Trong bối cảnh công nghệ số phát triển vượt bậc, các bảo tàng trên toàn thế giới đang trải qua cuộc cách mạng chưa từng có. Chủ đề “Museums In The Digital Era Future” không chỉ phản ánh xu hướng toàn cầu mà còn là một trong những đề tài thường xuyên xuất hiện trong IELTS Reading, đặc biệt trong các phần thi từ năm 2018 đến nay. Bài viết này cung cấp một bộ đề thi hoàn chỉnh với 3 passages từ dễ đến khó, giúp bạn làm quen với cấu trúc câu hỏi đa dạng và nâng cao kỹ năng làm bài. Bạn sẽ được luyện tập với 40 câu hỏi theo đúng format thi thật, kèm theo đáp án chi tiết và giải thích cặn kẽ từng câu. Đặc biệt, bộ đề này còn cung cấp từ vựng học thuật quan trọng và các kỹ thuật scanning, skimming hiệu quả. Dành cho học viên từ band 5.0 trở lên, bộ đề này là công cụ lý tưởng để bạn tự đánh giá năng lực và chuẩn bị tốt nhất cho kỳ thi IELTS sắp tới.
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 là 1 điểm, không có điểm âm cho câu trả lời sai. Việc phân bổ thời gian hợp lý là chìa khóa để hoàn thành toàn bộ bài thi.
Phân bổ thời gian khuyến nghị:
- Passage 1 (Easy): 15-17 phút
- Passage 2 (Medium): 18-20 phút
- Passage 3 (Hard): 23-25 phút
- Thời gian chuyển đáp án: 2-3 phút
Lưu ý rằng không có thời gian bổ sung để chuyển đáp án vào answer sheet như phần Listening, vì vậy bạn nên viết đáp án trực tiếp vào phiếu trả lời trong khi làm bài.
Các Dạng Câu Hỏi Trong Đề Này
Bộ đề thi này bao gồm 7 dạng câu hỏi phổ biến nhất trong IELTS Reading:
- Multiple Choice – Câu hỏi trắc nghiệm nhiều lựa chọn
- True/False/Not Given – Xác định thông tin đúng/sai/không được nhắc đến
- Matching Information – Nối thông tin với đoạn văn tương ứng
- Sentence Completion – Hoàn thành câu
- Matching Headings – Nối tiêu đề với đoạn văn
- 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 tìm kiếm thông tin chi tiết đến hiểu ý chính và suy luận.
Hướng dẫn phân bổ thời gian hiệu quả cho bài thi IELTS Reading 3 passages
IELTS Reading Practice Test
PASSAGE 1 – The Digital Transformation of Museums
Độ khó: Easy (Band 5.0-6.5)
Thời gian đề xuất: 15-17 phút
Museums have long been regarded as custodians of cultural heritage, preserving artifacts and artworks for future generations. However, the advent of digital technology has fundamentally transformed how these institutions operate and engage with their audiences. This digital revolution is not merely about adding computers to museum spaces; it represents a complete reimagining of what museums can be and how they fulfill their educational mission.
The shift towards digitalization began in earnest in the early 2000s, when museums started to digitize their collections. This process involves creating high-resolution digital images of physical objects, along with detailed metadata describing each item’s history, materials, and significance. Major institutions like the British Museum and the Smithsonian have invested millions of dollars in these projects, making hundreds of thousands of objects accessible online. This democratization of access means that a student in rural Vietnam can now examine ancient Egyptian artifacts with the same clarity as a visitor standing in the museum’s gallery.
Virtual tours have become increasingly sophisticated, offering immersive experiences that go beyond simple photograph galleries. Using 360-degree photography and virtual reality (VR) technology, museums can transport users into their spaces without requiring physical presence. The Louvre in Paris, for instance, offers virtual tours that allow visitors to “walk” through its iconic galleries, examining paintings in detail and accessing information about each artwork through clickable hotspots. These digital experiences have proven particularly valuable during the COVID-19 pandemic, when physical museums were forced to close their doors for extended periods.
Interactive displays within physical museum spaces represent another dimension of digital transformation. Touchscreen interfaces, augmented reality (AR) applications, and motion sensors create engaging experiences that appeal especially to younger visitors. At the Natural History Museum in London, visitors can use tablets to see how dinosaurs would have moved and sounded in their natural habitats. This gamification of learning makes complex scientific concepts more accessible and memorable, particularly for children who might otherwise find traditional museum exhibits boring.
Social media has fundamentally changed how museums communicate with their audiences. Platforms like Instagram, Twitter, and TikTok enable institutions to share their collections in creative ways, reaching demographics that might never visit a physical museum. The Rijksmuseum in Amsterdam gained international attention through its innovative social media campaigns, which presented classical artworks in contemporary contexts. This two-way communication allows museums to receive instant feedback, understand audience preferences, and tailor their programming accordingly.
Digital archiving serves purposes beyond public engagement; it also provides crucial backup systems for preserving cultural heritage. Natural disasters, wars, and accidents can destroy irreplaceable artifacts, but digital copies ensure that knowledge about these objects survives. When fire devastated Brazil’s National Museum in 2018, destroying 20 million items, the digital records that existed became invaluable resources for understanding what was lost and potentially reconstructing some pieces.
However, this digital transformation presents significant challenges. The initial costs of digitization projects can be prohibitively expensive, particularly for smaller institutions with limited budgets. A single high-quality 3D scan of a sculpture can cost thousands of dollars, and museums may have thousands or millions of objects in their collections. There are also questions about digital preservation itself – as technology evolves, file formats become obsolete, requiring ongoing investment to ensure digital archives remain accessible.
Copyright and intellectual property issues add further complexity. Many museum collections include contemporary artworks or photographs that remain under copyright protection. Making these items available online requires negotiating permissions with artists, estates, or other rights holders, which can be time-consuming and expensive. Some artists oppose digital reproduction of their works, believing it diminishes the importance of experiencing art in person.
Despite these challenges, most experts agree that the digital transformation of museums is both inevitable and beneficial. The key lies in finding the right balance between digital innovation and the traditional museum experience. As museum director Maria Lopez notes, “Digital tools should enhance, not replace, the profound experience of standing before a real artifact or artwork.” When implemented thoughtfully, digital technologies can help museums fulfill their fundamental mission more effectively than ever before: educating the public and preserving cultural heritage for future generations.
Museums that successfully navigate this transformation will be those that view digital technology not as a threat to their traditional role but as a powerful tool for extending their reach and impact. The future museum will likely be a hybrid institution, maintaining physical spaces for those who can visit while simultaneously offering rich digital experiences that break down geographical and economic barriers to access. In this way, digital transformation may help museums become more relevant and accessible to the 21st-century public.
Questions 1-13
Questions 1-5: Multiple Choice
Choose the correct letter, A, B, C or D.
-
According to the passage, digital transformation in museums is best described as:
A. simply adding computers to existing spaces
B. a complete rethinking of museums’ purpose and methods
C. a temporary trend that will soon pass
D. only relevant for large institutions -
The digitization of museum collections in the early 2000s primarily involved:
A. creating virtual reality experiences
B. developing social media campaigns
C. producing digital images and detailed information about objects
D. building interactive displays for visitors -
During the COVID-19 pandemic, virtual tours proved to be:
A. less popular than expected
B. too expensive to maintain
C. particularly important when physical museums closed
D. only suitable for younger audiences -
Interactive displays in museums using digital technology are especially effective for:
A. adult researchers
B. museum staff
C. preservation purposes
D. engaging younger visitors -
The fire at Brazil’s National Museum in 2018 demonstrated that:
A. digital archives are unnecessary
B. digital records help preserve knowledge about destroyed items
C. all museums should close their physical spaces
D. digitization is too expensive
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
- The British Museum and the Smithsonian have made their entire collections available online.
- Virtual reality technology allows users to feel like they are physically present in museum spaces.
- All artists support the digital reproduction of their artworks.
- Museums charge visitors extra fees to access digital archives.
Questions 10-13: Sentence Completion
Complete the sentences below.
Choose NO MORE THAN TWO WORDS from the passage for each answer.
-
Social media platforms enable museums to engage in __ with their audiences, receiving immediate responses.
-
The initial costs of digitization can be __ for smaller museums with limited funding.
-
As technology changes, older __ may become outdated, requiring continued investment.
-
According to Maria Lopez, digital tools should __ rather than substitute the experience of viewing real objects.
PASSAGE 2 – Curating Digital Experiences: The New Museum Professional
Độ khó: Medium (Band 6.0-7.5)
Thời gian đề xuất: 18-20 phút
The proliferation of digital technologies in museums has given rise to an entirely new category of museum professional: the digital curator. Unlike traditional curators, whose expertise lies primarily in art-historical knowledge or scientific specialization, digital curators must possess a hybrid skill set that combines domain expertise with technical proficiency and an understanding of user experience design. This emerging role exemplifies how the digital transformation of museums extends far beyond simply installing new equipment; it requires fundamental changes to institutional structures, professional training, and curatorial practices.
A. The Evolution of Curatorial Work
Traditional curating involved selecting, researching, and interpreting objects for physical display. The curator’s primary responsibilities included authenticating artifacts, developing exhibition narratives, and writing interpretive labels and catalogue entries. These activities required deep scholarly knowledge but relatively little technical expertise. The digital age has exponentially expanded these responsibilities. Contemporary curators must now consider how objects will appear across multiple platforms – not just in gallery spaces but on museum websites, social media, virtual reality experiences, and mobile applications.
B. Technical Competencies
The technical demands placed upon digital curators are substantial. They must understand database management systems for cataloguing collections, content management systems for websites, and the principles of 3D scanning and photogrammetry. Many museums now expect curators to be conversant with HTML, CSS, and basic programming concepts, even if they don’t write code themselves. This technical literacy enables curators to communicate effectively with IT professionals and make informed decisions about digital projects. As Sarah Chen, Digital Curator at the Metropolitan Museum of Art, explains: “I don’t need to be a programmer, but I do need to understand what’s possible, what’s difficult, and what’s simply not feasible with current technology.”
C. Understanding User Experience
Perhaps the most radical departure from traditional curating involves the emphasis on user experience (UX). Physical museum exhibitions have always considered visitor experience to some degree, but digital platforms generate quantitative data about user behavior that was previously unavailable. Digital curators can see exactly which artworks receive the most attention online, how long users spend on different pages, and where they abandon virtual tours. This data-driven approach to curating represents a paradigm shift. Rather than relying solely on curatorial judgment about what should be important or interesting, digital curators must reconcile their expertise with empirical evidence about what actually engages audiences.
D. Balancing Accessibility and Scholarship
One particularly vexing challenge for digital curators involves finding the appropriate balance between accessibility and scholarly rigor. Digital platforms can reach extraordinarily diverse audiences, from school children to specialized researchers. Creating content that serves all these constituencies simultaneously is exceptionally difficult. Some museums have addressed this by developing tiered content systems, offering basic information for general audiences while providing deeper scholarly resources for those who want them. The Victoria and Albert Museum’s website, for instance, includes brief introductory texts alongside extensive research articles and high-resolution images suitable for academic study.
E. Collaborative Approaches
Digital curation is inherently collaborative in ways that traditional curating often was not. Developing a digital exhibition typically requires input from designers, programmers, educators, marketing specialists, and accessibility experts, in addition to curators with subject matter expertise. This multidisciplinary teamwork can be challenging for curators trained in traditional academic environments that emphasize individual scholarship. Successful digital curators must develop interpersonal skills and project management abilities alongside their scholarly expertise. They must learn to articulate curatorial goals to non-specialists and remain receptive to suggestions from team members whose backgrounds differ from their own.
F. Ethical Considerations
The digital realm introduces ethical complexities that curators must navigate carefully. Questions about cultural sensitivity become more pressing when materials are accessible globally. An object displayed in a Western museum might be viewed quite differently by members of the culture that created it, particularly when that object has sacred significance or was obtained through colonial appropriation. Digital curators must consider whether certain objects should be displayed online at all, and if so, how to contextualize them appropriately. Some museums have begun consulting with descendant communities before digitizing culturally sensitive materials, though such consultation requires time and resources that institutions don’t always possess.
G. Professional Training and Development
Museum studies programs have struggled to keep pace with these evolving requirements. Many graduate programs still focus primarily on traditional curatorial skills, offering only limited training in digital technologies. This has created a talent gap, with museums seeking professionals who possess skills that formal education programs don’t consistently provide. In response, some institutions have developed in-house training programs or established partnerships with technology companies. The Guggenheim Museum’s Digital Innovation Fellowship, for example, provides intensive training in digital methods for early-career curators.
The emergence of digital curating represents more than simply a new job category; it signals a fundamental reconceptualization of what museums are and how they function. As museums continue to navigate the digital transformation, the role of the digital curator will likely continue evolving. Those who can successfully bridge the traditional and digital worlds – maintaining scholarly rigor while embracing new technologies and audience-centered approaches – will shape how future generations experience and understand cultural heritage. The most successful institutions will be those that recognize digital curating not as a peripheral specialty but as central to the museum’s core mission in the 21st century.
Questions 14-26
Questions 14-18: Matching Headings
The passage has seven paragraphs labeled A-G.
Choose the correct heading for each paragraph from the list of headings below.
Write the correct number, i-x.
List of Headings:
i. The challenge of serving multiple audience types
ii. Working in multidisciplinary teams
iii. Changes to traditional curatorial responsibilities
iv. Financial constraints on digital projects
v. Required technological skills for modern curators
vi. Respecting cultural values in digital contexts
v. Inadequate preparation for digital roles
vii. Using data to inform curatorial decisions
viii. The history of museum technology
ix. Visitor preferences for physical museums
x. International collaboration between museums
- Paragraph A
- Paragraph B
- Paragraph C
- Paragraph D
- Paragraph E
Questions 19-22: 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
- Digital curators need to be expert programmers who can write complex code.
- Data about online user behavior has fundamentally changed how museums approach curation.
- All museums should consult with descendant communities before digitizing any artifacts.
- Museum studies programs have successfully adapted to prepare students for digital curating roles.
Questions 23-26: Summary Completion
Complete the summary below.
Choose NO MORE THAN TWO WORDS from the passage for each answer.
Digital curating requires a combination of traditional knowledge and new technical skills. Modern curators must understand various systems including those for managing (23) __ and websites. They also need to focus on (24) __, using quantitative information about how people interact with digital platforms. Creating digital content is challenging because museums must serve (25) __, from children to scholars. Additionally, digital curators must address (26) __ when displaying materials online, particularly regarding objects with sacred or cultural importance.
PASSAGE 3 – Museums and Artificial Intelligence: Promises and Perils of Machine Learning
Độ khó: Hard (Band 7.0-9.0)
Thời gian đề xuất: 23-25 phút
The integration of artificial intelligence (AI) into museum operations represents perhaps the most transformative yet contentious development in the ongoing digitalization of cultural institutions. While earlier digital innovations – databases, virtual tours, social media engagement – extended existing practices into new mediums, AI technologies possess the potential to fundamentally reconfigure core museum functions, from cataloguing collections to interpreting artworks. This prospect simultaneously excites and alarms museum professionals, raising profound questions about automation, expertise, algorithmic bias, and the very nature of curatorial judgment.
Machine learning algorithms have demonstrated remarkable capabilities in pattern recognition tasks that previously required extensive human expertise. In 2019, researchers at Rutgers University developed an AI system capable of identifying the artistic style of paintings with greater accuracy than many human art historians. The algorithm, trained on thousands of digitized artworks, learned to recognize subtle stylistic signatures – brushwork patterns, color palettes, compositional elements – that characterize different artists and art movements. When presented with previously unseen paintings, the system could attribute them to the correct artist or school with approximately 80% accuracy, a success rate comparable to specialists in the field.
Such capabilities offer tantalizing possibilities for museums struggling with vast unattributed or misattributed collections. The Metropolitan Museum of Art estimates that approximately 30% of its European paintings lack definitive attributions – they are categorized as “school of” or “attributed to” rather than confidently assigned to specific artists. AI systems could potentially resolve thousands of these attributional uncertainties, enhancing scholarly knowledge and increasing the value of museum holdings. Moreover, these systems could identify previously unrecognized connections between artworks, revealing stylistic influences and historical relationships that human researchers might overlook.
However, the epistemic status of AI-generated attributions remains philosophically problematic. When a human expert attributes a painting to a particular artist, that judgment rests on a complex interplay of visual analysis, historical documentation, technical examination, and intuitive expertise developed through years of experience. The expert can explain their reasoning, cite supporting evidence, and engage in scholarly debate about contested attributions. In contrast, deep learning algorithms operate as “black boxes” – even their creators often cannot fully explain why the system reached a particular conclusion. The algorithm identifies patterns in training data, but these patterns may not correspond to the art-historical criteria that scholars consider meaningful.
This opacity becomes particularly troubling when AI systems perpetuate or amplify existing biases in museum collections and scholarship. Museum holdings have historically over-represented Western, male artists while marginalizing works by women, non-Western artists, and indigenous creators. When AI algorithms train on these skewed datasets, they risk encoding these biases into their decision-making processes. An AI trained primarily on European paintings might systematically undervalue or miscategorize non-Western artworks, reinforcing the very inequities that contemporary museums are attempting to address. As Dr. Miriam Kim, a researcher in algorithmic fairness, argues: “AI doesn’t eliminate human bias; it automates and obscures it, making biased judgments appear objective and scientific rather than reflecting the subjective preferences of those who created the training data.”
Beyond attribution, AI technologies promise to revolutionize how museums engage with visitors. Natural language processing enables AI chatbots to answer visitor questions, provide personalized recommendations, and offer interpretive information in multiple languages. Computer vision systems can identify objects that visitors photograph, automatically providing relevant information. The Cleveland Museum of Art’s ArtLens Exhibition uses facial recognition technology to match visitors with artworks featuring people whose facial structures resemble theirs, creating affective connections between visitors and historical art.
Yet these engagement technologies raise significant privacy concerns. Facial recognition systems, while creating engaging experiences, also collect biometric data that could potentially be used for surveillance purposes. Even anonymized data about visitor movements and interests creates digital profiles that reveal sensitive information about cultural preferences, political leanings, and personal identities. Museums have traditionally been spaces of intellectual freedom where individuals can explore ideas without fear of monitoring or judgment; ubiquitous data collection threatens this sanctuary function.
The deployment of AI for conservation and restoration introduces yet another dimension of complexity. Machine learning algorithms can analyze degraded artworks and generate hypothetical reconstructions of their original appearance. When fire damaged paintings at the Glasgow School of Art in 2018, researchers used AI to produce digital reconstructions based on photographs and descriptions. While such reconstructions provide valuable scholarly information, they also risk creating authoritative-seeming versions of artworks that are, ultimately, algorithmic speculations rather than historical facts. Museums must clearly distinguish between authentic objects and AI-generated approximations, a distinction that may blur in public understanding as digital reconstructions become increasingly sophisticated.
Furthermore, the substantial computational resources required for AI systems have environmental ramifications that contradict many museums’ sustainability commitments. Training a single large AI model can generate carbon emissions equivalent to the lifetime emissions of five automobiles. As museums incorporate increasingly sophisticated AI systems – for collection management, visitor engagement, climate control optimization, and other purposes – their carbon footprints expand significantly. The ethical imperative to preserve cultural heritage for future generations must be balanced against the environmental costs of the technologies used in that preservation.
Perhaps most fundamentally, the integration of AI into museums forces reconsideration of core institutional values. Museums have traditionally positioned themselves as sources of authoritative knowledge, with curators serving as trusted interpreters of cultural objects. AI systems complicate this authority, offering alternative interpretations generated through processes that even experts cannot fully explain or verify. Some theorists argue this epistemic disruption is ultimately beneficial, democratizing expertise and challenging the hierarchical knowledge structures that museums have historically embodied. Others worry that replacing human expertise with algorithmic judgment will impoverish the nuanced, contextual understanding that makes museum experiences meaningful.
The path forward requires neither wholesale embrace nor complete rejection of AI technologies, but rather critical, thoughtful integration that prioritizes human values over technological possibilities. Museums must maintain transparency about when and how they use AI systems, clearly communicating both the capabilities and limitations of these technologies. They should implement robust safeguards against algorithmic bias, regularly auditing AI systems for discriminatory outputs and ensuring diverse perspectives inform technology development. Most crucially, museums must insist that AI serves as a tool to augment rather than replace human expertise, judgment, and the essentially human activity of making meaning from cultural objects.
As museum director James Rodriguez observes: “Technology should never drive the mission; the mission should drive the technology. Our purpose is to connect people with cultural heritage in meaningful ways. AI can help us achieve that purpose, but only if we remain constantly vigilant about the values we’re encoding into these systems.” The museums that successfully navigate the AI revolution will be those that harness these powerful technologies while remaining steadfast in their commitment to equity, transparency, and the fundamentally human work of preserving and interpreting culture.
Công nghệ trí tuệ nhân tạo và machine learning trong bảo tàng thời đại số
Questions 27-40
Questions 27-31: Multiple Choice
Choose the correct letter, A, B, C or D.
-
According to the passage, the Rutgers University AI system for identifying artistic styles:
A. performs better than all human art historians
B. achieves around 80% accuracy, similar to human specialists
C. can only recognize modern artworks
D. requires human supervision for every decision -
The main problem with AI attributions, according to the passage, is that:
A. they are always incorrect
B. they cost too much money
C. the reasoning behind them cannot be fully explained
D. they take longer than human analysis -
When AI algorithms are trained on museum collections, they risk:
A. destroying physical artworks
B. reinforcing historical biases in the data
C. making museums less popular
D. replacing all museum staff -
The Cleveland Museum of Art’s facial recognition system:
A. is used for security purposes
B. matches visitors with similar-looking artworks
C. has been rejected by visitors
D. only works with contemporary art -
The passage suggests that training large AI models:
A. has no environmental impact
B. is cheaper than traditional methods
C. generates significant carbon emissions
D. is required by law for all museums
Questions 32-36: Matching Features
Match each researcher or museum professional (A-E) with their correct statement or view (32-36).
Write the correct letter, A-E.
List of People:
A. Dr. Miriam Kim
B. Sarah Chen
C. Maria Lopez
D. James Rodriguez
E. Not attributed to anyone specifically
- Technology should support museum missions rather than determining them
- Digital tools should complement rather than replace experiencing real objects
- Curators need to understand technological possibilities without being programmers
- AI doesn’t eliminate bias but makes it appear objective
- Museums need to clearly distinguish authentic objects from AI reconstructions
Questions 37-40: Short-answer Questions
Answer the questions below.
Choose NO MORE THAN THREE WORDS from the passage for each answer.
-
What percentage of the Metropolitan Museum’s European paintings lack definitive attributions?
-
What term describes how deep learning algorithms function, making their reasoning difficult to understand?
-
What type of data do facial recognition systems collect that raises privacy concerns?
-
What must museums regularly conduct on AI systems to check for discriminatory outputs?
Answer Keys – Đáp Án
PASSAGE 1: Questions 1-13
- B
- C
- C
- D
- B
- NOT GIVEN
- TRUE
- FALSE
- NOT GIVEN
- two-way communication
- prohibitively expensive
- file formats
- enhance
PASSAGE 2: Questions 14-26
- iii
- v
- vii
- i
- ii
- NO
- YES
- NOT GIVEN
- NO
- database(s)
- user experience / UX
- diverse audiences
- ethical complexities / ethical considerations
PASSAGE 3: Questions 27-40
- B
- C
- B
- B
- C
- D
- C
- B
- A
- E
- 30% / thirty percent / approximately 30%
- black boxes
- biometric data
- auditing / audit
Giải Thích Đáp Án Chi Tiết
Passage 1 – Giải Thích
Câu 1: B
- Dạng câu hỏi: Multiple Choice
- Từ khóa: digital transformation, museums, best described
- Vị trí trong bài: Đoạn 1, dòng 3-4
- Giải thích: Bài đọc nói rõ “This digital revolution is not merely about adding computers to museum spaces; it represents a complete reimagining of what museums can be” – điều này tương ứng với đáp án B về việc suy nghĩ lại hoàn toàn về mục đích và phương pháp của bảo tàng. Đáp án A bị loại vì bài viết chỉ rõ đây không chỉ đơn giản là thêm máy tính.
Câu 2: C
- Dạng câu hỏi: Multiple Choice
- Từ khóa: digitization, early 2000s, primarily involved
- Vị trí trong bài: Đoạn 2, dòng 1-3
- Giải thích: Đoạn văn mô tả “This process involves creating high-resolution digital images of physical objects, along with detailed metadata describing each item’s history” – khớp chính xác với đáp án C.
Câu 3: C
- Dạng câu hỏi: Multiple Choice
- Từ khóa: COVID-19 pandemic, virtual tours
- Vị trí trong bài: Đoạn 3, dòng 6-7
- Giải thích: Bài viết nêu “These digital experiences have proven particularly valuable during the COVID-19 pandemic, when physical museums were forced to close” – chứng tỏ virtual tours đặc biệt quan trọng khi bảo tàng vật lý đóng cửa.
Câu 6: NOT GIVEN
- Dạng câu hỏi: True/False/Not Given
- Từ khóa: British Museum, Smithsonian, entire collections online
- Vị trí trong bài: Đoạn 2
- Giải thích: Bài viết chỉ nói họ “making hundreds of thousands of objects accessible online” nhưng không xác nhận toàn bộ bộ sưu tập đã được số hóa. Không có đủ thông tin để xác định đúng hay sai.
Câu 8: FALSE
- Dạng câu hỏi: True/False/Not Given
- Từ khóa: all artists, support digital reproduction
- Vị trí trong bài: Đoạn 8, dòng cuối
- Giải thích: Bài viết nói rõ “Some artists oppose digital reproduction of their works” – chứng tỏ không phải tất cả nghệ sĩ đều ủng hộ, do đó câu này là FALSE.
Câu 10: two-way communication
- Dạng câu hỏi: Sentence Completion
- Từ khóa: social media, engage, audiences, immediate responses
- Vị trí trong bài: Đoạn 5, dòng 3-4
- Giải thích: Đoạn văn sử dụng chính xác cụm “two-way communication” để mô tả cách mạng xã hội cho phép tương tác hai chiều với khán giả.
Passage 2 – Giải Thích
Câu 14: iii
- Dạng câu hỏi: Matching Headings
- Từ khóa: evolution, curatorial work, responsibilities
- Vị trí trong bài: Đoạn A
- Giải thích: Đoạn A thảo luận về cách công việc quản lý bảo tàng truyền thống đã thay đổi, với tiêu đề “The Evolution of Curatorial Work” và mô tả các trách nhiệm mới. Heading iii “Changes to traditional curatorial responsibilities” phù hợp nhất.
Câu 15: v
- Dạng câu hỏi: Matching Headings
- Từ khóa: technical demands, database management, programming
- Vị trí trong bài: Đoạn B
- Giải thích: Toàn bộ đoạn B tập trung vào các kỹ năng công nghệ cần thiết như database management, 3D scanning, HTML, CSS. Heading v “Required technological skills for modern curators” mô tả chính xác nội dung này.
Câu 19: NO
- Dạng câu hỏi: Yes/No/Not Given
- Từ khóa: digital curators, expert programmers, complex code
- Vị trí trong bài: Đoạn B, trích dẫn Sarah Chen
- Giải thích: Sarah Chen nói rõ “I don’t need to be a programmer” – điều này trái ngược với ý kiến trong câu hỏi, do đó đáp án là NO.
Câu 20: YES
- Dạng câu hỏi: Yes/No/Not Given
- Từ khóa: data, user behavior, fundamentally changed, curation
- Vị trí trong bài: Đoạn C
- Giải thích: Đoạn C nói “This data-driven approach to curating represents a paradigm shift” – rõ ràng cho thấy tác giả đồng ý rằng dữ liệu đã thay đổi căn bản cách tiếp cận quản lý bảo tàng.
Câu 23: database(s)
- Dạng câu hỏi: Summary Completion
- Từ khóa: managing, websites, systems
- Vị trí trong bài: Đoạn B, dòng 2-3
- Giải thích: Bài viết đề cập “database management systems for cataloguing collections” – từ “database(s)” phù hợp với ngữ cảnh về các hệ thống quản lý.
Câu 24: user experience
- Dạng câu hỏi: Summary Completion
- Từ khóa: focus on, quantitative information, interact
- Vị trí trong bài: Đoạn C
- Giải thích: Đoạn C nhấn mạnh “emphasis on user experience (UX)” và việc sử dụng dữ liệu định lượng về hành vi người dùng.
Passage 3 – Giải Thích
Câu 27: B
- Dạng câu hỏi: Multiple Choice
- Từ khóa: Rutgers University, AI system, accuracy
- Vị trí trong bài: Đoạn 2, dòng 5-6
- Giải thích: Bài viết nói “the system could attribute them to the correct artist or school with approximately 80% accuracy, a success rate comparable to specialists in the field” – khớp chính xác với đáp án B.
Câu 28: C
- Dạng câu hỏi: Multiple Choice
- Từ khóa: main problem, AI attributions
- Vị trí trong bài: Đoạn 4
- Giải thích: Đoạn 4 giải thích vấn đề chính: “deep learning algorithms operate as ‘black boxes’ – even their creators often cannot fully explain why the system reached a particular conclusion” – tương ứng với đáp án C về việc không thể giải thích đầy đủ lý do.
Câu 29: B
- Dạng câu hỏi: Multiple Choice
- Từ khóa: AI algorithms, trained, museum collections, risk
- Vị trí trong bài: Đoạn 5
- Giải thích: Đoạn 5 nêu rõ “When AI algorithms train on these skewed datasets, they risk encoding these biases into their decision-making processes” – đáp án B về việc củng cố các thiên kiến lịch sử.
Câu 32: D (James Rodriguez)
- Dạng câu hỏi: Matching Features
- Vị trí trong bài: Đoạn cuối, trích dẫn trực tiếp
- Giải thích: James Rodriguez nói “Technology should never drive the mission; the mission should drive the technology” – tương ứng với ý “Technology should support museum missions”.
Câu 35: A (Dr. Miriam Kim)
- Dạng câu hỏi: Matching Features
- Vị trí trong bài: Đoạn 5, trích dẫn
- Giải thích: Dr. Kim nói “AI doesn’t eliminate human bias; it automates and obscures it, making biased judgments appear objective” – khớp chính xác với câu 35.
Câu 37: 30% / thirty percent
- Dạng câu hỏi: Short-answer Questions
- Từ khóa: Metropolitan Museum, European paintings, lack attributions
- Vị trí trong bài: Đoạn 3, dòng 2-3
- Giải thích: Bài viết nêu rõ “The Metropolitan Museum of Art estimates that approximately 30% of its European paintings lack definitive attributions”.
Câu 38: black boxes
- Dạng câu hỏi: Short-answer Questions
- Từ khóa: deep learning algorithms, function, reasoning difficult
- Vị trí trong bài: Đoạn 4
- Giải thích: Thuật ngữ “black boxes” được sử dụng để mô tả cách hoạt động không minh bạch của các thuật toán deep learning.
Câu 40: auditing / audit
- Dạng câu hỏi: Short-answer Questions
- Từ khóa: museums, regularly conduct, AI systems, discriminatory outputs
- Vị trí trong bài: Đoạn gần cuối
- Giải thích: Bài viết đề xuất “regularly auditing AI systems for discriminatory outputs” – từ “auditing” hoặc “audit” phù hợp với ngữ cảnh.
Từ Vựng Quan Trọng Theo Passage
Passage 1 – Essential Vocabulary
| Từ vựng | Loại từ | Phiên âm | Nghĩa tiếng Việt | Ví dụ từ bài | Collocation |
|---|---|---|---|---|---|
| custodian | n | /kʌˈstəʊdiən/ | người giữ gìn, bảo quản | custodians of cultural heritage | cultural custodian, museum custodian |
| digitize | v | /ˈdɪdʒɪtaɪz/ | số hóa | digitize their collections | digitize records, digitize documents |
| metadata | n | /ˈmetədeɪtə/ | siêu dữ liệu | detailed metadata describing each item | metadata standards, metadata schema |
| democratization | n | /dɪˌmɒkrətaɪˈzeɪʃən/ | dân chủ hóa | democratization of access | democratization of knowledge |
| immersive | adj | /ɪˈmɜːsɪv/ | đắm chìm, nhập vai | immersive experiences | immersive technology, immersive environment |
| hotspot | n | /ˈhɒtspɒt/ | điểm nóng, điểm tương tác | clickable hotspots | digital hotspot, interactive hotspot |
| augmented reality | n | /ɔːɡˌmentɪd riˈæləti/ | thực tế tăng cường | augmented reality applications | AR technology, AR experience |
| gamification | n | /ˌɡeɪmɪfɪˈkeɪʃən/ | trò chơi hóa | gamification of learning | gamification strategy, gamification elements |
| tailor | v | /ˈteɪlə(r)/ | điều chỉnh cho phù hợp | tailor their programming | tailor content, tailor services |
| prohibitively | adv | /prəˈhɪbɪtɪvli/ | một cách cấm đoán, quá đắt | prohibitively expensive | prohibitively high, prohibitively costly |
| negotiate | v | /nɪˈɡəʊʃieɪt/ | thương lượng, đàm phán | negotiating permissions | negotiate terms, negotiate agreement |
| hybrid | adj/n | /ˈhaɪbrɪd/ | lai, kết hợp | hybrid institution | hybrid model, hybrid approach |
Passage 2 – Essential Vocabulary
| Từ vựng | Loại từ | Phiên âm | Nghĩa tiếng Việt | Ví dụ từ bài | Collocation |
|---|---|---|---|---|---|
| proliferation | n | /prəˌlɪfəˈreɪʃən/ | sự gia tăng nhanh chóng | proliferation of digital technologies | nuclear proliferation, weapon proliferation |
| domain expertise | n | /dəʊˈmeɪn ˌekspɜːˈtiːz/ | chuyên môn lĩnh vực | combines domain expertise with technical proficiency | domain knowledge, domain specialist |
| authenticate | v | /ɔːˈθentɪkeɪt/ | xác thực | authenticating artifacts | authenticate documents, authenticate identity |
| exponentially | adv | /ˌekspəˈnenʃəli/ | theo cấp số nhân | exponentially expanded | grow exponentially, increase exponentially |
| photogrammetry | n | /ˌfəʊtəˈɡræmɪtri/ | trắc ảnh | principles of 3D scanning and photogrammetry | digital photogrammetry, aerial photogrammetry |
| paradigm shift | n | /ˈpærədaɪm ʃɪft/ | chuyển đổi mô hình | represents a paradigm shift | major paradigm shift, undergo paradigm shift |
| reconcile | v | /ˈrekənsaɪl/ | hòa giải, dung hòa | reconcile their expertise with empirical evidence | reconcile differences, reconcile conflicts |
| vexing | adj | /ˈveksɪŋ/ | gây phiền nhiễu, khó khăn | vexing challenge | vexing problem, vexing question |
| tiered | adj | /tɪəd/ | phân cấp, phân tầng | tiered content systems | tiered structure, tiered approach |
| inherently | adv | /ɪnˈherəntli/ | vốn dĩ, tự thân | inherently collaborative | inherently dangerous, inherently complex |
| articulate | v | /ɑːˈtɪkjuleɪt/ | diễn đạt rõ ràng | articulate curatorial goals | articulate ideas, articulate thoughts |
| descendant community | n | /dɪˈsendənt kəˈmjuːnəti/ | cộng đồng hậu duệ | consulting with descendant communities | indigenous descendant, direct descendant |
| peripheral | adj | /pəˈrɪfərəl/ | ngoại vi, bên lề | peripheral specialty | peripheral vision, peripheral role |
| reconceptualization | n | /ˌriːkənˌseptʃuəlaɪˈzeɪʃən/ | tái khái niệm hóa | fundamental reconceptualization | theoretical reconceptualization |
| bridge | v | /brɪdʒ/ | làm cầu nối | bridge the traditional and digital worlds | bridge the gap, bridge differences |
Passage 3 – Essential Vocabulary
| Từ vựng | Loại từ | Phiên âm | Nghĩa tiếng Việt | Ví dụ từ bài | Collocation |
|---|---|---|---|---|---|
| contentious | adj | /kənˈtenʃəs/ | gây tranh cãi | contentious development | contentious issue, contentious debate |
| reconfigure | v | /ˌriːkənˈfɪɡə(r)/ | cấu hình lại | reconfigure core museum functions | reconfigure system, reconfigure structure |
| algorithmic bias | n | /ˌælɡəˈrɪðmɪk ˈbaɪəs/ | thiên kiến thuật toán | questions about algorithmic bias | algorithmic fairness, algorithmic discrimination |
| stylistic signature | n | /staɪˈlɪstɪk ˈsɪɡnətʃə(r)/ | dấu ấn phong cách | recognize subtle stylistic signatures | artistic signature, unique signature |
| attribute | v | /əˈtrɪbjuːt/ | quy cho, cho là của | attribute them to the correct artist | attribute success, attribute blame |
| tantalizing | adj | /ˈtæntəlaɪzɪŋ/ | hấp dẫn, khêu gợi | tantalizing possibilities | tantalizing prospect, tantalizing glimpse |
| epistemic | adj | /ˌepɪˈstiːmɪk/ | thuộc về tri thức | epistemic status | epistemic value, epistemic uncertainty |
| interplay | n | /ˈɪntəpleɪ/ | sự tương tác | complex interplay of visual analysis | interplay between, dynamic interplay |
| black box | n | /blæk bɒks/ | hộp đen | operate as black boxes | algorithmic black box, technological black box |
| opacity | n | /əʊˈpæsəti/ | sự mờ đục, không trong suốt | This opacity becomes troubling | opacity of data, algorithmic opacity |
| perpetuate | v | /pəˈpetʃueɪt/ | duy trì, làm kéo dài | perpetuate or amplify existing biases | perpetuate stereotypes, perpetuate inequality |
| marginalize | v | /ˈmɑːdʒɪnəlaɪz/ | gạt ra ngoài lề | marginalizing works by women | marginalize groups, marginalize voices |
| encode | v | /ɪnˈkəʊd/ | mã hóa | encoding these biases | encode information, encode data |
| biometric data | n | /ˌbaɪəʊˈmetrɪk ˈdeɪtə/ | dữ liệu sinh trắc học | collect biometric data | biometric identification, biometric security |
| ubiquitous | adj | /juːˈbɪkwɪtəs/ | phổ biến khắp nơi | ubiquitous data collection | ubiquitous technology, ubiquitous computing |
| degraded | adj | /dɪˈɡreɪdɪd/ | bị xuống cấp, hư hỏng | analyze degraded artworks | degraded environment, degraded quality |
| authoritative | adj | /ɔːˈθɒrɪtətɪv/ | có thẩm quyền, đáng tin cậy | authoritative-seeming versions | authoritative source, authoritative text |
| ramification | n | /ˌræmɪfɪˈkeɪʃən/ | hậu quả, phân nhánh | environmental ramifications | legal ramifications, political ramifications |
| carbon footprint | n | /ˈkɑːbən ˈfʊtprɪnt/ | dấu chân carbon | carbon footprints expand | reduce carbon footprint, calculate carbon footprint |
| epistemic disruption | n | /ˌepɪˈstiːmɪk dɪsˈrʌpʃən/ | gián đoạn tri thức | epistemic disruption is beneficial | epistemic break, epistemic change |
| democratizing | v | /dɪˈmɒkrətaɪzɪŋ/ | dân chủ hóa | democratizing expertise | democratizing access, democratizing education |
| impoverish | v | /ɪmˈpɒvərɪʃ/ | làm nghèo đi | impoverish the nuanced understanding | impoverish culture, impoverish experience |
| wholesale | adj | /ˈhəʊlseɪl/ | toàn diện, bán buôn | neither wholesale embrace nor complete rejection | wholesale changes, wholesale destruction |
| safeguard | n/v | /ˈseɪfɡɑːd/ | biện pháp bảo vệ | implement robust safeguards | safeguard interests, safeguard rights |
| augment | v | /ɔːɡˈment/ | tăng cường, bổ sung | augment rather than replace | augment income, augment resources |
| steadfast | adj | /ˈstedfɑːst/ | kiên định | remaining steadfast in their commitment | steadfast support, steadfast loyalty |
Các bài viết liên quan về chủ đề tương tự mà bạn có thể tham khảo thêm để nâng cao kỹ năng đọc hiểu là How virtual art galleries are being used in art education, đây là một chủ đề gần gũi về ứng dụng công nghệ số trong việc tiếp cận nghệ thuật. Tương tự như The role of cultural heritage in modern societies, vấn đề bảo tồn di sản văn hóa trong kỷ nguyên hiện đại cũng có nhiều điểm liên quan đến chủ đề bảo tàng số. Ngoài ra, những thí sinh quan tâm đến The effects of globalization on cultural heritage sẽ thấy được mối liên hệ giữa toàn cầu hóa và cách các bảo tàng số giúp lan tỏa văn hóa trên phạm vi toàn cầu. Cuối cùng, The role of public art projects in community education cũng thảo luận về vai trò giáo dục của nghệ thuật công cộng, một khía cạnh khác của sứ mệnh giáo dục mà bảo tàng hiện đại đang theo đuổi thông qua công nghệ số.
Chiến lược luyện tập hiệu quả cho IELTS Reading về chủ đề bảo tàng
Kết Bài
Chủ đề “Museums in the digital era future” không chỉ phản ánh xu hướng phát triển quan trọng trong ngành bảo tàng mà còn là một đề tài thường gặp trong các đề thi IELTS Reading gần đây. Thông qua bộ đề thi hoàn chỉnh này với 3 passages có độ khó tăng dần từ band 5.0 đến 9.0, bạn đã được làm quen với nhiều dạng câu hỏi khác nhau từ Multiple Choice, True/False/Not Given đến Matching Headings và Summary Completion. Tổng cộng 40 câu hỏi này được thiết kế theo đúng format thi thật, giúp bạn trải nghiệm một bài thi IELTS Reading chân thực nhất.
Phần đáp án chi tiết kèm theo giải thích cặn kẽ về vị trí thông tin trong bài, cách paraphrase và lý do chọn đáp án sẽ giúp bạn tự đánh giá năng lực hiện tại và hiểu rõ những sai lầm cần khắc phục. Hơn 45 từ vựng học thuật được phân loại theo từng passage với phiên âm, nghĩa tiếng Việt và cách sử dụng thực tế sẽ là tài liệu quý giá để bạn mở rộng vốn từ vựng IELTS. Những kỹ thuật đọc như scanning để tìm thông tin chi tiết và skimming để nắm ý chính cũng được thể hiện rõ qua cấu trúc của từng passage.
Hãy nhớ rằng việc luyện tập thường xuyên với các đề thi đa dạng chủ đề là chìa khóa để đạt band điểm cao trong IELTS Reading. Sau khi hoàn thành bộ đề này, bạn nên xem lại những câu trả lời sai, phân tích nguyên nhân và rút ra bài học cho lần làm bài sau. Chúc bạn ôn tập hiệu quả và đạt kết quả như mong muốn trong kỳ thi IELTS sắp tới!
