IELTS Reading: Trí Tuệ Nhân Tạo Cải Thiện Giảng Dạy Ngôn Ngữ – Đề Thi Mẫu Có Đáp Án Chi Tiết

Mở bài

Chủ đề công nghệ trong giáo dục, đặc biệt là vai trò của trí tuệ nhân tạo (AI) trong việc cải thiện giảng dạy ngôn ngữ, đã trở thành một trong những đề tài xuất hiện thường xuyên trong IELTS Reading test những năm gần đây. Với sự phát triển vượt bậc của công nghệ và ứng dụng AI ngày càng rộng rãi trong lĩnh vực giáo dục, chủ đề này không chỉ có tính thời sự cao mà còn phản ánh xu hướng biến đổi của phương pháp học tập hiện đại.

Bài viết này cung cấp cho bạn một bộ đề thi IELTS Reading hoàn chỉnh với ba passages có độ khó tăng dần từ Easy đến Hard, bao gồm 40 câu hỏi đa dạng theo đúng format thi thật. Bạn sẽ được làm quen với các dạng bài từ Multiple Choice, True/False/Not Given, Yes/No/Not Given, Matching Headings, đến Summary Completion và nhiều dạng khác. Mỗi câu hỏi đều được thiết kế cẩn thận để mô phỏng chính xác độ khó và phong cách của đề thi Cambridge IELTS chính thức.

Bên cạnh đề thi, bạn sẽ nhận được đáp án chi tiết với giải thích cụ thể về cách xác định thông tin trong passage, kỹ thuật paraphrase, và chiến lược làm bài hiệu quả. Phần từ vựng được tổng hợp theo từng passage giúp bạn nắm vững những academic words và collocations quan trọng thường xuất hiện trong IELTS.

Bộ đề này phù hợp cho học viên có trình độ từ band 5.0 trở lên, từ những người mới bắt đầu làm quen với format thi đến những ai đang hướng tới band điểm cao.

1. 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. Độ dài mỗi passage dao động từ 650-1000 từ, với độ khó tăng dần từ Passage 1 đến Passage 3.

Phân bổ thời gian khuyến nghị:

• Passage 1: 15-17 phút (13 câu hỏi)
• Passage 2: 18-20 phút (13 câu hỏi)
• Passage 3: 23-25 phút (14 câu hỏi)

Lưu ý quan trọng: Không có thời gian thêm để chép đáp án sang phiếu trả lời, vì vậy bạn cần quản lý thời gian hiệu quả và viết đáp án trực tiếp vào answer sheet trong 60 phút.

Các Dạng Câu Hỏi Trong Đề Này

Bộ đề thi này bao gồm 7 dạng câu hỏi phổ biến nhất trong IELTS Reading:

1. Multiple Choice – Câu hỏi trắc nghiệm nhiều lựa chọn
2. True/False/Not Given – Xác định thông tin đúng, sai hoặc không được đề cập
3. Yes/No/Not Given – Xác định quan điểm của tác giả
4. Matching Headings – Nối tiêu đề với đoạn văn
5. Summary Completion – Hoàn thiện đoạn tóm tắt
6. Matching Features – Nối thông tin với đặc điểm
7. Short-answer Questions – Câu hỏi trả lời ngắn

2. IELTS Reading Practice Test

PASSAGE 1 – The Dawn of AI in Language Learning

Độ khó: Easy (Band 5.0-6.5)

Thời gian đề xuất: 15-17 phút

The integration of artificial intelligence into language education has revolutionized the way students learn new languages. Unlike traditional classroom settings where one teacher must attend to dozens of students simultaneously, AI-powered language learning platforms can provide personalized attention to each learner, adapting to their individual pace, learning style, and areas of difficulty. This technological advancement represents one of the most significant changes in education since the invention of the printing press.

Language learning applications powered by AI have become increasingly sophisticated in recent years. These programs use machine learning algorithms to analyze a student’s performance patterns, identifying specific areas where they struggle and automatically adjusting the difficulty level and type of exercises accordingly. For instance, if a student consistently makes errors with past tense verbs, the system will generate more practice exercises focusing on that particular grammatical structure until mastery is achieved. This level of customization was simply impossible in traditional educational settings where teachers had to follow a standardized curriculum for all students.

One of the most compelling advantages of AI in language instruction is its ability to provide immediate feedback. When a student makes a mistake, the AI system can instantly identify the error, explain why it is incorrect, and offer the correct form along with examples of proper usage. This instantaneous correction helps students learn from their mistakes in real-time, preventing the reinforcement of incorrect patterns that can occur when errors go unnoticed for extended periods. Research has shown that immediate feedback significantly improves retention rates and accelerates the learning process compared to delayed correction methods commonly used in traditional classrooms.

Speech recognition technology, another AI-powered feature, has transformed pronunciation training. Students can now practice speaking without fear of embarrassment in front of classmates, receiving detailed feedback on their pronunciation, intonation, and rhythm. The AI system compares the student’s speech to native speaker models and provides specific guidance on which sounds need improvement. This technology is particularly beneficial for learners who are self-conscious about speaking in public or those who live in areas where native speakers of their target language are not readily available.

The accessibility of AI-powered language learning tools has also democratized language education. Students in remote areas who previously had no access to qualified language teachers can now learn languages through their smartphones or computers. These applications are typically more affordable than traditional language courses, making language learning accessible to people from various socioeconomic backgrounds. Some platforms even offer free basic versions, ensuring that financial constraints do not prevent motivated learners from acquiring new language skills.

However, the implementation of AI in language learning is not without challenges. One significant concern is the potential loss of human interaction, which many educators believe is crucial for developing communicative competence. While AI can effectively teach vocabulary, grammar, and even pronunciation, it cannot fully replicate the nuanced social interactions that occur in human conversation. Language is not merely a system of rules but a tool for human connection, and some linguistic elements such as humor, cultural context, and emotional expression are difficult for AI to teach effectively.

Despite these limitations, most experts agree that AI should be viewed as a complementary tool rather than a replacement for human teachers. The ideal approach combines the strengths of both: AI handles the repetitive drilling and personalized practice, freeing teachers to focus on facilitating meaningful conversations, providing cultural insights, and helping students develop critical thinking skills in the target language. This hybrid model leverages technology to enhance rather than replace the human element of language education.

Questions 1-13

Questions 1-5: Multiple Choice

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

1. According to the passage, AI-powered language learning platforms differ from traditional classrooms in that they:

• A) require more teachers
• B) offer individual attention to each student
• C) are more expensive
• D) follow a standardized curriculum

2. Machine learning algorithms in language apps help students by:

• A) replacing human teachers completely
• B) teaching only vocabulary
• C) identifying weak areas and adjusting exercises
• D) making learning more difficult

3. The passage suggests that immediate feedback from AI systems:

• A) confuses students
• B) is less effective than delayed feedback
• C) helps prevent incorrect learning patterns
• D) only works for advanced learners

4. Speech recognition technology is particularly useful for students who:

• A) enjoy speaking in public
• B) feel embarrassed speaking in front of others
• C) already have perfect pronunciation
• D) prefer traditional classroom methods

5. The main concern about AI in language learning mentioned in the passage is:

• A) it is too expensive
• B) it teaches grammar incorrectly
• C) it may reduce human interaction
• D) it requires too much technology

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

6. AI-powered language learning represents the biggest change in education since the printing press.

7. All AI language learning applications are completely free to use.

8. Students in remote areas now have access to language learning through technology.

9. AI systems can teach humor and cultural context as effectively as human teachers.

Questions 10-13: Sentence Completion

Complete the sentences below. Choose NO MORE THAN THREE WORDS from the passage for each answer.

10. AI systems can compare a student’s speech to __ and provide feedback on pronunciation.

11. The passage states that language is not just a system of rules but a tool for __.

12. Experts believe AI should be used as a __ rather than replacing human teachers.

13. In the ideal approach, AI handles repetitive practice while teachers focus on facilitating __.

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PASSAGE 2 – Adaptive Learning Systems and Linguistic Competence

Độ khó: Medium (Band 6.0-7.5)

Thời gian đề xuất: 18-20 phút

The proliferation of adaptive learning systems in language education has precipitated a fundamental reassessment of pedagogical methodologies. These sophisticated algorithms, grounded in cognitive science and computational linguistics, represent a paradigm shift from the traditional one-size-fits-all approach to a more nuanced, individualized learning experience. By leveraging vast amounts of data regarding learner performance, these systems can construct detailed learner profiles that inform the sequencing, pacing, and presentation of linguistic material in ways that were previously inconceivable.

At the core of these adaptive systems lies the principle of spaced repetition, a learning technique that has been empirically validated through decades of cognitive research. AI algorithms optimize this principle by calculating the ideal intervals at which specific lexical items or grammatical structures should be reviewed to maximize long-term retention. Unlike static flashcard systems, these intelligent platforms continuously recalibrate the review schedule based on the learner’s actual performance, ensuring that items on the verge of being forgotten receive timely reinforcement while well-mastered content is reviewed less frequently. This dynamic optimization results in significantly more efficient learning compared to traditional rote memorization techniques.

The implementation of natural language processing (NLP) has further enhanced the capabilities of AI-driven language instruction. Contemporary systems can analyze not merely whether a student’s response is correct or incorrect, but can evaluate the sophistication and appropriacy of language use. For instance, when a student completes a writing exercise, the AI can assess grammatical accuracy, lexical diversity, coherence, cohesion, and even the register appropriateness for the given context. This multidimensional analysis provides learners with granular feedback that addresses not only surface-level errors but also more subtle aspects of linguistic competence such as style and pragmatic appropriacy.

Moreover, these systems are increasingly capable of generating authentic, contextually relevant practice materials. Rather than relying on a finite database of pre-written exercises, advanced AI can create novel practice items tailored to a student’s specific needs and interests. If a learner is particularly interested in environmental science, for example, the system can generate reading passages, vocabulary exercises, and discussion prompts related to that domain, thereby increasing engagement and making the learning process more intrinsically motivating. This content personalization addresses a longstanding challenge in language education: maintaining student motivation throughout the often arduous process of language acquisition.

The gamification elements integrated into many AI-powered platforms represent another strategic innovation. By incorporating features such as progress bars, achievement badges, leaderboards, and reward systems, these applications tap into psychological principles of motivation and behavioral reinforcement. Research indicates that such game-like features can significantly enhance learner engagement and persistence, particularly among younger learners who have grown up in an environment saturated with digital games and interactive media. However, critics caution that excessive gamification may trivialize the learning process or lead students to focus on extrinsic rewards rather than developing intrinsic interest in the language itself.

Hệ thống học ngôn ngữ thông minh AI cá nhân hóa cho từng học viên theo trình độ và sở thích cá nhân

One particularly promising application of AI in language learning involves conversational agents or chatbots designed to simulate human interaction. These AI-powered interlocutors can engage learners in text-based or voice-based conversations, providing opportunities for authentic communication practice without the logistical constraints of finding human conversation partners. Advanced chatbots can maintain contextually coherent dialogues, adapt their language level to match the learner’s proficiency, and even exhibit personality traits that make interactions more engaging. While these systems still fall short of replicating the full complexity of human conversation, they offer valuable scaffolded practice opportunities, particularly for intermediate learners seeking to build conversational fluency.

Nevertheless, the integration of AI into language pedagogy is not without substantive concerns. Data privacy issues loom large, as these systems collect extensive information about learners’ performance, preferences, and learning behaviors. Questions arise regarding who owns this data, how it might be used beyond its educational purpose, and what safeguards exist to protect learners’ privacy. Additionally, there is the risk of algorithmic bias—if the training data used to develop these systems under-represents certain linguistic varieties or cultural contexts, the AI may perpetuate existing inequalities or inadvertently privilege certain forms of language use over others.

Questions 14-26

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. Adaptive learning systems represent a significant improvement over traditional teaching methods.

15. Spaced repetition is a new learning technique developed specifically for AI systems.

16. AI systems can now evaluate the appropriacy of language use, not just grammatical correctness.

17. All students prefer gamified learning approaches to traditional methods.

18. Current AI chatbots can fully replicate the complexity of human conversation.

Questions 19-22: Matching Headings

Choose the correct heading for paragraphs B-E from the list of headings below.

List of Headings:

• i. The role of motivation in game-based learning
• ii. Privacy concerns in AI education systems
• iii. How AI optimizes memory retention
• iv. The benefits of personalized content generation
• v. Analyzing multiple dimensions of language competence
• vi. The limitations of conversational AI
• vii. Traditional teaching methods compared
• viii. The future of language education

19. Paragraph B

20. Paragraph C

21. Paragraph D

22. Paragraph E

Questions 23-26: Summary Completion

Complete the summary below. Choose NO MORE THAN TWO WORDS from the passage for each answer.

AI-powered conversational agents, also known as (23) __, can engage learners in practice conversations. These systems can maintain dialogues that are (24) __ and adjust their language to match the student’s ability level. Although they cannot yet match the full (25) __ of human conversation, they provide useful practice, especially for (26) __ who want to improve their speaking fluency.

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PASSAGE 3 – Neurolinguistic Implications of AI-Mediated Language Acquisition

Độ khó: Hard (Band 7.0-9.0)

Thời gian đề xuất: 23-25 phút

The advent of artificial intelligence in language pedagogy has engendered not merely practical innovations in instructional delivery but has also catalyzed profound theoretical discussions regarding the fundamental nature of language acquisition itself. Neurolinguistic research, employing advanced neuroimaging techniques such as functional magnetic resonance imaging (fMRI) and electroencephalography (EEG), has begun to illuminate the differential cognitive processes activated when learners engage with AI-mediated instruction compared to traditional human-led pedagogical interactions. These findings suggest that the modality and medium of language instruction may have far-reaching implications for the neuroplasticity underlying second language acquisition (SLA), potentially challenging long-held assumptions about optimal learning conditions.

Empirical investigations have revealed that AI-based language learning platforms capitalize on the brain’s reward circuitry in ways that diverge markedly from conventional classroom instruction. The immediate reinforcement provided by these systems triggers dopaminergic responses in the ventral tegmental area and nucleus accumbens—regions implicated in motivation and reward processing. This neurochemical cascade, repeatedly activated through successful task completion and instantaneous positive feedback, appears to facilitate the consolidation of linguistic memories through the strengthening of synaptic connections in the hippocampus and prefrontal cortex. However, researchers have observed that this accelerated reinforcement cycle, while potentially enhancing procedural memory formation for grammatical rules and vocabulary retention, may not equivalently support the development of declarative knowledge associated with pragmatic competence and sociocultural aspects of language use, which neuroimaging studies suggest rely more heavily on distributed neural networks involving the superior temporal sulcus and medial prefrontal cortex—regions activated primarily through genuine social interaction.

The phenomenon of neural entrainment—whereby the brain’s electrical oscillations synchronize with external rhythmic stimuli—presents another compelling dimension to understanding AI’s role in language learning. Research has demonstrated that prosodic features of language, including stress patterns, intonation contours, and rhythmic structure, are fundamentally processed through neural entrainment mechanisms in the auditory cortex. AI-powered systems employing sophisticated speech synthesis technology can deliver linguistic input with precisely calibrated prosodic features, potentially optimizing neural entrainment in ways that human teachers, with their inevitable variability and individual idiosyncrasies, cannot consistently achieve. Longitudinal studies utilizing magnetoencephalography (MEG) have indicated that learners exposed to such systematically controlled prosodic input demonstrate more rapid development of implicit phonological processing capabilities, as evidenced by enhanced P600 event-related potentials—a neurophysiological marker of syntactic processing automaticity.

Nghiên cứu não bộ và quá trình học ngoại ngữ qua công nghệ trí tuệ nhân tạo hiện đại

Nevertheless, the putative advantages of AI-mediated instruction must be weighed against potential neurological trade-offs. The theory of mind—the capacity to attribute mental states to others and comprehend their perspectives—is crucially implicated in pragmatic language use and is thought to be subserved by a neural network encompassing the temporoparietal junction, posterior superior temporal sulcus, and medial prefrontal cortex. This cognitive capacity, which develops through repeated social interactions requiring perspective-taking and intention recognition, may be inadequately stimulated in AI-based learning environments that lack genuine communicative intent and the rich paralinguistic cues—facial expressions, gestures, eye gaze—that characterize human interaction. Neuroimaging evidence suggests that even highly advanced conversational AI fails to activate the full constellation of social cognitive neural networks engaged during human-to-human communication, potentially constraining the development of nuanced pragmatic competence.

The concept of cognitive load presents another critical consideration in evaluating AI’s efficacy in language instruction. According to cognitive load theory, working memory has finite capacity, and optimal learning occurs when instructional design manages intrinsic load (inherent difficulty of material), extraneous load (poorly designed instruction), and germane load (processing that contributes to learning) to prevent cognitive overload. AI systems, through their capacity for precise difficulty calibration and adaptive sequencing, can theoretically optimize cognitive load by presenting linguistic challenges that consistently align with the learner’s zone of proximal development—the Vygotskian concept describing the difference between what a learner can do independently and what they can achieve with guidance. Neuroscientific research employing near-infrared spectroscopy (NIRS) has demonstrated that AI-adapted lessons indeed produce more consistent activation patterns in the dorsolateral prefrontal cortex—a region associated with working memory—suggesting better-managed cognitive load compared to non-adaptive instruction.

However, this very precision in difficulty calibration may inadvertently deprive learners of experiences that, while temporarily inducing greater cognitive load, are essential for developing metalinguistic awareness and strategic competence. The productive struggle that occurs when learners grapple with linguistic challenges slightly beyond their current capabilities—what some theorists term “desirable difficulties“—has been shown to promote deeper cognitive processing and more robust long-term retention. Functional connectivity analyses using resting-state fMRI have revealed that learners who periodically experience such productive struggle demonstrate enhanced connectivity between the default mode network and executive control network—a neural signature associated with reflective learning and self-regulatory capabilities. The extent to which AI systems, in their optimization for immediate performance, may undermine this developmentally crucial experience of productive struggle remains an open empirical question.

Furthermore, the socioaffective dimension of language learning—encompassing factors such as anxiety, motivation, identity formation, and community belonging—is inextricably linked to neurobiological processes that may be differentially influenced by AI versus human instruction. Language learning anxiety, for instance, has been correlated with hyperactivation of the amygdala and reduced functional connectivity between emotional regulation regions and language processing areas. While some learners may experience reduced anxiety with AI tutors due to the absence of social evaluation threat, others may find the lack of empathetic human presence alienating, potentially elevating cortisol levels and activating stress response systems that impair learning. The neuroscience of social connection suggests that positive relationships with teachers and peers activate oxytocin pathways that facilitate trust, reduce stress, and enhance memory consolidation—neurochemical processes that AI systems, regardless of their sophistication, cannot biologically replicate.

Questions 27-40

Questions 27-31: Multiple Choice

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

27. According to the passage, neurolinguistic research using fMRI and EEG has shown that:

• A) AI is always better than human teachers
• B) the medium of instruction affects cognitive processes
• C) traditional methods are more effective
• D) brain plasticity is unrelated to language learning

28. The immediate feedback from AI systems activates brain regions associated with:

• A) visual processing
• B) motor control
• C) reward and motivation
• D) auditory perception only

29. Neural entrainment refers to:

• A) training neural networks
• B) brain waves synchronizing with rhythmic stimuli
• C) the speed of neural processing
• D) the difficulty of neural tasks

30. Theory of mind is important for language learning because it:

• A) helps with vocabulary memorization
• B) enables understanding of others’ perspectives
• C) improves pronunciation
• D) speeds up grammar learning

31. According to cognitive load theory, optimal learning happens when:

• A) tasks are extremely easy
• B) working memory is overloaded
• C) instructional design properly manages different types of cognitive load
• D) students work without any guidance

Questions 32-36: Matching Features

Match each research finding (32-36) with the correct brain region or concept (A-H). You may use any letter more than once.

Research Findings:

32. Region activated during reward processing in AI-based learning

33. Areas involved in theory of mind and social cognition

34. Region associated with working memory during adapted lessons

35. Area where synaptic connections strengthen for linguistic memory

36. Region that becomes hyperactive during language learning anxiety

Brain Regions/Concepts:

• A) Amygdala
• B) Hippocampus
• C) Dorsolateral prefrontal cortex
• D) Nucleus accumbens
• E) Auditory cortex
• F) Temporoparietal junction
• G) Broca’s area
• H) Visual cortex

Questions 37-40: Short-answer Questions

Answer the questions below. Choose NO MORE THAN THREE WORDS from the passage for each answer.

37. What type of memory formation does the accelerated reinforcement cycle in AI systems particularly enhance?

38. What term describes the difference between independent ability and guided achievement, according to Vygotsky?

39. What phrase describes challenges that promote deeper cognitive processing despite increased difficulty?

40. What chemical pathways activated by positive teacher-student relationships cannot be biologically replicated by AI?

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3. Answer Keys – Đáp Án

PASSAGE 1: Questions 1-13

1. B
2. C
3. C
4. B
5. C
6. TRUE
7. FALSE
8. TRUE
9. FALSE
10. native speaker models
11. human connection
12. complementary tool
13. meaningful conversations

PASSAGE 2: Questions 14-26

14. YES
15. NO
16. YES
17. NOT GIVEN
18. NO
19. iii
20. v
21. iv
22. i
23. chatbots
24. contextually coherent
25. complexity
26. intermediate learners

PASSAGE 3: Questions 27-40

27. B
28. C
29. B
30. B
31. C
32. D
33. F
34. C
35. B
36. A
37. procedural memory
38. zone of proximal development
39. desirable difficulties
40. oxytocin pathways

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4. Giải Thích Đáp Án Chi Tiết

Passage 1 – Giải Thích

Câu 1: B – offer individual attention to each student

• Dạng câu hỏi: Multiple Choice
• Từ khóa: AI-powered platforms, differ from traditional classrooms
• Vị trí trong bài: Đoạn A, dòng 2-5
• Giải thích: Bài đọc nói rõ “Unlike traditional classroom settings where one teacher must attend to dozens of students simultaneously, AI-powered language learning platforms can provide personalized attention to each learner”. Đây là sự paraphrase của “individual attention” = “personalized attention”.

Câu 2: C – identifying weak areas and adjusting exercises

• Dạng câu hỏi: Multiple Choice
• Từ khóa: Machine learning algorithms, help students
• Vị trí trong bài: Đoạn B, dòng 2-7
• Giải thích: Đoạn văn chỉ ra “These programs use machine learning algorithms to analyze a student’s performance patterns, identifying specific areas where they struggle and automatically adjusting the difficulty level”. Câu trả lời paraphrase “identifying specific areas where they struggle” thành “identifying weak areas”.

Câu 3: C – helps prevent incorrect learning patterns

• Dạng câu hỏi: Multiple Choice
• Từ khóa: immediate feedback, AI systems
• Vị trí trong bài: Đoạn C, dòng 3-6
• Giải thích: Bài đọc đề cập “This instantaneous correction helps students learn from their mistakes in real-time, preventing the reinforcement of incorrect patterns”. Đáp án C paraphrase ý này một cách chính xác.

Câu 6: TRUE

• Dạng câu hỏi: True/False/Not Given
• Từ khóa: biggest change in education, printing press
• Vị trí trong bài: Đoạn A, dòng cuối
• Giải thích: Đoạn văn khẳng định rõ ràng “This technological advancement represents one of the most significant changes in education since the invention of the printing press”, khớp hoàn toàn với statement.

Câu 7: FALSE

• Dạng câu hỏi: True/False/Not Given
• Từ khóa: all AI applications, completely free
• Vị trí trong bài: Đoạn E, dòng 3-4
• Giải thích: Bài viết nói “These applications are typically more affordable than traditional language courses” và “Some platforms even offer free basic versions”, cho thấy không phải tất cả đều miễn phí hoàn toàn.

Câu 10: native speaker models

• Dạng câu hỏi: Sentence Completion
• Từ khóa: compare student’s speech, feedback on pronunciation
• Vị trí trong bài: Đoạn D, dòng 3-5
• Giải thích: Câu trong bài: “The AI system compares the student’s speech to native speaker models and provides specific guidance”. Cụm từ “native speaker models” xuất hiện đúng vị trí cần điền.

Câu 13: meaningful conversations

• Dạng câu hỏi: Sentence Completion
• Từ khóa: teachers focus on facilitating
• Vị trí trong bài: Đoạn G, dòng 3-5
• Giải thích: Đoạn văn nói “AI handles the repetitive drilling and personalized practice, freeing teachers to focus on facilitating meaningful conversations”. Đáp án là “meaningful conversations”.

Passage 2 – Giải Thích

Câu 14: YES

• Dạng câu hỏi: Yes/No/Not Given
• Từ khóa: adaptive learning systems, significant improvement
• Vị trí trong bài: Đoạn A, dòng 1-3
• Giải thích: Tác giả sử dụng cụm từ “paradigm shift” và “reassessment of pedagogical methodologies”, cho thấy quan điểm tích cực về sự cải thiện đáng kể của hệ thống học thích ứng.

Câu 15: NO

• Dạng câu hỏi: Yes/No/Not Given
• Từ khóa: spaced repetition, new technique, developed for AI
• Vị trí trong bài: Đoạn B, dòng 1-3
• Giải thích: Bài viết nói rõ spaced repetition là “a learning technique that has been empirically validated through decades of cognitive research”, cho thấy đây không phải kỹ thuật mới được phát triển cho AI.

Câu 16: YES

• Dạng câu hỏi: Yes/No/Not Given
• Từ khóa: AI systems, evaluate appropriacy, not just grammatical correctness
• Vị trí trong bài: Đoạn C, dòng 2-6
• Giải thích: Đoạn văn khẳng định “Contemporary systems can analyze not merely whether a student’s response is correct or incorrect, but can evaluate the sophistication and appropriacy of language use”, đúng với statement.

Câu 19: iii – How AI optimizes memory retention

• Dạng câu hỏi: Matching Headings
• Vị trí: Paragraph B
• Giải thích: Đoạn B tập trung vào nguyên tắc spaced repetition và cách AI tối ưu hóa khoảng thời gian ôn tập để tăng cường khả năng ghi nhớ dài hạn (long-term retention).

Câu 20: v – Analyzing multiple dimensions of language competence

• Dạng câu hỏi: Matching Headings
• Vị trí: Paragraph C
• Giải thích: Đoạn C mô tả cách NLP phân tích nhiều khía cạnh của ngôn ngữ: grammatical accuracy, lexical diversity, coherence, cohesion, và register appropriateness.

Câu 23: chatbots

• Dạng câu hỏi: Summary Completion
• Từ khóa: conversational agents, also known as
• Vị trí trong bài: Đoạn F, dòng 1-2
• Giải thích: Câu trong bài: “conversational agents or chatbots designed to simulate human interaction”, cho thấy “chatbots” là tên gọi khác của conversational agents.

Câu 26: intermediate learners

• Dạng câu hỏi: Summary Completion
• Từ khóa: useful practice, especially for, improve speaking fluency
• Vị trí trong bài: Đoạn F, dòng cuối
• Giải thích: Bài viết nói rõ “particularly for intermediate learners seeking to build conversational fluency”.

Passage 3 – Giải Thích

Câu 27: B – the medium of instruction affects cognitive processes

• Dạng câu hỏi: Multiple Choice
• Từ khóa: neurolinguistic research, fMRI, EEG
• Vị trí trong bài: Đoạn A, dòng 2-6
• Giải thích: Đoạn văn chỉ ra “differential cognitive processes activated when learners engage with AI-mediated instruction compared to traditional human-led pedagogical interactions”, cho thấy phương thức giảng dạy ảnh hưởng đến quá trình nhận thức.

Câu 28: C – reward and motivation

• Dạng câu hỏi: Multiple Choice
• Từ khóa: immediate feedback, AI systems, activates brain regions
• Vị trí trong bài: Đoạn B, dòng 2-4
• Giải thích: Bài viết nói rõ “The immediate reinforcement provided by these systems triggers dopaminergic responses in the ventral tegmental area and nucleus accumbens—regions implicated in motivation and reward processing”.

Câu 29: B – brain waves synchronizing with rhythmic stimuli

• Dạng câu hỏi: Multiple Choice
• Từ khóa: neural entrainment refers to
• Vị trí trong bài: Đoạn C, dòng 1-3
• Giải thích: Định nghĩa rõ ràng: “The phenomenon of neural entrainment—whereby the brain’s electrical oscillations synchronize with external rhythmic stimuli”.

Câu 32: D – Nucleus accumbens

• Dạng câu hỏi: Matching Features
• Vị trí trong bài: Đoạn B, dòng 3-4
• Giải thích: Bài viết nói nucleus accumbens là vùng liên quan đến “motivation and reward processing” trong học tập dựa trên AI.

Câu 35: B – Hippocampus

• Dạng câu hỏi: Matching Features
• Vị trí trong bài: Đoạn B, dòng 5-7
• Giải thích: Đoạn văn đề cập “consolidation of linguistic memories through the strengthening of synaptic connections in the hippocampus and prefrontal cortex”.

Câu 37: procedural memory

• Dạng câu hỏi: Short-answer Questions
• Từ khóa: accelerated reinforcement cycle, particularly enhance
• Vị trí trong bài: Đoạn B, dòng 7-9
• Giải thích: Bài viết nói rõ “while potentially enhancing procedural memory formation for grammatical rules and vocabulary retention”.

Câu 38: zone of proximal development

• Dạng câu hỏi: Short-answer Questions
• Từ khóa: difference between independent ability, guided achievement, Vygotsky
• Vị trí trong bài: Đoạn E, dòng 6-8
• Giải thích: Định nghĩa Vygotskian concept: “the zone of proximal development—the Vygotskian concept describing the difference between what a learner can do independently and what they can achieve with guidance”.

Câu 40: oxytocin pathways

• Dạng câu hỏi: Short-answer Questions
• Từ khóa: positive teacher-student relationships, cannot be biologically replicated
• Vị trí trong bài: Đoạn G, dòng cuối
• Giải thích: Câu cuối của passage: “positive relationships with teachers and peers activate oxytocin pathways that facilitate trust, reduce stress, and enhance memory consolidation—neurochemical processes that AI systems, regardless of their sophistication, cannot biologically replicate”.

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5. 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, hợp nhất	The integration of artificial intelligence into language education	system integration, full integration
revolutionize	v	/ˌrevəˈluːʃənaɪz/	cách mạng hóa, thay đổi hoàn toàn	AI has revolutionized the way students learn	revolutionize education, revolutionize industry
personalized	adj	/ˈpɜːrsənəlaɪzd/	được cá nhân hóa	AI provides personalized attention to each learner	personalized learning, personalized approach
sophisticated	adj	/səˈfɪstɪkeɪtɪd/	tinh vi, phức tạp cao	Language learning applications have become increasingly sophisticated	sophisticated technology, sophisticated system
algorithm	n	/ˈælɡərɪðəm/	thuật toán	Machine learning algorithms analyze performance patterns	complex algorithm, learning algorithm
mastery	n	/ˈmæstəri/	sự thành thạo, làm chủ	Practice until mastery is achieved	achieve mastery, complete mastery
compelling	adj	/kəmˈpelɪŋ/	thuyết phục, hấp dẫn	One of the most compelling advantages of AI	compelling evidence, compelling reason
retention	n	/rɪˈtenʃn/	sự giữ lại, ghi nhớ	Immediate feedback improves retention rates	information retention, memory retention
embarrassment	n	/ɪmˈbærəsmənt/	sự xấu hổ, bối rối	Practice without fear of embarrassment	avoid embarrassment, cause embarrassment
democratize	v	/dɪˈmɒkrətaɪz/	dân chủ hóa, phổ cập	AI has democratized language education	democratize access, democratize education
nuanced	adj	/ˈnjuːɑːnst/	tinh tế, nhiều sắc thái	AI cannot replicate nuanced social interactions	nuanced understanding, nuanced approach
complementary	adj	/ˌkɒmplɪˈmentri/	bổ sung, bổ trợ	AI should be viewed as a complementary tool	complementary role, complementary skills

Passage 2 – Essential Vocabulary

Từ vựng	Loại từ	Phiên âm	Nghĩa tiếng Việt	Ví dụ từ bài	Collocation
proliferation	n	/prəˌlɪfəˈreɪʃn/	sự gia tăng nhanh chóng	The proliferation of adaptive learning systems	rapid proliferation, nuclear proliferation
precipitate	v	/prɪˈsɪpɪteɪt/	thúc đẩy, gây ra	Has precipitated a fundamental reassessment	precipitate a crisis, precipitate change
pedagogical	adj	/ˌpedəˈɡɒdʒɪkl/	thuộc sư phạm, giảng dạy	Reassessment of pedagogical methodologies	pedagogical approach, pedagogical practice
paradigm shift	n phrase	/ˈpærədaɪm ʃɪft/	sự thay đổi mô hình căn bản	Represents a paradigm shift in education	experience a paradigm shift, create a paradigm shift
empirically	adv	/ɪmˈpɪrɪkli/	dựa trên thực nghiệm	A technique that has been empirically validated	empirically proven, empirically tested
recalibrate	v	/riːˈkælɪbreɪt/	hiệu chỉnh lại, điều chỉnh lại	These platforms continuously recalibrate the schedule	recalibrate approach, recalibrate strategy
granular	adj	/ˈɡrænjələr/	chi tiết, tỉ mỉ	Provides learners with granular feedback	granular detail, granular data
pragmatic	adj	/præɡˈmætɪk/	thực dụng, thực tế	Subtle aspects of pragmatic appropriacy	pragmatic approach, pragmatic solution
intrinsically	adv	/ɪnˈtrɪnsɪkli/	vốn có, về bản chất	Making learning more intrinsically motivating	intrinsically motivated, intrinsically valuable
gamification	n	/ˌɡeɪmɪfɪˈkeɪʃn/	trò chơi hóa	Gamification elements integrated into platforms	gamification strategy, gamification techniques
trivialize	v	/ˈtrɪviəlaɪz/	xem thường, đơn giản hóa	Excessive gamification may trivialize learning	trivialize the problem, trivialize concerns
conversational agent	n phrase	/ˌkɒnvəˈseɪʃənl ˈeɪdʒənt/	tác nhân hội thoại (chatbot)	Conversational agents designed to simulate interaction	AI conversational agent, virtual conversational agent
algorithmic bias	n phrase	/ˌælɡəˈrɪðmɪk ˈbaɪəs/	thiên lệch thuật toán	The risk of algorithmic bias	address algorithmic bias, reduce algorithmic bias
perpetuate	v	/pərˈpetʃueɪt/	duy trì, kéo dài	The AI may perpetuate existing inequalities	perpetuate stereotypes, perpetuate myths

Từ vựng học thuật IELTS Reading chủ đề trí tuệ nhân tạo trong giáo dục ngôn ngữ

Passage 3 – Essential Vocabulary

Từ vựng	Loại từ	Phiên âm	Nghĩa tiếng Việt	Ví dụ từ bài	Collocation
advent	n	/ˈædvent/	sự xuất hiện, sự ra đời	The advent of artificial intelligence	the advent of technology, since the advent of
engender	v	/ɪnˈdʒendər/	tạo ra, gây ra	Has engendered profound theoretical discussions	engender debate, engender trust
catalyze	v	/ˈkætəlaɪz/	xúc tác, thúc đẩy	Has catalyzed profound discussions	catalyze change, catalyze innovation
neuroimaging	n	/ˈnjʊərəʊˌɪmɪdʒɪŋ/	chụp ảnh thần kinh	Employing advanced neuroimaging techniques	neuroimaging study, neuroimaging data
neuroplasticity	n	/ˌnjʊərəʊplæˈstɪsəti/	tính dẻo thần kinh	Implications for neuroplasticity underlying SLA	brain neuroplasticity, enhance neuroplasticity
dopaminergic	adj	/ˌdəʊpəmɪˈnɜːdʒɪk/	liên quan đến dopamine	Triggers dopaminergic responses	dopaminergic system, dopaminergic pathway
consolidation	n	/kənˌsɒlɪˈdeɪʃn/	sự củng cố	Facilitate the consolidation of linguistic memories	memory consolidation, consolidation process
neural entrainment	n phrase	/ˈnjʊərəl ɪnˈtreɪnmənt/	sự đồng bộ thần kinh	The phenomenon of neural entrainment	neural entrainment mechanism, enhance neural entrainment
prosodic	adj	/prəˈsɒdɪk/	thuộc nhịp điệu (ngôn ngữ)	Prosodic features of language	prosodic patterns, prosodic structure
putative	adj	/ˈpjuːtətɪv/	được cho là, giả định	The putative advantages of AI	putative benefits, putative role
theory of mind	n phrase	/ˈθɪəri əv maɪnd/	lý thuyết tâm trí	Theory of mind is crucially implicated	develop theory of mind, theory of mind abilities
paralinguistic	adj	/ˌpærəlɪŋˈɡwɪstɪk/	phi ngôn ngữ (cử chỉ, ánh mắt)	Rich paralinguistic cues characterize interaction	paralinguistic features, paralinguistic communication
cognitive load	n phrase	/ˈkɒɡnətɪv ləʊd/	tải nhận thức	The concept of cognitive load	manage cognitive load, reduce cognitive load
zone of proximal development	n phrase	/zəʊn əv ˈprɒksɪməl dɪˈveləpmənt/	vùng phát triển gần nhất	Align with the learner’s zone of proximal development	within the zone of proximal development, identify the zone
desirable difficulties	n phrase	/dɪˈzaɪərəbl ˈdɪfɪkəltiz/	khó khăn mong muốn	What theorists term desirable difficulties	create desirable difficulties, benefit from desirable difficulties
socioaffective	adj	/ˌsəʊsiəʊəˈfektɪv/	thuộc tình cảm xã hội	The socioaffective dimension of learning	socioaffective factors, socioaffective development
amygdala	n	/əˈmɪɡdələ/	hạch hạnh nhân (não)	Hyperactivation of the amygdala	amygdala response, amygdala activation
oxytocin	n	/ˌɒksɪˈtəʊsɪn/	oxytocin (hormone)	Activate oxytocin pathways	oxytocin release, oxytocin levels

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Kết bài

Chủ đề “How Artificial Intelligence Is Improving Language Instruction” không chỉ phản ánh xu hướng công nghệ hiện đại mà còn là một trong những đề tài thường xuyên xuất hiện trong IELTS Reading test với nhiều góc độ khác nhau: khoa học công nghệ, giáo dục, tâm lý học, và thần kinh học. Việc nắm vững chủ đề này giúp bạn chuẩn bị tốt cho nhiều dạng bài tương tự về công nghệ trong giáo dục.

Ba passages trong bộ đề này đã được thiết kế cẩn thận với độ khó tăng dần từ Easy (Band 5.0-6.5) đến Medium (Band 6.0-7.5) và Hard (Band 7.0-9.0), phản ánh chính xác cấu trúc của đề thi IELTS thực tế. Passage 1 giới thiệu các khái niệm cơ bản về AI trong học ngôn ngữ với ngôn ngữ dễ hiểu. Passage 2 đào sâu vào các hệ thống học thích ứng với từ vựng học thuật phong phú hơn. Passage 3 khám phá các khía cạnh thần kinh ngôn ngữ học với độ phức tạp cao nhất, đòi hỏi kỹ năng đọc hiểu và phân tích nâng cao.

Đáp án chi tiết kèm giải thích đã chỉ ra cách xác định thông tin trong bài, kỹ thuật paraphrase, và chiến lược làm bài cho từng dạng câu hỏi. Điều quan trọng là bạn cần hiểu logic đằng sau mỗi đáp án, không chỉ ghi nhớ câu trả lời. Hãy đọc lại phần giải thích nhiều lần để nắm vững phương pháp tiếp cận.

Phần từ vựng tổng hợp theo ba passages cung cấp kho từ vựng học thuật phong phú với hơn 40 từ và cụm từ quan trọng, kèm phiên âm, nghĩa, ví dụ và collocations. Đây là những từ vựng có tần suất cao trong IELTS Reading, đặc biệt ở các passages về khoa học, công nghệ và giáo dục. Việc thuộc lòng những từ này sẽ giúp bạn đọc hiểu nhanh hơn và chính xác hơn.

Để tận dụng tối đa bộ đề này, bạn nên:

• Làm bài trong đúng 60 phút như thi thật để rèn luyện khả năng quản lý thời gian
• Đối chiếu đáp án và đọc kỹ phần giải thích để hiểu rõ lý do đúng/sai
• Học thuộc từ vựng theo ngữ cảnh, không học riêng lẻ
• Làm lại bài sau 1-2 tuần để kiểm tra khả năng ghi nhớ
• Áp dụng các kỹ thuật đã học vào các đề thi khác

Tương tự như The rise of e-learning in higher education, chủ đề về AI trong giáo dục ngôn ngữ cũng phản ánh xu hướng chuyển đổi số toàn cầu trong lĩnh vực đào tạo. Những học viên quan tâm đến The impact of collaborative learning on student performance sẽ thấy có nhiều điểm tương đồng về phương pháp giảng dạy hiện đại. Đồng thời, đề tài này cũng liên quan chặt chẽ đến How does the digital divide affect educational equity? khi bàn về vấn đề tiếp cận công nghệ trong giáo dục.

Chúc bạn học tập hiệu quả và đạt được band điểm mong muốn trong kỳ thi IELTS sắp tới!