IELTS Reading: How to Learn Coding Online – Đề thi mẫu có đáp án chi tiết

Trong thời đại công nghệ số bùng nổ, kỹ năng lập trình đang trở thành một trong những năng lực quan trọng nhất của thế kỷ 21. Chủ đề “How To Learn Coding Online” không chỉ phản ánh xu hướng học tập hiện đại mà còn thường xuyên xuất hiện trong IELTS Reading với nhiều góc độ khác nhau: công nghệ giáo dục, phương pháp tự học, hoặc tác động của kỹ năng số đến nghề nghiệp. Bài viết này cung cấp một bộ đề thi IELTS Reading hoàn chỉnh với 3 passages được xây dựng theo đúng chuẩn Cambridge IELTS, từ mức độ dễ đến khó. Bạn sẽ được trải nghiệm 40 câu hỏi đa dạng bao gồm Multiple Choice, True/False/Not Given, Matching Headings, Summary Completion và nhiều dạng khác. Mỗi câu hỏi đều có đáp án chi tiết kèm giải thích vị trí trong bài, từ khóa quan trọng và kỹ thuật paraphrase. Bộ đề này phù hợp cho học viên từ band 5.0 trở lên, giúp bạn làm quen với cấu trúc đề thi thật, nâng cao kỹ năng đọc hiểu và tích lũy vốn từ vựng học thuật quý giá.

1. 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 đòi hỏi khả năng đọc hiểu, phân tích và quản lý thời gian hiệu quả. Mỗi passage có độ dài khoảng 700-1000 từ và độ khó tăng dần từ Passage 1 đến Passage 3.

Phân bổ thời gian khuyến nghị:

• Passage 1: 15-17 phút (độ khó dễ, dành cho band 5.0-6.5)
• Passage 2: 18-20 phút (độ khó trung bình, dành cho band 6.0-7.5)
• Passage 3: 23-25 phút (độ khó cao, dành cho band 7.0-9.0)

Lưu ý quan trọng: Bạn cần chuyển đáp án lên Answer Sheet trong 60 phút này, không có thời gian bổ sung. Do đó, hãy luyện tập quản lý thời gian ngay từ đầu.

Các Dạng Câu Hỏi Trong Đề Này

Bộ đề thi mẫu 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/không được đề cập
3. Yes/No/Not Given – Xác định quan điểm tác giả
4. Matching Headings – Nối tiêu đề với đoạn văn
5. Summary Completion – Hoàn thành đoạn tóm tắt
6. Matching Features – Nối thông tin với đặc điểm
7. Short-answer Questions – Câu hỏi trả lời ngắn

Mỗi dạng câu hỏi yêu cầu kỹ năng đọc khác nhau: skimming (đọc lướt), scanning (tìm thông tin cụ thể), đọc hiểu chi tiết, và suy luận. Bạn sẽ gặp tất cả các dạng này trong bộ đề dưới đây.

Hướng dẫn làm bài IELTS Reading hiệu quả cho chủ đề học lập trình trực tuyến

2. IELTS Reading Practice Test

PASSAGE 1 – The Rise of Online Coding Education

Độ khó: Easy (Band 5.0-6.5)

Thời gian đề xuất: 15-17 phút

The digital revolution has fundamentally transformed the way people acquire new skills, and learning to code is no exception. Online coding education has experienced exponential growth over the past decade, making programming knowledge accessible to millions worldwide who might never have had the opportunity to learn these valuable skills through traditional educational pathways.

The emergence of online coding platforms began in earnest around 2010, when several pioneering websites recognized that there was a significant gap between the demand for programming skills and the availability of affordable, flexible learning options. Traditional computer science degrees were expensive, time-consuming, and often inaccessible to working adults or those living in areas without prestigious universities. Early innovators in this space, such as Codecademy and Khan Academy, offered free, interactive tutorials that allowed complete beginners to write their first lines of code within minutes of visiting their websites.

What makes online coding education particularly appealing is its self-paced nature. Unlike traditional classroom settings where students must follow a fixed schedule, online learners can progress through course materials at their own speed. This flexibility has proven especially valuable for career changers – individuals who want to transition into technology roles while maintaining their current employment. A typical learner might spend early mornings or evenings working through coding exercises, gradually building their skills over several months without the financial pressure of leaving their job.

The interactive component of modern coding platforms represents a significant advancement over simply reading textbooks or watching video lectures. Most platforms now feature built-in code editors where students can write programs directly in their web browsers, receiving immediate feedback on whether their code works correctly. This hands-on approach mirrors how professional programmers actually work and helps learners develop practical problem-solving skills rather than just theoretical knowledge. When a student makes a mistake, the platform typically provides helpful error messages and hints, creating a supportive learning environment that encourages experimentation.

Community support has emerged as another crucial factor in successful online coding education. Most platforms now include forums where learners can ask questions, share their projects, and learn from others’ experiences. This peer-to-peer interaction helps combat one of the main challenges of online learning: the sense of isolation that can lead to decreased motivation and higher dropout rates. Additionally, many platforms have incorporated gamification elements such as points, badges, and progress tracking, which provide psychological rewards that keep learners engaged throughout their journey.

The economic implications of accessible coding education are substantial. In many developing countries, learning to code online has created unprecedented opportunities for economic advancement. A talented programmer in Vietnam or Nigeria can now compete for freelance projects or remote positions with companies in Silicon Valley, earning income that would have been impossible to achieve through local employment options. This democratization of opportunity has the potential to reduce global economic inequality and create a more geographically diverse technology workforce.

However, online coding education is not without its challenges. Completion rates for free online courses remain relatively low, typically ranging between 5-15%. The abundance of choice can be overwhelming for beginners, who may struggle to determine which programming language to learn first or which platform offers the most comprehensive curriculum. Furthermore, while online courses excel at teaching syntax and basic programming concepts, they may not fully replicate the experience of working on large, complex projects with a team – a crucial skill for professional software development.

Despite these limitations, the trajectory of online coding education continues upward. New platforms are constantly emerging with innovative approaches to teaching programming. Some focus on specific niches, such as mobile app development or data science, while others emphasize project-based learning where students build real-world applications from day one. As artificial intelligence becomes more sophisticated, we are beginning to see adaptive learning systems that can personalize the educational experience based on each student’s strengths, weaknesses, and learning style.

Questions 1-6

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

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

1. Online coding platforms started becoming popular around 2010.
2. Traditional computer science degrees are more effective than online courses for learning programming.
3. Self-paced learning is particularly beneficial for people who want to change careers.
4. All online coding platforms charge fees for their advanced courses.
5. Students can write and test code directly in their web browsers on most modern platforms.
6. Online coding education has completely eliminated global economic inequality.

Questions 7-10

Complete the sentences below.

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

7. Online platforms provide __ when students write incorrect code, helping them learn from mistakes.
8. Forums on coding platforms enable __ that reduces feelings of isolation.
9. Many platforms use __ like points and badges to maintain learner engagement.
10. The typical __ for free online coding courses is between 5-15%.

Questions 11-13

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

11. According to the passage, what was the main problem that early online coding platforms addressed?

    • A. The poor quality of computer science education
    • B. The gap between skill demand and accessible learning options
    • C. The lack of interest in programming careers
    • D. The absence of free educational content online

12. What aspect of online coding education helps learners develop practical problem-solving skills?

    • A. Video lectures from expert programmers
    • B. Detailed programming textbooks
    • C. Interactive code editors with immediate feedback
    • D. Community forums and discussion boards

13. What challenge of online coding education does the passage mention?

    • A. It is too expensive for most learners
    • B. It doesn’t teach enough programming languages
    • C. Completion rates for free courses are relatively low
    • D. It requires too much time commitment from students

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PASSAGE 2 – Effective Strategies for Learning Programming Online

Độ khó: Medium (Band 6.0-7.5)

Thời gian đề xuất: 18-20 phút

While the proliferation of online coding resources has made programming knowledge more accessible than ever, the abundance of options can paradoxically create confusion and analysis paralysis for aspiring developers. Success in online coding education requires not just access to quality resources, but also strategic approaches to learning that maximize retention and skill development. Educational researchers have identified several key principles that distinguish successful self-taught programmers from those who struggle or abandon their learning journey prematurely.

A. Establishing Clear Objectives

The first critical step in effective online coding education involves defining specific, measurable goals. Vague aspirations such as “learn to code” or “become a programmer” provide insufficient direction for structuring a learning path. Instead, successful learners typically begin by identifying concrete outcomes they wish to achieve – for example, “build a personal portfolio website,” “create a mobile app for tracking expenses,” or “analyze datasets using Python.” These tangible objectives serve multiple purposes: they help learners select appropriate courses and resources, provide motivational milestones to celebrate, and create portfolio pieces that demonstrate competence to potential employers.

B. Choosing the Right Starting Point

The question of which programming language to learn first generates considerable debate within the developer community. Conventional wisdom once suggested starting with languages considered pedagogically ideal for beginners, such as Pascal or Scheme. However, contemporary educators increasingly advocate for a more pragmatic approach: selecting a language aligned with one’s ultimate goals. Aspiring web developers might begin with JavaScript and HTML/CSS, while those interested in data analysis would benefit from starting with Python or R. This goal-oriented selection ensures that early learning efforts yield practical, applicable skills rather than abstract knowledge that may not transfer readily to real-world applications.

C. Implementing Active Learning Techniques

Passive consumption of educational content – watching video tutorials or reading documentation without hands-on practice – represents one of the most common pitfalls in online coding education. Cognitive science research consistently demonstrates that active engagement with material significantly enhances both understanding and long-term retention. Effective strategies include typing out example code rather than copying and pasting, modifying tutorial projects to add new features or change functionality, and most importantly, attempting to build small projects independently before consulting reference materials. This approach, sometimes called “productive failure,” helps learners develop problem-solving resilience and genuine understanding rather than superficial familiarity.

D. Utilizing Spaced Repetition

The spacing effect – the observation that learning is more effective when study sessions are distributed over time rather than concentrated intensively – has profound implications for online coding education. Many enthusiastic beginners attempt to learn programming through marathon sessions, spending entire weekends working through tutorials. While this approach may produce a subjective feeling of progress, neuroscientific research indicates that knowledge consolidation occurs primarily during intervals between study sessions. More effective learners space out their practice, perhaps coding for 60-90 minutes daily rather than 10 hours every Saturday. This distributed practice allows the brain to solidify neural pathways associated with programming concepts and prevents the cognitive fatigue that impairs learning during extended sessions.

E. Engaging with Programming Communities

The collaborative nature of professional software development stands in stark contrast to the often solitary experience of online learning. Successful self-taught programmers actively seek to bridge this gap by engaging with developer communities both online and, where possible, in person. Participating in online forums like Stack Overflow, joining local coding meetups, contributing to open-source projects, and attending hackathons provide invaluable opportunities to observe how experienced developers approach problems, learn industry best practices, and develop the communication skills essential for team-based work. Moreover, these interactions often yield networking opportunities that can facilitate career transitions into technology roles.

F. Building Progressive Projects

Educational theorist Lev Vygotsky introduced the concept of the “zone of proximal development” – the space between what a learner can do independently and what they can achieve with guidance. Effective online learners intuitively apply this principle by selecting projects that are challenging yet achievable with their current skill level plus some research and problem-solving. A common mistake involves attempting overly ambitious projects that require expertise far beyond one’s current abilities, leading to frustration and abandonment. Instead, successful learners build a progression of increasingly complex projects, each one incorporating a few new concepts or techniques. This incremental approach maintains motivation through regular accomplishments while steadily expanding competency.

G. Developing Debugging Skills

Perhaps the most underappreciated aspect of programming education involves learning to effectively debug code – the process of identifying and resolving errors. Beginners often view bugs as failures or evidence of inadequacy, but professional developers recognize that debugging constitutes a substantial portion of actual programming work. Effective online learners cultivate systematic approaches to debugging: carefully reading error messages, using print statements or debuggers to inspect program state, isolating problematic code segments, and searching for similar issues others have encountered. These metacognitive skills – thinking about and regulating one’s own learning process – often prove more valuable than knowledge of specific syntax or functions.

The landscape of online coding education continues to evolve rapidly, with new platforms, pedagogical approaches, and technologies emerging constantly. However, these fundamental principles of effective learning remain relatively constant. By establishing clear goals, selecting appropriate starting points, engaging actively with material, spacing practice over time, participating in communities, building progressive projects, and developing robust debugging skills, aspiring programmers can navigate the abundance of available resources and transform themselves from curious beginners into competent, employable developers.

Questions 14-20

The passage has seven sections, A-G. Which section contains the following information?

Write the correct letter, A-G.

14. An explanation of why consistent short practice sessions are more effective than longer infrequent ones
15. The importance of selecting programming languages based on career objectives
16. A description of how error-solving abilities represent a crucial but often overlooked skill
17. The need to set specific and measurable learning targets rather than general ambitions
18. Ways to counteract the isolation that comes with independent online study
19. The recommendation to manually write code rather than simply copying examples
20. The concept of choosing projects that are difficult but not impossibly beyond current abilities

Questions 21-24

Complete the summary below.

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

Effective online coding education requires several strategic approaches. Learners should avoid (21) __ such as just watching videos without practicing. Instead, they should engage in hands-on activities and even embrace (22) __, which involves attempting to build projects before looking at solutions. Educational research shows that (23) __ occurs mainly during breaks between study sessions, not during the sessions themselves. Additionally, participating in developer communities helps learners observe how professionals (24) __ and learn industry standards.

Questions 25-26

Choose TWO letters, A-E.

Which TWO challenges for online coding learners are mentioned in the passage?

A. The high cost of quality online courses
B. Difficulty in choosing which programming language to learn
C. Lack of internet access in developing countries
D. Attempting projects that are too ambitious for their current level
E. Insufficient time for learning due to work commitments

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Chiến lược học lập trình trực tuyến hiệu quả và phương pháp tự học coding online

PASSAGE 3 – The Neuroscience and Pedagogy of Online Code Acquisition

Độ khó: Hard (Band 7.0-9.0)

Thời gian đề xuất: 23-25 phút

The exponential proliferation of online coding education platforms over the past decade has catalyzed unprecedented access to programming knowledge, yet the efficacy of these digital pedagogical approaches remains subject to rigorous academic scrutiny. Neuroscientific investigations into skill acquisition, combined with educational psychology research, are beginning to illuminate both the cognitive mechanisms underlying successful programming education and the optimal instructional designs that facilitate this complex form of knowledge construction. Understanding these intricate dynamics is essential for developing maximally effective online learning environments and for helping individual learners optimize their educational strategies.

At its neurological foundation, learning to program involves the development of multiple overlapping cognitive competencies that engage disparate regions of the brain’s cortical architecture. Functional neuroimaging studies using fMRI technology have demonstrated that programming tasks activate areas associated with language processing (Broca’s area and Wernicke’s area), mathematical reasoning (bilateral inferior parietal lobules), working memory (dorsolateral prefrontal cortex), and error detection (anterior cingulate cortex). This multimodal activation pattern helps explain why programming proficiency correlates with, yet remains distinct from, traditional measures of linguistic ability or mathematical aptitude. The brain, in effect, must construct novel neural pathways that integrate these various cognitive functions in ways not typically required by other intellectual activities.

The acquisition of programming expertise follows a trajectory that educational psychologist Anders Ericsson’s research on deliberate practice helps contextualize. Ericsson’s work, spanning decades of investigation into expertise development across domains from chess to music, demonstrates that elite performance results not merely from accumulated experience but from specific types of focused, effortful practice characterized by immediate feedback, concentration on technique, and systematic identification of weaknesses. In the programming context, this translates to practices such as code review, systematic debugging, and incremental problem-solving – activities that many self-directed online learners, left to their own devices, may insufficiently prioritize in favor of more superficially rewarding activities like completing tutorial after tutorial.

Cognitive load theory, pioneered by educational psychologist John Sweller, provides another crucial theoretical framework for understanding the challenges and opportunities of online coding education. This theory posits that human working memory possesses inherent limitations in the amount of information it can process simultaneously. When instructional materials present excessive intrinsic cognitive load (complexity inherent to the material), extraneous cognitive load (poor instructional design), or insufficient germane cognitive load (mental effort devoted to schema construction), learning becomes suboptimal. Online coding platforms must therefore carefully calibrate the complexity of programming concepts introduced, minimize distracting interface elements, and provide scaffolding that helps learners construct mental schemas – organized knowledge structures that allow programmers to chunk information and thereby circumvent working memory limitations.

The phenomenon of transfer – the ability to apply knowledge gained in one context to novel situations – represents both a paramount objective and a persistent challenge in programming education. Educational researchers distinguish between “near transfer” (applying knowledge to closely similar problems) and “far transfer” (applying knowledge to fundamentally different domains). While online coding courses typically succeed in facilitating near transfer – students can solve problems similar to those encountered in tutorials – far transfer remains elusive. This limitation helps explain a common frustration among self-taught programmers: despite completing numerous online courses, they struggle when confronted with real-world projects that don’t neatly correspond to tutorial examples. Addressing this transfer problem requires instructional approaches that emphasize underlying principles rather than surface features, provide varied practice contexts, and encourage metacognitive reflection on problem-solving strategies.

The social constructivist perspective on learning, particularly as articulated by psychologist Lev Vygotsky, offers valuable insights into the role of community and collaboration in online coding education. Vygotsky’s concept of the zone of proximal development suggests that optimal learning occurs through social interaction with more knowledgeable others who can provide appropriate scaffolding. This theory problematizes purely solitary online learning experiences and validates the intuitions of many successful self-taught programmers who actively seek mentorship, participate in coding communities, and engage in collaborative projects. Indeed, research by computer science education scholars has consistently demonstrated that peer instruction and collaborative problem-solving enhance both learning outcomes and persistence rates in programming courses.

Recent innovations in online coding education increasingly leverage artificial intelligence to provide adaptive, personalized learning experiences that approximate aspects of human tutoring. Intelligent tutoring systems can analyze learners’ code in real-time, identify common misconceptions, and provide targeted feedback that addresses individual knowledge gaps. Some systems employ natural language processing to interpret students’ questions and provide relevant explanations, while others use machine learning algorithms to predict which learners are at risk of disengagement and intervene proactively. However, these AI-driven approaches also raise important questions about algorithmic bias, data privacy, and the potential homogenization of learning pathways that may not accommodate diverse cognitive styles and cultural contexts.

The long-term retention of programming skills presents another dimension requiring careful consideration. Research on memory consolidation suggests that knowledge undergoes transformation during sleep and subsequent rest periods, with initially fragile memories becoming progressively more stable and integrated into existing knowledge structures through a process called systems consolidation. This neurological reality underscores the importance of distributed practice – spacing learning sessions over extended periods – rather than massed practice (cramming). Furthermore, the testing effect – the finding that retrieving information from memory enhances subsequent retention more effectively than additional study – suggests that online platforms should incorporate frequent quizzes, coding challenges, and project milestones that require learners to actively recall and apply previously learned concepts.

As online coding education continues to mature, the integration of insights from neuroscience, cognitive psychology, and educational research becomes increasingly critical. The most pedagogically sophisticated platforms will likely feature multimodal instructional approaches that accommodate diverse learning preferences, adaptive systems that personalize content and pacing, robust social features that facilitate community learning, and assessment mechanisms that promote both skill acquisition and accurate self-evaluation. For individual learners, understanding the cognitive science underlying effective learning can empower more strategic educational choices and realistic expectations about the temporal investment and deliberate effort required to achieve genuine programming proficiency.

Questions 27-31

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

27. According to the passage, what do fMRI studies reveal about programming tasks?

    • A. They primarily activate mathematical reasoning areas of the brain
    • B. They engage multiple brain regions associated with different cognitive functions
    • C. They require less brain activity than other intellectual activities
    • D. They only activate areas related to language processing

28. What does Anders Ericsson’s research on deliberate practice emphasize?

    • A. The quantity of practice hours is more important than quality
    • B. Elite performance comes mainly from natural talent
    • C. Focused, effortful practice with feedback is essential for expertise
    • D. Tutorial completion is the most effective learning method

29. According to cognitive load theory, what should online coding platforms do?

    • A. Increase the complexity of all materials to challenge learners
    • B. Remove all interface elements to minimize distractions
    • C. Balance concept complexity, design clarity, and schema-building support
    • D. Focus exclusively on intrinsic cognitive load

30. What is the main challenge regarding “transfer” in programming education?

    • A. Students cannot solve any problems outside of tutorials
    • B. Near transfer is impossible to achieve in online courses
    • C. Far transfer to fundamentally different problems remains difficult
    • D. Online courses completely fail at teaching transferable skills

31. What role does artificial intelligence play in modern online coding education?

    • A. It has completely replaced human instructors
    • B. It provides personalized feedback and identifies learning gaps
    • C. It eliminates the need for peer collaboration
    • D. It guarantees perfect learning outcomes for all students

Questions 32-36

Complete the summary using the list of phrases, A-J, below.

Recent research into online coding education has revealed important insights about how people learn programming. Neurological studies show that programming involves (32) __ that integrate various cognitive functions. The theory of cognitive load suggests that instructional materials must be carefully designed to avoid overloading (33) __. Social constructivist theory emphasizes the importance of (34) __ in the learning process. Research on memory shows that (35) __ is more effective than cramming for long-term retention. Additionally, the testing effect demonstrates that (36) __ helps strengthen memory better than passive review.

A. working memory capacity
B. novel neural pathways
C. immediate financial rewards
D. distributed practice over time
E. social interaction and mentorship
F. expensive educational technology
G. actively retrieving information
H. avoiding all challenging content
I. memorizing syntax rules
J. watching video lectures repeatedly

Questions 37-40

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

Write:

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

37. Programming proficiency is completely identical to linguistic and mathematical abilities.
38. Purely solitary online learning experiences may not be optimal according to Vygotsky’s theories.
39. Artificial intelligence in education raises concerns about algorithmic bias and data privacy.
40. All online coding platforms currently use the most advanced neuroscientific findings in their design.

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3. Answer Keys – Đáp Án

PASSAGE 1: Questions 1-13

1. TRUE
2. NOT GIVEN
3. TRUE
4. NOT GIVEN
5. TRUE
6. FALSE
7. error messages / helpful error messages
8. peer-to-peer interaction
9. gamification elements
10. completion rate / completion rates
11. B
12. C
13. C

PASSAGE 2: Questions 14-26

14. D
15. B
16. G
17. A
18. E
19. C
20. F
21. passive consumption
22. productive failure
23. knowledge consolidation
24. approach problems
25. B, D (in any order)
26. B, D (in any order)

PASSAGE 3: Questions 27-40

27. B
28. C
29. C
30. C
31. B
32. B
33. A
34. E
35. D
36. G
37. NO
38. YES
39. YES
40. NOT GIVEN

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4. Giải Thích Đáp Án Chi Tiết

Passage 1 – Giải Thích

Câu 1: TRUE

• Dạng câu hỏi: True/False/Not Given
• Từ khóa: online coding platforms, started, 2010
• Vị trí trong bài: Đoạn 2, dòng 1-2
• Giải thích: Bài đọc nói rõ “The emergence of online coding platforms began in earnest around 2010” – sự xuất hiện của các nền tảng học lập trình trực tuyến bắt đầu nghiêm túc vào khoảng năm 2010. Câu hỏi sử dụng từ “started becoming popular” để paraphrase “began in earnest”.

Câu 2: NOT GIVEN

• Dạng câu hỏi: True/False/Not Given
• Từ khóa: traditional computer science degrees, more effective
• Vị trí trong bài: Đoạn 2
• Giải thích: Bài đọc đề cập đến việc các khóa học truyền thống “expensive, time-consuming, and often inaccessible” nhưng không so sánh tính hiệu quả (effectiveness) giữa hai hình thức. Đây là thông tin không được đề cập.

Câu 3: TRUE

• Dạng câu hỏi: True/False/Not Given
• Từ khóa: self-paced learning, beneficial, career changers
• Vị trí trong bài: Đoạn 3, dòng 2-5
• Giải thích: Bài đọc nói “This flexibility has proven especially valuable for career changers” – sự linh hoạt này đặc biệt có giá trị cho những người muốn chuyển nghề. “Beneficial” paraphrase “valuable”, “people who want to change careers” paraphrase “career changers”.

Câu 4: NOT GIVEN

• Dạng câu hỏi: True/False/Not Given
• Từ khóa: all online platforms, charge fees, advanced courses
• Vị trí trong bài: Không có thông tin cụ thể
• Giải thích: Bài đọc đề cập “free, interactive tutorials” nhưng không nói về chính sách thu phí của tất cả các nền tảng, đặc biệt là cho các khóa học nâng cao.

Câu 5: TRUE

• Dạng câu hỏi: True/False/Not Given
• Từ khóa: write and test code, web browsers
• Vị trí trong bài: Đoạn 4, dòng 2-4
• Giải thích: Bài đọc nói “Most platforms now feature built-in code editors where students can write programs directly in their web browsers” – hầu hết các nền tảng có trình soạn thảo mã tích hợp nơi học viên có thể viết chương trình trực tiếp trong trình duyệt web.

Câu 6: FALSE

• Dạng câu hỏi: True/False/Not Given
• Từ khóa: completely eliminated, global economic inequality
• Vị trí trong bài: Đoạn 6, câu cuối
• Giải thích: Bài đọc nói “has the potential to reduce global economic inequality” (có tiềm năng giảm bất bình đẳng kinh tế toàn cầu) chứ không phải “completely eliminated” (hoàn toàn loại bỏ). Đây là thông tin mâu thuẫn.

Câu 7: error messages / helpful error messages

• Dạng câu hỏi: Sentence Completion
• Từ khóa: platforms provide, incorrect code
• Vị trí trong bài: Đoạn 4, dòng 6-7
• Giải thích: “the platform typically provides helpful error messages and hints” – nền tảng thường cung cấp thông báo lỗi hữu ích và gợi ý.

Câu 8: peer-to-peer interaction

• Dạng câu hỏi: Sentence Completion
• Từ khóa: forums, reduces isolation
• Vị trí trong bài: Đoạn 5, dòng 2-4
• Giải thích: “This peer-to-peer interaction helps combat one of the main challenges of online learning: the sense of isolation” – tương tác ngang hàng giúp chống lại cảm giác cô lập.

Câu 9: gamification elements

• Dạng câu hỏi: Sentence Completion
• Từ khóa: points and badges, maintain engagement
• Vị trí trong bài: Đoạn 5, dòng 5-7
• Giải thích: “many platforms have incorporated gamification elements such as points, badges, and progress tracking” – nhiều nền tảng đã kết hợp các yếu tố game hóa như điểm, huy hiệu.

Câu 10: completion rate / completion rates

• Dạng câu hỏi: Sentence Completion
• Từ khóa: 5-15%, free online courses
• Vị trí trong bài: Đoạn 7, dòng 1-2
• Giải thích: “Completion rates for free online courses remain relatively low, typically ranging between 5-15%” – tỷ lệ hoàn thành cho các khóa học trực tuyến miễn phí vẫn còn thấp.

Câu 11: B

• Dạng câu hỏi: Multiple Choice
• Từ khóa: main problem, early platforms addressed
• Vị trí trong bài: Đoạn 2, dòng 1-3
• Giải thích: “recognized that there was a significant gap between the demand for programming skills and the availability of affordable, flexible learning options” – nhận ra khoảng cách đáng kể giữa nhu cầu về kỹ năng lập trình và sự sẵn có của các lựa chọn học tập linh hoạt, giá cả phải chăng.

Câu 12: C

• Dạng câu hỏi: Multiple Choice
• Từ khóa: practical problem-solving skills
• Vị trí trong bài: Đoạn 4, dòng 2-5
• Giải thích: “built-in code editors… receiving immediate feedback… This hands-on approach… helps learners develop practical problem-solving skills” – trình soạn thảo mã tích hợp với phản hồi tức thì giúp phát triển kỹ năng giải quyết vấn đề thực tế.

Câu 13: C

• Dạng câu hỏi: Multiple Choice
• Từ khóa: challenge mentioned
• Vị trí trong bài: Đoạn 7, dòng 1-2
• Giải thích: “Completion rates for free online courses remain relatively low, typically ranging between 5-15%” – một thách thức được đề cập là tỷ lệ hoàn thành thấp.

Giải đáp chi tiết các câu hỏi IELTS Reading về học lập trình trực tuyến

Passage 2 – Giải Thích

Câu 14: D

• Dạng câu hỏi: Matching Headings/Information
• Từ khóa: short practice sessions, more effective, longer infrequent ones
• Vị trí trong bài: Section D – “Utilizing Spaced Repetition”
• Giải thích: Đoạn D giải thích về spacing effect và tại sao “coding for 60-90 minutes daily rather than 10 hours every Saturday” hiệu quả hơn. Đây là lý do tại sao các buổi luyện tập ngắn nhất quán hiệu quả hơn các buổi dài không thường xuyên.

Câu 15: B

• Dạng câu hỏi: Matching Headings/Information
• Từ khóa: selecting programming languages, career objectives
• Vị trí trong bài: Section B – “Choosing the Right Starting Point”
• Giải thích: Đoạn B thảo luận về việc “selecting a language aligned with one’s ultimate goals” – chọn ngôn ngữ phù hợp với mục tiêu nghề nghiệp.

Câu 16: G

• Dạng câu hỏi: Matching Headings/Information
• Từ khóa: error-solving, crucial but overlooked
• Vị trí trong bài: Section G – “Developing Debugging Skills”
• Giải thích: Đoạn G mô tả debugging là “the most underappreciated aspect” – khía cạnh bị đánh giá thấp nhất của giáo dục lập trình.

Câu 17: A

• Dạng câu hỏi: Matching Headings/Information
• Từ khóa: specific measurable targets, not general ambitions
• Vị trí trong bài: Section A – “Establishing Clear Objectives”
• Giải thích: Đoạn A nói về việc “defining specific, measurable goals” thay vì “vague aspirations” – xác định mục tiêu cụ thể, có thể đo lường được thay vì khát vọng mơ hồ.

Câu 18: E

• Dạng câu hỏi: Matching Headings/Information
• Từ khóa: counteract isolation, independent online study
• Vị trí trong bài: Section E – “Engaging with Programming Communities”
• Giải thích: Đoạn E thảo luận về “bridge this gap” giữa collaborative nature của phát triển phần mềm và “solitary experience” của học trực tuyến.

Câu 19: C

• Dạng câu hỏi: Matching Headings/Information
• Từ khóa: manually write code, not copying
• Vị trí trong bài: Section C – “Implementing Active Learning Techniques”
• Giải thích: Đoạn C đề cập “typing out example code rather than copying and pasting” – gõ mã ví dụ thay vì sao chép và dán.

Câu 20: F

• Dạng câu hỏi: Matching Headings/Information
• Từ khóa: projects difficult but not impossible, current abilities
• Vị trí trong bài: Section F – “Building Progressive Projects”
• Giải thích: Đoạn F giải thích về “zone of proximal development” và chọn “projects that are challenging yet achievable” – dự án khó khăn nhưng có thể đạt được.

Câu 21: passive consumption

• Dạng câu hỏi: Summary Completion
• Từ khóa: avoid, watching videos without practicing
• Vị trí trong bài: Section C, dòng 1
• Giải thích: “Passive consumption of educational content – watching video tutorials… without hands-on practice – represents one of the most common pitfalls”.

Câu 22: productive failure

• Dạng câu hỏi: Summary Completion
• Từ khóa: attempting to build before solutions
• Vị trí trong bài: Section C, dòng 5-6
• Giải thích: “This approach, sometimes called ‘productive failure,’ helps learners develop problem-solving resilience”.

Câu 23: knowledge consolidation

• Dạng câu hỏi: Summary Completion
• Từ khóa: occurs mainly during breaks
• Vị trí trong bài: Section D, dòng 4-5
• Giải thích: “neuroscientific research indicates that knowledge consolidation occurs primarily during intervals between study sessions”.

Câu 24: approach problems

• Dạng câu hỏi: Summary Completion
• Từ khóa: observe how professionals
• Vị trí trong bài: Section E, dòng 4-5
• Giải thích: “provide invaluable opportunities to observe how experienced developers approach problems”.

Câu 25-26: B, D

• Dạng câu hỏi: Multiple Choice (choose TWO)
• Từ khóa: challenges mentioned
• Vị trí trong bài: Section B và Section F
• Giải thích:
  • B: “The question of which programming language to learn first generates considerable debate” (Section B)
  • D: “A common mistake involves attempting overly ambitious projects” (Section F)

Passage 3 – Giải Thích

Câu 27: B

• Dạng câu hỏi: Multiple Choice
• Từ khóa: fMRI studies, reveal
• Vị trí trong bài: Đoạn 2, dòng 2-5
• Giải thích: “programming tasks activate areas associated with language processing… mathematical reasoning… working memory… and error detection” – các nhiệm vụ lập trình kích hoạt các khu vực liên quan đến nhiều chức năng nhận thức khác nhau. Đáp án B phản ánh chính xác “multimodal activation pattern”.

Câu 28: C

• Dạng câu hỏi: Multiple Choice
• Từ khóa: Anders Ericsson, deliberate practice, emphasize
• Vị trí trong bài: Đoạn 3, dòng 3-6
• Giải thích: “elite performance results… from specific types of focused, effortful practice characterized by immediate feedback” – hiệu suất xuất sắc đến từ loại thực hành tập trung, nỗ lực cụ thể với phản hồi tức thì.

Câu 29: C

• Dạng câu hỏi: Multiple Choice
• Từ khóa: cognitive load theory, should do
• Vị trí trong bài: Đoạn 4, dòng 6-9
• Giải thích: “Online coding platforms must therefore carefully calibrate the complexity… minimize distracting interface elements, and provide scaffolding” – các nền tảng phải cân bằng độ phức tạp, thiết kế rõ ràng và hỗ trợ xây dựng schema.

Câu 30: C

• Dạng câu hỏi: Multiple Choice
• Từ khóa: main challenge, transfer
• Vị trí trong bài: Đoạn 5, dòng 3-5
• Giải thích: “While online coding courses typically succeed in facilitating near transfer… far transfer remains elusive” – chuyển giao xa vẫn khó nắm bắt.

Câu 31: B

• Dạng câu hỏi: Multiple Choice
• Từ khóa: artificial intelligence, role
• Vị trí trong bài: Đoạn 7, dòng 2-4
• Giải thích: “Intelligent tutoring systems can analyze learners’ code… identify common misconceptions, and provide targeted feedback” – hệ thống hướng dẫn thông minh có thể phân tích mã, xác định sai lầm và cung cấp phản hồi được nhắm mục tiêu.

Câu 32: B (novel neural pathways)

• Dạng câu hỏi: Summary Completion
• Từ khóa: programming involves
• Vị trí trong bài: Đoạn 2, câu cuối
• Giải thích: “The brain… must construct novel neural pathways that integrate these various cognitive functions”.

Câu 33: A (working memory capacity)

• Dạng câu hỏi: Summary Completion
• Từ khóa: avoid overloading
• Vị trí trong bài: Đoạn 4, dòng 2-3
• Giải thích: “human working memory possesses inherent limitations in the amount of information it can process”.

Câu 34: E (social interaction and mentorship)

• Dạng câu hỏi: Summary Completion
• Từ khóa: social constructivist, importance of
• Vị trí trong bài: Đoạn 6, dòng 2-4
• Giải thích: “optimal learning occurs through social interaction with more knowledgeable others who can provide appropriate scaffolding”.

Câu 35: D (distributed practice over time)

• Dạng câu hỏi: Summary Completion
• Từ khóa: more effective than cramming
• Vị trí trong bài: Đoạn 8, dòng 4-5
• Giải thích: “the importance of distributed practice – spacing learning sessions over extended periods – rather than massed practice”.

Câu 36: G (actively retrieving information)

• Dạng câu hỏi: Summary Completion
• Từ khóa: testing effect, strengthen memory
• Vị trí trong bài: Đoạn 8, dòng 5-7
• Giải thích: “the testing effect – the finding that retrieving information from memory enhances subsequent retention”.

Câu 37: NO

• Dạng câu hỏi: Yes/No/Not Given
• Từ khóa: completely identical, linguistic and mathematical abilities
• Vị trí trong bài: Đoạn 2, dòng 5-6
• Giải thích: Bài viết nói “programming proficiency correlates with, yet remains distinct from, traditional measures of linguistic ability or mathematical aptitude” – lập trình có tương quan nhưng vẫn khác biệt với khả năng ngôn ngữ và toán học. “Completely identical” mâu thuẫn với “distinct from”.

Câu 38: YES

• Dạng câu hỏi: Yes/No/Not Given
• Từ khóa: purely solitary, not optimal, Vygotsky
• Vị trí trong bài: Đoạn 6, dòng 4-5
• Giải thích: “This theory problematizes purely solitary online learning experiences” – lý thuyết này đặt vấn đề với trải nghiệm học trực tuyến hoàn toàn đơn độc. Điều này đồng ý với quan điểm rằng học đơn độc có thể không tối ưu.

Câu 39: YES

• Dạng câu hỏi: Yes/No/Not Given
• Từ khóa: AI, concerns, algorithmic bias, data privacy
• Vị trí trong bài: Đoạn 7, dòng 6-7
• Giải thích: “these AI-driven approaches also raise important questions about algorithmic bias, data privacy” – các phương pháp dựa trên AI đặt ra câu hỏi quan trọng về thiên lệch thuật toán và quyền riêng tư dữ liệu.

Câu 40: NOT GIVEN

• Dạng câu hỏi: Yes/No/Not Given
• Từ khóa: all platforms, currently use, most advanced findings
• Vị trí trong bài: Không có thông tin cụ thể
• Giải thích: Bài viết nói về “most pedagogically sophisticated platforms will likely feature” (các nền tảng tinh vi nhất về mặt sư phạm có khả năng sẽ có) – đây là dự đoán tương lai, không xác nhận rằng tất cả các nền tảng hiện tại đang sử dụng các phát hiện khoa học thần kinh tiên tiến nhất.

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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
fundamentally	adv	/ˌfʌndəˈmentəli/	Về cơ bản, căn bản	The digital revolution has fundamentally transformed the way people acquire new skills	fundamentally different, fundamentally change
exponential	adj	/ˌekspəˈnenʃəl/	Theo cấp số nhân, tăng nhanh	Online coding education has experienced exponential growth	exponential growth, exponential increase
accessible	adj	/əkˈsesəbl/	Có thể tiếp cận, dễ dàng	Making programming knowledge accessible to millions	easily accessible, widely accessible
emergence	n	/ɪˈmɜːdʒəns/	Sự xuất hiện, sự nổi lên	The emergence of online coding platforms began in 2010	the emergence of, rapid emergence
interactive	adj	/ˌɪntərˈæktɪv/	Tương tác	Offered free, interactive tutorials	interactive learning, interactive platform
self-paced	adj	/ˌself ˈpeɪst/	Tự điều chỉnh tốc độ	The self-paced nature of online learning	self-paced learning, self-paced course
career changers	n	/kəˈrɪr ˈtʃeɪndʒərz/	Người chuyển đổi nghề nghiệp	Flexibility is valuable for career changers	support career changers, help career changers
immediate feedback	n	/ɪˈmiːdiət ˈfiːdbæk/	Phản hồi tức thì	Receiving immediate feedback on their code	provide immediate feedback, get immediate feedback
hands-on approach	n	/hændz ɒn əˈproʊtʃ/	Phương pháp thực hành	This hands-on approach mirrors professional work	take a hands-on approach, hands-on experience
peer-to-peer	adj	/pɪr tə pɪr/	Ngang hàng, đồng đẳng	This peer-to-peer interaction helps combat isolation	peer-to-peer learning, peer-to-peer support
dropout rates	n	/ˈdrɒpaʊt reɪts/	Tỷ lệ bỏ học	Higher dropout rates in online learning	reduce dropout rates, high dropout rates
democratization	n	/dɪˌmɒkrətaɪˈzeɪʃən/	Dân chủ hóa, phổ cập	This democratization of opportunity	democratization of education, democratization of access

Passage 2 – Essential Vocabulary

Từ vựng	Loại từ	Phiên âm	Nghĩa tiếng Việt	Ví dụ từ bài	Collocation
proliferation	n	/prəˌlɪfəˈreɪʃən/	Sự tăng nhanh, lan tràn	The proliferation of online coding resources	rapid proliferation, proliferation of
analysis paralysis	n	/əˈnæləsɪs pəˈræləsɪs/	Tê liệt vì phân tích quá nhiều	Can create analysis paralysis for aspiring developers	suffer from analysis paralysis, avoid analysis paralysis
retention	n	/rɪˈtenʃən/	Sự ghi nhớ, lưu giữ	Maximize retention and skill development	improve retention, knowledge retention
tangible objectives	n	/ˈtændʒəbl əbˈdʒektɪvz/	Mục tiêu cụ thể	Identifying tangible objectives they wish to achieve	set tangible objectives, achieve tangible objectives
pragmatic approach	n	/præɡˈmætɪk əˈproʊtʃ/	Cách tiếp cận thực dụng	Educators advocate for a more pragmatic approach	take a pragmatic approach, adopt a pragmatic approach
goal-oriented	adj	/ɡoʊl ˈɔːriəntɪd/	Hướng đến mục tiêu	This goal-oriented selection ensures practical skills	goal-oriented learning, goal-oriented approach
passive consumption	n	/ˈpæsɪv kənˈsʌmpʃən/	Tiêu thụ thụ động	Passive consumption of educational content	avoid passive consumption, passive consumption of information
pitfalls	n	/ˈpɪtfɔːlz/	Cạm bẫy, sai lầm	One of the most common pitfalls	avoid pitfalls, common pitfalls
cognitive science	n	/ˈkɒɡnɪtɪv ˈsaɪəns/	Khoa học nhận thức	Cognitive science research demonstrates	cognitive science findings, cognitive science research
productive failure	n	/prəˈdʌktɪv ˈfeɪljər/	Thất bại mang tính xây dựng	This approach, called productive failure	embrace productive failure, productive failure approach
spacing effect	n	/ˈspeɪsɪŋ ɪˈfekt/	Hiệu ứng khoảng cách (học tập)	The spacing effect – learning is more effective when distributed	utilize the spacing effect, spacing effect demonstrates
consolidation	n	/kənˌsɒlɪˈdeɪʃən/	Sự củng cố	Knowledge consolidation occurs during rest	memory consolidation, knowledge consolidation
solitary experience	n	/ˈsɒlɪteri ɪkˈspɪriəns/	Trải nghiệm đơn độc	The often solitary experience of online learning	avoid solitary experience, overcome solitary experience
open-source projects	n	/ˈoʊpən sɔːrs ˈprɒdʒekts/	Dự án nguồn mở	Contributing to open-source projects	contribute to open-source projects, work on open-source projects
zone of proximal development	n	/zoʊn əv ˈprɒksɪməl dɪˈveləpmənt/	Vùng phát triển gần kề	Vygotsky introduced the zone of proximal development	within the zone of proximal development, leverage zone of proximal development

Passage 3 – Essential Vocabulary

Từ vựng	Loại từ	Phiên âm	Nghĩa tiếng Việt	Ví dụ từ bài	Collocation
exponential proliferation	n	/ˌekspəˈnenʃəl prəˌlɪfəˈreɪʃən/	Sự lan tràn theo cấp số nhân	The exponential proliferation of platforms	exponential proliferation of, witness exponential proliferation
catalyzed	v	/ˈkætəlaɪzd/	Xúc tác, thúc đẩy	Has catalyzed unprecedented access	catalyze change, catalyze development
efficacy	n	/ˈefɪkəsi/	Hiệu quả, hiệu lực	The efficacy of these approaches	demonstrate efficacy, evaluate efficacy
rigorous academic scrutiny	n	/ˈrɪɡərəs ˌækəˈdemɪk ˈskruːtəni/	Sự xem xét học thuật nghiêm ngặt	Remains subject to rigorous academic scrutiny	undergo rigorous scrutiny, withstand rigorous scrutiny
neuroscientific investigations	n	/ˌnjʊroʊˌsaɪənˈtɪfɪk ɪnˌvestɪˈɡeɪʃənz/	Các nghiên cứu khoa học thần kinh	Neuroscientific investigations into skill acquisition	conduct neuroscientific investigations, neuroscientific investigations reveal
cognitive mechanisms	n	/ˈkɒɡnɪtɪv ˈmekənɪzəmz/	Cơ chế nhận thức	The cognitive mechanisms underlying learning	understand cognitive mechanisms, cognitive mechanisms involved
cortical architecture	n	/ˈkɔːtɪkəl ˈɑːkɪtektʃər/	Cấu trúc vỏ não	Disparate regions of the brain’s cortical architecture	cortical architecture of, complex cortical architecture
functional neuroimaging	n	/ˈfʌŋkʃənəl ˌnjʊroʊˈɪmɪdʒɪŋ/	Hình ảnh thần kinh chức năng	Functional neuroimaging studies using fMRI	functional neuroimaging reveals, functional neuroimaging techniques
multimodal activation	n	/ˌmʌltiˈmoʊdəl ˌæktɪˈveɪʃən/	Kích hoạt đa phương thức	This multimodal activation pattern	multimodal activation patterns, show multimodal activation
deliberate practice	n	/dɪˈlɪbərət ˈpræktɪs/	Thực hành có chủ đích	Anders Ericsson’s research on deliberate practice	engage in deliberate practice, deliberate practice leads to
cognitive load theory	n	/ˈkɒɡnɪtɪv loʊd ˈθɪəri/	Lý thuyết tải nhận thức	Cognitive load theory provides a framework	apply cognitive load theory, cognitive load theory suggests
intrinsic cognitive load	n	/ɪnˈtrɪnsɪk ˈkɒɡnɪtɪv loʊd/	Tải nhận thức nội tại	Excessive intrinsic cognitive load	manage intrinsic cognitive load, reduce intrinsic cognitive load
scaffolding	n	/ˈskæfəldɪŋ/	Giàn giáo hỗ trợ (học tập)	Provide scaffolding that helps learners	provide scaffolding, instructional scaffolding
mental schemas	n	/ˈmentl ˈskiːməz/	Sơ đồ tư duy	Construct mental schemas	develop mental schemas, organized mental schemas
transfer	n	/trænsˈfɜːr/	Sự chuyển giao (kiến thức)	The phenomenon of transfer	facilitate transfer, knowledge transfer
far transfer	n	/fɑːr trænsˈfɜːr/	Chuyển giao xa	Far transfer remains elusive	achieve far transfer, far transfer of skills
metacognitive reflection	n	/ˌmetəˈkɒɡnɪtɪv rɪˈflekʃən/	Suy nghĩ siêu nhận thức	Encourage metacognitive reflection	promote metacognitive reflection, metacognitive reflection on
social constructivist	adj	/ˈsoʊʃəl kənˈstrʌktɪvɪst/	Thuộc trường phái xây dựng xã hội	The social constructivist perspective	social constructivist approach, social constructivist theory
intelligent tutoring systems	n	/ɪnˈtelɪdʒənt ˈtuːtərɪŋ ˈsɪstəmz/	Hệ thống hướng dẫn thông minh	Intelligent tutoring systems can analyze code	develop intelligent tutoring systems, intelligent tutoring systems provide
algorithmic bias	n	/ˌælɡəˈrɪðmɪk ˈbaɪəs/	Thiên lệch thuật toán	Questions about algorithmic bias	address algorithmic bias, algorithmic bias in AI
systems consolidation	n	/ˈsɪstəmz kənˌsɒlɪˈdeɪʃən/	Củng cố hệ thống (trí nhớ)	Through a process called systems consolidation	systems consolidation occurs, facilitate systems consolidation
distributed practice	n	/dɪˈstrɪbjətɪd ˈpræktɪs/	Thực hành phân tán	The importance of distributed practice	engage in distributed practice, distributed practice versus massed practice
testing effect	n	/ˈtestɪŋ ɪˈfekt/	Hiệu ứng kiểm tra	The testing effect enhances retention	leverage the testing effect, testing effect demonstrates

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Kết luận

Bộ đề thi IELTS Reading về chủ đề “How to learn coding online” mà bạn vừa hoàn thành đã cung cấp một trải nghiệm toàn diện về cách kỳ thi IELTS thực tế đánh giá khả năng đọc hiểu của bạn. Ba passages với độ khó tăng dần từ Easy đến Hard không chỉ giúp bạn làm quen với cấu trúc đề thi mà còn giới thiệu một chủ đề cực kỳ thời sự và quan trọng trong thế giới hiện đại.

Passage 1 đã giới thiệu các khái niệm cơ bản về giáo dục lập trình trực tuyến một cách dễ hiểu, phù hợp cho band 5.0-6.5. Passage 2 đi sâu vào các chiến lược học tập hiệu quả với độ phức tạp tăng lên, thách thức những học viên hướng tới band 6.0-7.5. Cuối cùng, Passage 3 mang đến góc nhìn học thuật sâu sắc về khoa học thần kinh và sư phạm của việc học lập trình, yêu cầu kỹ năng đọc hiểu ở mức band 7.0-9.0.

Như đã đề cập trong bài viết về how learning simulations are improving student outcomes, việc luyện tập với các đề thi mô phỏng như thế này là cách tốt nhất để cải thiện kỹ năng và tự tin của bạn. Đáp án chi tiết kèm giải thích vị trí, từ khóa và kỹ thuật paraphrase sẽ giúp bạn hiểu rõ cách tiếp cận từng dạng câu hỏi. Bảng từ vựng với hơn 40 từ và cụm từ quan trọng, kèm phiên âm, nghĩa tiếng Việt, ví dụ và collocation, là tài liệu quý giá để bạn mở rộng vốn từ học thuật.

Hãy nhớ rằng, việc cải thiện kỹ năng IELTS Reading đòi hỏi sự kiên trì và luyện tập đều đặn. Thực hành với các đề thi đa dạng, phân tích lỗi sai, và không ngừng mở rộng vốn từ vựng sẽ giúp bạn đạt được band điểm mục tiêu. Chúc bạn thành công trên hành trình chinh phục IELTS!