CAT RC Trends 2017-2026 | The Only Analysis You Need for CAT 2026 | VARC1000 with Gejo

Main ideas / lessons conveyed

• CAT Reading Comprehension (VARC) is best understood by analyzing past papers, because preparation should match what CAT actually tests.
• The video suggests consistent patterns from 2017–2025, but warns that CAT 2026 could come in a “complete new avatar.”
• Key quantitative/structural findings:
  • 9 years analyzed (2017–2025): 102 passages and 438 questions
  • Passage length is consistently ~500 words, likely similar for CAT 2026
• Content variety is intentional:
  • Topics span social sciences, humanities, and natural sciences, with social sciences ~50%
  • Difficulty is framed as “thinking layperson” level rather than requiring subject-matter expertise
  • CAT uses a mix of sources (articles, essays, encyclopedia entries, journals, books) to avoid giving advantage to any one prior-knowledge group
• Reading strategy should emphasize reasoning/comprehension, not “retrieval-only.”
  • Questions increasingly demand logical inference and argument-related reasoning
  • A core rule: “Everything you need is in the passage.”
• Question types follow a demand hierarchy (big picture → detail → logic/inference → author positioning → function → strengthen/weaken → application)

Methodology / analytical approach presented

Data collection

• Use access to actual CAT RC passages from past years
• Analyze CAT paper years 2017–2025 (9 years; papers released annually)
• Note the CAT conducting IIM rotation:
  • Ahmedabad, Bangalore, Lucknow, Kolkata, Kozhikode, Indore
  • The video infers 2026 likely Indore, but still cautions that patterns may change

High-level decomposition

• Use a “deep dive” plan with:
  • 5 passage deep dive: length, genre, style, source, and takeaway
  • 3 question deep dive: type, frequency, and takeaway

Passage analysis

• Length
  • Count/estimate passage word count across all passages
  • Conclude ~500 words consistently
• Genre/topic split
  • Broad categories: social sciences, humanities, natural sciences
  • Estimated emphasis: social sciences ~50%
  • Example framing:
    • Natural sciences: animal/cold climate questions
    • Social sciences: societal change
    • Humanities: “accessible philosophy”
• Style classification (3 types)
  • Expository: neutral explanation; facts/processes; minimal author opinion
  • Analytical: neutral causality/why/how; compare/contrast; pros/cons; analysis of phenomena
  • Argumentative: author stance; claim + defense + counterarguments
• Style distribution claimed across 2017–2025
  • ~44% argumentative
  • ~34% expository
  • ~22% analytical
• Source classification (where passages are adapted from)
  • Articles (e.g., NYT, Economist, Guardian, Atlantic, Smithsonian) — often easier for general readers
  • Essays (example: Aeon) — complex ideas made accessible
  • Encyclopedia entries (example sources like the Stanford Encyclopedia / encyclopedia-style entries)
  • Journals — peer-reviewed research; CAT avoids passages requiring heavy prior knowledge
  • Books (non-fiction; history/philosophy themed examples)
• Source distribution claimed overall
  • Articles ~60%
  • Books ~17%
  • Essays ~9%
  • Encyclopedia ~7%
  • Journals ~8%
• Year-to-year variability caveat
  • Distribution can shift by year/IIM
  • Example given: Kozhikode expanding beyond articles/essays toward more encyclopedia/book sources

Question analysis

• Group question demand into 3 broad families
  1. Global (big picture): main idea, author intent/tone/function
  2. Local (retrieve specific info)
     • Local closed: exact detail retrieval from a specific paragraph/place
     • Local open: “truth-set” style (e.g., “all true except…”) where statements may be across multiple locations
  3. Logical (reasoning/inference): implied meaning, assumptions, explanation of author choice, etc.
• Further break down into ~9 question types (names as given)
  1. Central idea (Global)
  2. Author’s purpose / tone / keyword/term fit (Global)
  3. Central argument (Global; especially common in argumentative passages)
  4. Retrieve a specific fact/detail (Local closed)
  5. True/false except (Local open; evaluate multiple statements)
  6. Implied truth (Inference / meaning)
  7. Meaning in context: interpret phrasing without needing vocabulary knowledge
  8. Author agreement: what the author would support/oppose
  9. Specific function: why an example is used / purpose of a given example
  10. Strengthen / weaken / negate: evidence that supports/attacks the main claim
  11. Application: apply the author’s logic to a new external scenario
• Frequency claims
  • ~63% overall demand falls under logical reasoning family (nearly two in three questions)
  • Among 9 types, inference ~100 out of 438 (explicitly stated)
  • Application is rare: ~4.3% (explicitly stated)

Preparation takeaway

• Expect variety, not a fixed pattern
• Don’t avoid topics because you dislike them; CAT can include anything
• Strategy shift: prepare to reason, not only retrieve
• Core rule: you can answer every question using passage comprehension, even for meaning-in-context

Overall conclusions implied by the video

• CAT RC is structurally predictable in some aspects (notably ~500-word passages and consistent category coverage), but question logic changes over time—with stronger logic/inference appearing especially from 2019 onward (as per the narrator).
• Best preparation is broad and reasoning-focused:
  • Be comfortable with unfamiliar subjects and varied passage sources
  • Train to extract main idea + author intent + implied logic, not just explicit details

Speakers / sources featured (as mentioned)

Speaker(s)

• Gejo (identified via “VARC1000 with Gejo” / “I’m a trainer… VRC 1000”; narrator)

Course / organization

• VARC1000
• CAT conducting IIM rotation:
  • IIM Ahmedabad, IIM Bangalore, IIM Lucknow, IIM Kolkata, IIM Kozhikode, IIM Indore

External source examples mentioned (where passages may be adapted from)

• The Hindu (mentioned once as an example of an article source)
• New York Times
• The Economist
• The Guardian
• The Atlantic
• Smithsonian magazine
• Aeon (Eon) essays (example)
• Stanford Encyclopedia of Philosophy (example)
• Encyclopedia of Human Geography (example)
• Encyclopedia of emotions (example)
• Journals (general category mentioned)
• Non-fiction books (example title: “Scandalous Knowledge” by Barbara Smith)

Music / video framing

• [music] appears in subtitles (no named composer/artist provided)