CBTA Scenario Pack — Instructor Guide
✈️ CBTA Scenario Pack — Instructor Guide
Part 121/135‑Ready • LOSA‑Aligned • Scenario‑Based Training
Each scenario includes:
- Training Objective
- Scenario Setup
- Instructor Injects
- Expected Competency Behaviors
- Common Errors / Red Flags
- Evaluation Focus Points
- Debrief Questions
- TEM Mapping
1. COMMUNICATION SCENARIOS
Scenario 1A — ATC Frequency Congestion During Weather Deviations
Training Objective
Assess clarity, brevity, and accuracy of communication under time pressure and ambiguity.
Scenario Setup
- Enroute at FL350
- Convective line ahead
- ATC overloaded; long delays on frequency
Instructor Injects
- Late reroute clearance
- Ambiguous altitude restriction
- Cabin crew call during ATC congestion
Expected Behaviors
- Clear, concise readbacks
- Proactive updates to PF/PM
- Closed‑loop communication
- Prioritization of ATC vs internal communication
Common Errors
- Stepping on transmissions
- Incomplete readbacks
- Failure to brief crew
Evaluation Focus
- Accuracy under pressure
- Maintaining shared mental model
- Prioritization of communication channels
Debrief Questions
- “What information was most critical to communicate?”
- “How did you ensure the crew shared the same mental model?”
TEM Mapping
- Threats: Weather, ATC overload
- Errors: Incorrect readback, delayed communication
- Mitigation: Closed‑loop communication, workload distribution
Scenario 1B — Dispatch Replan Mid‑Flight
Training Objective
Evaluate clarity and prioritization when coordinating with dispatch during dynamic changes.
Scenario Setup
- Fuel burn trending high
- Dispatch sends ACARS reroute
- Weather deteriorating at destination
Instructor Injects
- Conflicting fuel numbers
- Cabin crew request for ETA
- ATC asking for intentions
Expected Behaviors
- Clarifies constraints with dispatch
- Communicates plan to ATC and cabin crew
- Prioritizes safety‑critical communication
Common Errors
- Accepting reroute without verifying fuel
- Over‑communicating non‑critical info
Evaluation Focus
- Information triage
- Clarity with dispatch
- Maintaining situational awareness
Debrief Questions
- “How did you validate dispatch’s numbers?”
- “What communication had the highest priority?”
TEM Mapping
- Threats: Fuel, weather
- Errors: Misinterpretation of ACARS
- Mitigation: Verification, cross‑checking
2. LEADERSHIP & TEAMWORK SCENARIOS
Scenario 2A — High‑Workload Approach With Junior FO
Training Objective
Assess leadership, delegation, and team coordination during high workload.
Scenario Setup
- Busy terminal area
- Runway change
- FO low experience
Instructor Injects
- ATC speed assignment
- Cabin call
- Automation mode change
Expected Behaviors
- Clear delegation
- Calm, assertive tone
- Encourages FO input
- Supports without micromanaging
Common Errors
- Taking over unnecessarily
- Poor task distribution
Evaluation Focus
- Leadership style
- Team climate
- Effective delegation
Debrief Questions
- “How did you balance support vs autonomy?”
- “What cues told you the FO needed help?”
TEM Mapping
- Threats: High workload, inexperience
- Errors: Over‑control, missed callouts
- Mitigation: Delegation, cross‑checking
Scenario 2B — Cabin Crew Reports Smoke Odor
Training Objective
Evaluate leadership and coordination across departments.
Scenario Setup
- Cruise
- Cabin crew uncertain about source
- No cockpit indications
Instructor Injects
- Cabin crew reports worsening smell
- ATC frequency busy
- Weather marginal at alternate
Expected Behaviors
- Calm coordination
- Clarifies details before acting
- Uses structured decision model
Common Errors
- Dismissing cabin report
- Delayed action
Evaluation Focus
- Cross‑department teamwork
- Assertiveness
- Prioritization
Debrief Questions
- “How did you validate the cabin report?”
- “What decision model did you use?”
TEM Mapping
- Threats: Ambiguous cues
- Errors: Under‑reacting
- Mitigation: Verification, structured decision‑making
3. SITUATIONAL AWARENESS SCENARIOS
Scenario 3A — Automation Mode Reversion on Departure
Training Objective
Assess monitoring discipline and rapid mental model updating.
Scenario Setup
- LNAV drops
- Aircraft reverts to basic modes
- High workload departure
Instructor Injects
- ATC speed change
- Terrain alert (nuisance)
- Cabin call
Expected Behaviors
- Immediate recognition of FMA changes
- Rebuilds mental model
- Communicates mode changes
Common Errors
- Mode confusion
- Fixation on automation
Evaluation Focus
- Monitoring
- Future‑state projection
- Mode awareness
Debrief Questions
- “What was your first cue that something changed?”
- “How did you rebuild your mental model?”
TEM Mapping
- Threats: Mode reversion
- Errors: Incorrect mode selection
- Mitigation: Cross‑checking, verbalizing modes
Scenario 3B — Rapidly Changing Weather at Destination
Training Objective
Evaluate dynamic SA and adaptability.
Scenario Setup
- ATIS changing every 5 minutes
- Ceilings dropping
- Fuel marginal
Instructor Injects
- New PIREP
- ATC delay
- Dispatch message
Expected Behaviors
- Updates plan continuously
- Identifies diversion triggers
- Communicates changes
Common Errors
- Outdated mental model
- Press‑on‑itis
Evaluation Focus
- Future‑state projection
- Risk assessment
Debrief Questions
- “What were your diversion triggers?”
- “How did you track changing conditions?”
TEM Mapping
- Threats: Weather
- Errors: Late diversion
- Mitigation: Continuous reassessment
4. WORKLOAD MANAGEMENT SCENARIOS
Scenario 4A — Multiple MEL Items on Turnaround
Training Objective
Assess prioritization and task management under time pressure.
Scenario Setup
- Tight schedule
- MEL items require coordination
- Cabin crew asking for updates
Instructor Injects
- Maintenance delay
- Gate agent pressure
- Dispatch request
Expected Behaviors
- Prioritizes tasks
- Avoids rushing
- Uses checklists correctly
Common Errors
Evaluation Focus
- Task triage
- Time management
Debrief Questions
- “How did you prioritize MEL vs operational tasks?”
- “What nearly caused task saturation?”
TEM Mapping
- Threats: Time pressure
- Errors: Checklist omissions
- Mitigation: Structured workflow
Scenario 4B — ATC Issues Unexpected Hold
Training Objective
Evaluate workload distribution and time‑critical decision‑making.
Scenario Setup
- Fuel tight
- Complex hold instructions
- Weather deteriorating
Instructor Injects
- ATC amends hold
- Cabin crew asks for ETA
- Dispatch sends fuel update
Expected Behaviors
- Distributes tasks
- Manages time‑critical decisions
- Avoids fixation
Common Errors
- Poor fuel monitoring
- Over‑focusing on ATC
Evaluation Focus
- Time management
- Task distribution
Debrief Questions
- “How did you manage fuel vs hold requirements?”
- “What tasks did you delegate?”
TEM Mapping
- Threats: Fuel, ATC
- Errors: Miscalculations
- Mitigation: Cross‑checking
5. DECISION‑MAKING SCENARIOS
Scenario 5A — Engine Vibration Increasing Slowly
Training Objective
Assess structured decision‑making under ambiguous cues.
Scenario Setup
- Vibration trending upward
- No checklist triggered
- Weather marginal at alternate
Instructor Injects
- Cabin crew reports noise
- ATC delay
- Dispatch asks for update
Expected Behaviors
- Uses structured model (T‑DODAR, FORDEC)
- Considers diversion early
- Reassesses decisions
Common Errors
- Waiting too long
- Over‑reliance on automation
Evaluation Focus
- Risk‑based reasoning
- Information gathering
Debrief Questions
- “What information did you need first?”
- “What risks drove your decision?”
TEM Mapping
- Threats: Ambiguous cues
- Errors: Delay
- Mitigation: Structured model
Scenario 5B — Conflicting Weather Reports
Training Objective
Evaluate information weighting and conservative decision‑making.
Scenario Setup
- ATIS VFR
- PIREPs LIFR
- Fuel adequate but not generous
Instructor Injects
- New PIREP
- ATC delay
- Dispatch suggests continuing
Expected Behaviors
- Validates sources
- Chooses conservative option
- Communicates rationale
Common Errors
- Over‑valuing ATIS
- Press‑on‑itis
Evaluation Focus
- Information weighting
- Risk tolerance
Debrief Questions
- “Which source did you trust most and why?”
- “What was your diversion trigger?”
TEM Mapping
- Threats: Conflicting data
- Errors: Misinterpretation
- Mitigation: Conservative bias
6. APPLICATION OF PROCEDURES SCENARIOS
Scenario 6A — Unstable Approach at 1,000 ft
Training Objective
Assess SOP discipline and go‑around decision‑making.
Scenario Setup
- High energy
- Automation not helping
- ATC speed assignment
Instructor Injects
- Windshear alert
- Cabin call
- ATC runway change
Expected Behaviors
- Calls go‑around per SOP
- Follows stabilized criteria
- Communicates clearly
Common Errors
- Press‑on‑itis
- Delayed go‑around
Evaluation Focus
Debrief Questions
- “What stabilized criteria were not met?”
- “What made the go‑around decision difficult?”
TEM Mapping
- Threats: High energy
- Errors: Late go‑around
- Mitigation: SOP discipline
Scenario 6B — Checklist Interruption During Abnormal
Training Objective
Evaluate procedural integrity under distraction.
Scenario Setup
- Abnormal checklist in progress
- Cabin call interrupts
- ATC request
Instructor Injects
- Cabin crew urgency
- ATC frequency congestion
Expected Behaviors
- Verifies step before resuming
- Maintains procedural integrity
- Avoids skipping steps
Common Errors
- Resuming at wrong step
- Losing place
Evaluation Focus
- Error trapping
- Checklist discipline
Debrief Questions
- “How did you ensure you resumed correctly?”
- “What distractions were most challenging?”
TEM Mapping
- Threats: Distraction
- Errors: Checklist omissions
- Mitigation: Verification
7. FLIGHT PATH MANAGEMENT SCENARIOS
Scenario 7A — Automation Surprise on Final
Training Objective
Assess manual flying and recovery from startle.
Scenario Setup
- Autopilot disconnects
- Gusty winds
- High workload
Instructor Injects
- ATC speed change
- Cabin call
Expected Behaviors
- Smooth manual control
- Re‑stabilizes quickly
- Communicates mode changes
Common Errors
- Over‑controlling
- Fixation
Evaluation Focus
- Aircraft handling
- Mode awareness
Debrief Questions
- “What was your first action after disconnect?”
- “How did you regain stability?”
TEM Mapping
- Threats: Startle
- Errors: Over‑control
- Mitigation: Smooth control inputs
Scenario 7B — VNAV Path Drop During STAR
Training Objective
Evaluate mode management and vertical path control.
Scenario Setup
- VNAV unavailable
- Must revert to basic modes
- ATC speed restrictions
Instructor Injects
- ATC altitude change
- Cabin call
Expected Behaviors
- Selects appropriate modes
- Maintains vertical profile manually
- Communicates changes
Common Errors
- Wrong mode selection
- Deviations
Evaluation Focus
- Mode management
- Vertical path control
Debrief Questions
- “How did you choose which mode to use?”
- “What cues helped you maintain vertical path?”
TEM Mapping
- Threats: Mode confusion
- Errors: Deviations
- Mitigation: Verbalizing modes
8. KNOWLEDGE APPLICATION SCENARIOS
Scenario 8A — Pressurization System Anomaly
Training Objective
Assess systems knowledge and interpretation of subtle cues.
Scenario Setup
- Cabin altitude rising slowly
- No master warning
- Weather marginal at alternate
Instructor Injects
- Cabin crew reports ear discomfort
- ATC delay
Expected Behaviors
- Interprets system indications
- Applies memory items if needed
- Plans descent/diversion
Common Errors
- Waiting too long
- Misreading indications
Evaluation Focus
- Systems understanding
- Timeliness
Debrief Questions
- “What indications were most important?”
- “What was your decision trigger?”
TEM Mapping
- Threats: Slow‑burn abnormal
- Errors: Delay
- Mitigation: Early recognition
Scenario 8B — Performance‑Limited Takeoff
Training Objective
Evaluate performance knowledge and verification discipline.
Scenario Setup
- Hot day
- Short runway
- MEL item affecting performance
Instructor Injects
- Gate agent pressure
- Cabin crew asks for delay reason
Expected Behaviors
- Calculates correct performance
- Verifies assumptions
- Communicates clearly
Common Errors
- Incorrect data entry
- Rushing
Evaluation Focus
- Technical accuracy
- Verification discipline
Debrief Questions
- “What assumptions did you verify?”
- “What nearly caused an error?”
TEM Mapping
- Threats: Marginal performance
- Errors: Incorrect calculations
- Mitigation: Cross‑checking