers to customer service roles focused on handling exceptions, providing personalized assistance, and managing disruptions—tasks that both add greater value and prove more resistant to automation. This pattern suggests a potential pathway wherein automation eliminates specific tasks rather than entire occupations, necessitating workforce adaptation rather than wholesale displacement.
The skills implications of travel industry automation extend beyond narrow technical competencies. While demand for workers with programming, data analytics, and systems maintenance expertise will undoubtedly increase, the most resilient positions will likely be those requiring sophisticated interpersonal skills, cultural intelligence, creative problem-solving, and adaptive learning capabilities—attributes that current automation technology cannot easily replicate. This suggests that educational systems must pivot away from rote learning and task-specific training toward cultivating higher-order thinking skills, emotional intelligence, and cognitive flexibility.
Policy responses to travel industry automation have varied considerably across jurisdictions. Some nations, particularly in Northern Europe, have adopted proactive strategies emphasizing worker retraining programmes, robust social safety nets, and regulatory frameworks that encourage gradual transition. Others have taken more laissez-faire approaches, allowing market forces to drive adjustment, with minimal government intervention. Early evidence suggests that proactive approaches may reduce the social costs of automation while maintaining economic competitiveness, though definitive conclusions require longer-term assessment.
Perhaps most critically, the automation of travel industry services raises profound questions about the nature and purpose of work itself. If machines can perform many tasks more efficiently than humans, society must confront fundamental decisions about income distribution, social identity, and human fulfillment. Proposals such as universal basic income, reduced working hours, and expanded leisure time have gained traction as potential responses to automation-driven unemployment. The travel industry, as both a significant employer and a facilitator of human experiences, sits at the nexus of these debates, making its successful navigation of the automation transition a matter of considerable societal importance.
The challenge facing the global travel industry, therefore, extends far beyond technical implementation of automated systems. It encompasses workforce development, social policy, educational reform, and ultimately, a reimagining of how humans and machines can coexist productively in an economy increasingly characterized by artificial intelligence. The decisions made in the coming decade will shape not only the future of travel but also broader patterns of work, inequality, and human flourishing in an automated age.
Tác động xã hội và kinh tế của tự động hóa trong ngành du lịch toàn cầu
Questions 27-31: Multiple Choice
Choose the correct letter, A, B, C, or D.
27. According to the passage, what proportion of tasks in the travel industry could potentially be automated?
A. Exactly 10%
B. Around one-third
C. Approximately 47%
D. Between 40 and 75%
28. What do optimists believe about automation and employment?
A. It will destroy more jobs than it creates
B. It will create jobs in completely new areas
C. It will only affect low-skilled workers
D. It will have no significant impact
29. How do pessimists view current automation compared to previous technological changes?
A. It is essentially the same
B. It only augments human abilities
C. It can independently perform cognitive tasks
D. It is slower and less impactful
30. What did Frey and Osborne’s research find about automation risk?
A. All travel jobs face equal risk
B. Higher-paid jobs face greater risk
C. Tour guides are most at risk
D. Lower-income workers are more vulnerable
31. What do airlines’ experiences with automated check-in demonstrate?
A. All front-desk staff were made redundant
B. Some workers were moved to different roles
C. Automation completely failed
D. Customer satisfaction decreased significantly
Questions 32-36: Matching Features
Match each statement (32-36) with the correct group of people (A-E).
A. Optimists
B. Pessimists
C. Oxford University researchers
D. Northern European nations
E. Travel industry employers
32. Have implemented comprehensive retraining programs for workers
33. Believe historical patterns suggest job creation will exceed job losses
34. Found that wage levels correlate with automation risk
35. Argue that modern AI differs fundamentally from previous technology
36. Reallocated workers to customer service positions
Questions 37-40: Summary Completion
Complete the summary below. Choose NO MORE THAN TWO WORDS from the passage for each answer.
The automation of the travel industry raises important questions about the future of work. While machines can perform many tasks with greater (37) ____ than humans, society must address issues related to income distribution and social identity. Some proposals to address automation-driven unemployment include implementing a (38) ____, reducing working hours, and expanding leisure time. The travel industry is particularly important in these debates because it is both a major employer and a provider of (39) __. Successfully managing the transition to automation requires not just technical implementation but also workforce development, social policy, and **(40) __, ensuring that humans and machines can work together productively.
Answer Keys – Đáp Án
PASSAGE 1: Questions 1-13
- C
- B
- B
- C
- C
- C
- NOT GIVEN
- TRUE
- NOT GIVEN
- TRUE
- TRUE
- FALSE
- TRUE
PASSAGE 2: Questions 14-26
- NOT GIVEN
- YES
- YES
- NOT GIVEN
- YES
- ix (Guest reactions to automated systems) / Alternatively acceptable: Robotic staff in Asian hotels
- ii
- v
- vi
- i
- human interaction / human touch
- behaviour patterns
- weather forecasts / local events / competitor pricing
PASSAGE 3: Questions 27-40
- B
- B
- C
- D
- B
- D
- A
- C
- B
- E
- efficiency
- universal basic income
- human experiences
- educational reform
Giải Thích Đáp Án Chi Tiết
Passage 1 – Giải Thích
Câu 1: C
- Dạng câu hỏi: Multiple Choice
- Từ khóa: how has travel booking changed, past twenty years
- Vị trí trong bài: Đoạn 1, dòng 1-3
- Giải thích: Câu đầu tiên nói “The way people book their holidays has changed dramatically over the past two decades” và sau đó nhấn mạnh việc book trong vòng “minutes”. Đây là paraphrase của “much faster”. Các phương án khác không được đề cập hoặc trái ngược với thông tin trong bài.
Câu 2: B
- Dạng câu hỏi: Multiple Choice
- Từ khóa: online booking platforms use
- Vị trí trong bài: Đoạn 2, dòng 2-3
- Giải thích: Bài viết nói rõ “These platforms use sophisticated algorithms”, trong đó “sophisticated algorithms” chính là “complex computer programs”.
Câu 7: NOT GIVEN
- Dạng câu hỏi: True/False/Not Given
- Từ khóa: traditional travel agencies, completely disappeared
- Vị trí trong bài: Đoạn 1
- Giải thích: Bài chỉ nói “Gone are the days when travellers had to visit traditional travel agencies” – nghĩa là không còn bắt buộc phải đến đó, nhưng không khẳng định chúng đã hoàn toàn biến mất khỏi thị trường.
Câu 8: TRUE
- Dạng câu hỏi: True/False/Not Given
- Từ khóa: automated booking systems, search, thousands of options, very short time
- Vị trí trong bài: Đoạn 2, dòng 4-6
- Giải thích: Câu “what once took travel agents hours or even days to research can now be completed in seconds” khẳng định hệ thống tự động có thể tìm kiếm qua hàng nghìn lựa chọn trong thời gian rất ngắn.
Câu 12: FALSE
- Dạng câu hỏi: True/False/Not Given
- Từ khóa: chatbots, solve all customer service problems
- Vị trí trong bài: Đoạn 6, dòng 4-6
- Giải thích: Bài viết nói “these AI-powered assistants cannot always handle complex issues that require human judgment” – điều này trái ngược với việc chatbot có thể giải quyết TẤT CẢ vấn đề.
Passage 2 – Giải Thích
Câu 15: YES
- Dạng câu hỏi: Yes/No/Not Given
- Từ khóa: robots in hotels, solve communication problems, international guests
- Vị trí trong bài: Đoạn C, dòng 5-7
- Giải thích: Đoạn văn nói rõ “multilingual robot receptionists…demonstrating the potential for automation to overcome language barriers that often challenge the international travel industry”. Đây là quan điểm của tác giả về khả năng robot giải quyết vấn đề giao tiếp.
Câu 16: YES
- Dạng câu hỏi: Yes/No/Not Given
- Từ khóa: Henn-na Hotel, proves, robot technology, limitations
- Vị trí trong bài: Đoạn D, toàn bộ
- Giải thích: Tác giả sử dụng câu “This high-profile setback serves as a reminder that automation technology…is not yet capable of fully replacing” để thể hiện quan điểm về hạn chế của công nghệ robot hiện tại.
Câu 20: ii (Lessons learned from robot failures)
- Dạng câu hỏi: Matching Headings
- Vị trí trong bài: Đoạn D
- Giải thích: Đoạn này tập trung vào việc khách sạn Henn-na phải “sa thải” robot vì chúng tạo ra nhiều vấn đề hơn là giải quyết, và bài học rút ra về giới hạn của công nghệ tự động hóa hiện tại.
Cần lưu ý rằng đoạn về tự động hóa trong ngành dịch vụ có sự liên quan mật thiết với The influence of social networks on public opinion khi cả hai đều liên quan đến tác động của công nghệ đối với xã hội hiện đại.
Câu 24: human interaction / human touch
- Dạng câu hỏi: Sentence Completion
- Từ khóa: hotels, use automation, move employees, more important
- Vị trí trong bài: Đoạn B, dòng 6-8
- Giải thích: Câu “allows hotels to reallocate staff to other areas where human interaction adds more value” cho thấy nhân viên được chuyển đến nơi “human interaction” quan trọng hơn.
Passage 3 – Giải Thích
Câu 27: B
- Dạng câu hỏi: Multiple Choice
- Từ khóa: proportion of tasks, travel industry, automated
- Vị trí trong bài: Đoạn B, dòng 3-4
- Giải thích: Bài viết nói “up to 30% of tasks currently performed by human workers in the travel industry could be automated” – tương đương với “around one-third”.
Câu 29: C
- Dạng câu hỏi: Multiple Choice
- Từ khóa: pessimists view, current automation, previous technological changes
- Vị trí trong bài: Đoạn D, dòng 1-5
- Giải thích: Đoạn văn nói “Unlike earlier innovations that primarily augmented human capabilities, modern AI systems can independently perform cognitive tasks” – đây là điểm khác biệt then chốt mà những người bi quan nhấn mạnh.
Câu 30: D
- Dạng câu hỏi: Multiple Choice
- Từ khóa: Frey and Osborne’s research, automation risk
- Vị trí trong bài: Đoạn E, dòng 6-8
- Giải thích: Nghiên cứu “found a strong negative correlation between automation risk and both wage levels and educational requirements, suggesting that automation may exacerbate existing inequalities by disproportionately affecting lower-income workers”.
Câu 35: B (Pessimists)
- Dạng câu hỏi: Matching Features
- Từ khóa: modern AI differs fundamentally from previous technology
- Vị trí trong bài: Đoạn D, dòng 1-2
- Giải thích: Đoạn văn bắt đầu bằng “Pessimists, however, contend that contemporary automation differs fundamentally from previous technological revolutions”.
Câu 37: efficiency
- Dạng câu hỏi: Summary Completion
- Từ khóa: machines, perform tasks, greater than humans
- Vị trí trong bài: Đoạn I, dòng 1-2
- Giải thích: Câu “If machines can perform many tasks more efficiently than humans” cung cấp từ cần điền.
Câu 40: educational reform
- Dạng câu hỏi: Summary Completion
- Từ khóa: workforce development, social policy
- Vị trí trong bài: Đoạn J, dòng 1-3
- Giải thích: Bài liệt kê “workforce development, social policy, educational reform” như những yếu tố cần thiết để quản lý chuyển đổi sang tự động hóa.
Từ Vựng Quan Trọng Theo Passage
Passage 1 – Essential Vocabulary
| Từ vựng | Loại từ | Phiên âm | Nghĩa tiếng Việt | Ví dụ từ bài | Collocation |
|---|---|---|---|---|---|
| dramatically | adv | /drəˈmætɪkli/ | một cách đáng kể, mạnh mẽ | The way people book holidays has changed dramatically | change dramatically, increase dramatically |
| sophisticated | adj | /səˈfɪstɪkeɪtɪd/ | tinh vi, phức tạp | These platforms use sophisticated algorithms | sophisticated technology, sophisticated system |
| tailor | v | /ˈteɪlə(r)/ | điều chỉnh, tùy chỉnh theo nhu cầu | best deals tailored to their preferences | tailor to needs, tailor-made |
| transparency | n | /trænsˈpærənsi/ | tính minh bạch | This transparency has saved consumers time | price transparency, ensure transparency |
| personalised | adj | /ˈpɜːsənəlaɪzd/ | được cá nhân hóa | make personalised recommendations | personalised service, personalised experience |
| streamlined | adj | /ˈstriːmlaɪnd/ | được tối ưu hóa, đơn giản hóa | This streamlined process reduces waiting times | streamlined process, streamlined operation |
| impersonal | adj | /ɪmˈpɜːsənl/ | thiếu tính cá nhân, xa cách | find these systems impersonal | impersonal service, impersonal interaction |
| chatbot | n | /ˈtʃætbɒt/ | trợ lý ảo, robot trò chuyện | Many companies rely on chatbots | AI chatbot, customer service chatbot |
| flight cancellation | n | /flaɪt ˌkænsəˈleɪʃn/ | hủy chuyến bay | problems such as flight cancellations | flight cancellation policy, deal with cancellations |
| industry expert | n | /ˈɪndəstri ˈekspɜːt/ | chuyên gia ngành | Industry experts predict future developments | according to industry experts |
| predictive technology | n | /prɪˈdɪktɪv tekˈnɒlədʒi/ | công nghệ dự đoán | more predictive technology that anticipates needs | use predictive technology |
| efficiency gain | n | /ɪˈfɪʃnsi ɡeɪn/ | lợi ích về hiệu quả | balance the efficiency gains from automation | achieve efficiency gains |
Passage 2 – Essential Vocabulary
| Từ vựng | Loại từ | Phiên âm | Nghĩa tiếng Việt | Ví dụ từ bài | Collocation |
|---|---|---|---|---|---|
| hospitality sector | n | /ˌhɒspɪˈtæləti ˈsektə(r)/ | ngành khách sạn và dịch vụ | The hospitality sector has emerged as an enthusiastic adopter | work in hospitality sector |
| deploy | v | /dɪˈplɔɪ/ | triển khai, sử dụng | hotels deploying a wide range of automated solutions | deploy technology, deploy resources |
| operational efficiency | n | /ˌɒpəˈreɪʃənl ɪˈfɪʃnsi/ | hiệu quả hoạt động | enhance operational efficiency | improve operational efficiency |
| Internet of Things (IoT) | n | /ˈɪntənet əv θɪŋz/ | Internet vạn vật | driven by advances in IoT | IoT sensors, IoT devices |
| reallocate | v | /ˌriːˈæləkeɪt/ | phân bổ lại | allows hotels to reallocate staff | reallocate resources, reallocate budget |
| concierge service | n | /ˌkɒnsiˈeəʒ ˈsɜːvɪs/ | dịch vụ hỗ trợ khách hàng | such as concierge services or guest relations | provide concierge service |
| predominantly | adv | /prɪˈdɒmɪnəntli/ | chủ yếu, phần lớn | a staff composed predominantly of robots | predominantly used, predominantly male |
| multilingual | adj | /ˌmʌltiˈlɪŋɡwəl/ | đa ngôn ngữ | multilingual robot receptionists | multilingual staff, multilingual support |
| overcome | v | /ˌəʊvəˈkʌm/ | vượt qua, khắc phục | overcome language barriers | overcome challenges, overcome difficulties |
| high-profile | adj | /haɪ ˈprəʊfaɪl/ | nổi tiếng, được chú ý nhiều | This high-profile setback | high-profile case, high-profile event |
| coordinate | v | /kəʊˈɔːdɪneɪt/ | phối hợp, điều phối | central system that coordinates orders | coordinate activities, coordinate efforts |
| customise | v | /ˈkʌstəmaɪz/ | tùy chỉnh theo yêu cầu | allow customers to customise orders | customise settings, fully customisable |
| back-end operation | n | /bæk end ˌɒpəˈreɪʃn/ | hoạt động hậu cần | back-end operations of hospitality businesses | manage back-end operations |
| predictive maintenance | n | /prɪˈdɪktɪv ˈmeɪntənəns/ | bảo trì dự đoán | Predictive maintenance systems use data | implement predictive maintenance |
| revenue management | n | /ˈrevənjuː ˈmænɪdʒmənt/ | quản lý doanh thu | Revenue management has been revolutionised | revenue management strategy |
| dynamically | adv | /daɪˈnæmɪkli/ | một cách linh hoạt, năng động | dynamically adjust room rates in real-time | dynamically change, dynamically respond |
Đối với những ai quan tâm đến ảnh hưởng rộng hơn của công nghệ, chủ đề How does the global food industry contribute to climate change? cũng thể hiện mối liên hệ giữa các ngành công nghiệp toàn cầu và thách thức hiện đại.
Passage 3 – Essential Vocabulary
| Từ vựng | Loại từ | Phiên âm | Nghĩa tiếng Việt | Ví dụ từ bài | Collocation |
|---|---|---|---|---|---|
| inexorable | adj | /ɪnˈeksərəbl/ | không thể ngăn cản, tất yếu | The inexorable march of automation | inexorable rise, inexorable decline |
| fundamental restructuring | n | /ˌfʌndəˈmentl ˌriːˈstrʌktʃərɪŋ/ | tái cấu trúc cơ bản | constitutes a fundamental restructuring | undergo fundamental restructuring |
| profound implication | n | /prəˈfaʊnd ˌɪmplɪˈkeɪʃn/ | hệ quả sâu xa | profound implications for labour markets | have profound implications |
| supplant | v | /səˈplɑːnt/ | thay thế, chiếm chỗ | AI increasingly supplant human workers | supplant traditional methods |
| grapple with | v | /ˈɡræpl wɪð/ | vật lộn với, đối phó với | workers must grapple with the complex ramifications | grapple with challenges |
| unprecedented | adj | /ʌnˈpresɪdentɪd/ | chưa từng có tiền lệ | this unprecedented transformation | unprecedented scale, unprecedented crisis |
| displacement | n | /dɪsˈpleɪsmənt/ | sự thay thế, di dời | The scale of potential displacement is staggering | job displacement, workforce displacement |
| redeployed | v | /ˌriːdɪˈplɔɪd/ | được triển khai lại | workers may be redeployed to other responsibilities | redeploy staff, redeploy resources |
| distributional impact | n | /ˌdɪstrɪˈbjuːʃənl ˈɪmpækt/ | tác động phân phối | The distributional impact will be far from uniform | assess distributional impact |
| disproportionate | adj | /ˌdɪsprəˈpɔːʃənət/ | không cân đối, không tương xứng | with lower-skilled positions facing disproportionate vulnerability | disproportionate effect, disproportionate impact |
| invoke | v | /ɪnˈvəʊk/ | viện dẫn, gợi lên | Optimists invoke historical precedent | invoke authority, invoke tradition |
| augment | v | /ɔːɡˈment/ | tăng cường, bổ sung | innovations that primarily augmented human capabilities | augment capabilities, augment income |
| affective computing | n | /əˈfektɪv kəmˈpjuːtɪŋ/ | công nghệ tính toán cảm xúc | affective computing enable machines to engage | develop affective computing |
| outstrip | v | /ˌaʊtˈstrɪp/ | vượt qua, bỏ xa | rapid pace may outstrip the capacity of educational systems | outstrip demand, outstrip supply |
| protracted period | n | /prəˈtræktɪd ˈpɪəriəd/ | giai đoạn kéo dài | creating a protracted period of structural unemployment | protracted period of time |
| nuanced | adj | /ˈnjuːɑːnst/ | tinh tế, nhiều sắc thái | empirical evidence presents a nuanced picture | nuanced understanding, nuanced approach |
| longitudinal data | n | /ˌlɒndʒɪˈtjuːdɪnl ˈdeɪtə/ | dữ liệu theo thời gian | longitudinal data from early adopters | collect longitudinal data |
| proactive strategy | n | /prəʊˈæktɪv ˈstrætədʒi/ | chiến lược chủ động | adopted proactive strategies | implement proactive strategy |
| laissez-faire | adj | /ˌleseɪ ˈfeə(r)/ | tự do, không can thiệp | taken more laissez-faire approaches | laissez-faire approach, laissez-faire policy |
| universal basic income | n | /ˌjuːnɪvɜːsl ˌbeɪsɪk ˈɪnkʌm/ | thu nhập cơ bản toàn dân | Proposals such as universal basic income | implement universal basic income |
Bảng từ vựng quan trọng trong IELTS Reading chủ đề tự động hóa du lịch
Kết Bài
Chủ đề “The rise of automation in the travel industry” không chỉ là một xu hướng công nghệ mà còn phản ánh sự thay đổi sâu sắc trong cách con người làm việc, du lịch và tương tác với dịch vụ. Qua bộ đề thi IELTS Reading này, bạn đã được tiếp cận với ba perspectives khác nhau về tự động hóa: từ những tiện ích cơ bản trong việc đặt vé và check-in (Passage 1), đến ứng dụng thực tế của robot và AI trong khách sạn (Passage 2), và cuối cùng là những tác động kinh tế-xã hội sâu rộng đối với lực lượng lao động toàn cầu (Passage 3).
Ba passages này đã được thiết kế với độ khó tăng dần từ band 5.0 đến 9.0, giúp bạn làm quen với các dạng câu hỏi đa dạng và phát triển kỹ năng đọc hiểu từ cơ bản đến nâng cao. Đáp án chi tiết kèm giải thích không chỉ cho bạn biết câu trả lời đúng mà còn hướng dẫn cách xác định thông tin, nhận biết paraphrase và áp dụng chiến lược làm bài hiệu quả.
Phần từ vựng được tổng hợp từ ba passages cung cấp cho bạn hơn 40 từ và cụm từ quan trọng liên quan đến công nghệ, du lịch và kinh tế. Những từ vựng này không chỉ hữu ích cho bài thi Reading mà còn có thể áp dụng trong Writing Task 2 và Speaking Part 3 khi thảo luận về các chủ đề liên quan đến công nghệ và xã hội.
Để đạt kết quả tốt trong IELTS Reading, hãy thường xuyên luyện tập với các đề thi mẫu như thế này, phân tích kỹ cách câu hỏi được paraphrase từ nội dung bài đọc, và xây dựng vốn từ vựng học thuật phong phú. Hãy nhớ rằng việc hiểu sâu về cấu trúc câu hỏi và phương pháp tìm thông tin quan trọng hơn việc chỉ biết từ vựng. Chúc bạn ôn tập hiệu quả và đạt band điểm mong muốn trong kỳ thi IELTS sắp tới.
