How to Analyse CAT Mocks: Error Taxonomy, Time Audits & the Adaptive Loop
Most aspirants treat mocks as score-checkers. Top 1% treat them as diagnostic instruments. This framework turns every mock into a remediation roadmap, free on AdaptHub.
The 5-tag error taxonomy
Every wrong or skipped mock answer gets exactly one primary tag: concept gap, calculation error, trap or misread, time sink, or avoidable skip. Single-tag discipline turns a mock score into a prioritised drill list.
Every wrong/skipped answer gets exactly one tag. No "multiple issues"; pick the primary failure:
- Concept Gap: Didn't know the rule/property/formula. Fix: targeted concept study + 5 adaptive drills mapped to your mastery-based progression tier.
- Calculation Error: Arithmetic slip, sign error, unit mismatch. Fix: verification ritual per topic (sign check, unit check, boundary check).
- Trap / Misread: Negation trap, root-cause mismatch, distractor matched (read our full distractor error taxonomy analysis). Fix: mandatory re-read check for that question type.
- Time Sink: Correct but >3 min. Fix: heuristics / faster method / skip rule.
- Avoidable Skip: Solved correctly untimed. Fix: selection heuristic / mental stamina.
The analysis session (same day, 90–120 min)
Analyse each mock the same day for 90–120 minutes: log section scores and attempt patterns, re-attempt every wrong or skipped question untimed, tag the primary failure, and write the specific fix for your top errors before the next mock.
- Log section scores, accuracy, attempts, time spent per section.
- Re-attempt every wrong/skipped question untimed. Assign one tag.
- Re-solve all time-sink correct answers; find faster path.
- Re-read all RC passages you missed; mark inference vs detail vs tone errors.
- Enter tags into your log (or AdaptHub; tags auto-flow into next drill queue).
Weekly pattern review (every Sunday)
Every Sunday, rank your three most frequent error tags and set next week's drill focus, check attempt-order stability across sections, and verify that accuracy, not attempt count, drives your mock-to-mock percentile movement.
- Top 3 tags by frequency → next week's drill focus.
- Section attempt-order stability check (VARC first? DILR first?).
- Sectional accuracy trends: is QA accuracy climbing, DILR stable?
- Time-budget adherence: did you hit 40/40/40 or borrow from one section?
Where AdaptHub changes the loop
AdaptHub automates the action layer of mock analysis: adaptive routing keeps practice in your Zone of Proximal Development, distractor tagging classifies mistakes automatically, and the daily plan re-prioritises what to drill next without spreadsheet bookkeeping.
Manual logs work until they don't. AdaptHub's adaptive engine keeps practice inside your Zone of Proximal Development, tags distractor-style mistakes, and prioritises what to drill next, so the "action layer" of mock analysis is continuous, not a weekend spreadsheet. Learn the method on adaptive learning for CAT, or start on the pricing page.