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Otter.ai and Whisper transcribe interviews free — then Claude can code themes the way grad students do for $1000.
For oral history projects or capstone interviews, transcription used to take hours. Now Otter does it live, and Claude can pull the patterns.
For your next project interview, record (with consent) into Otter. Drop the transcript into Claude with 'Find 5 quote-worthy moments.'
A 30-minute interview used to take 2-3 hours to transcribe by hand. Now Otter.ai, Whisper (free, local), and Apple's built-in Voice Memos transcribe a recording in minutes — usually 95%+ accurate. The transcription is just the start: 'coding' (tagging themes) is where the real research happens.
Interview a family member for 10 minutes about something they remember — a specific event, their first job, their childhood neighborhood. Record on your phone, upload to Otter.ai, and read the transcript. You just made a primary source that didn't exist before.
15 questions · take it digitally for instant feedback at tendril.neural-forge.io/learn/quiz/end-builders-research-AI-and-interview-transcript-r8a10-teen
What is the primary benefit of using Otter.ai for transcribing student interviews?
What does the term 'thematic coding' refer to in AI-assisted research?
Why is obtaining recorded consent important before beginning an interview?
How many minutes of transcription does the Otter.ai free tier provide each month?
In what situation would using Whisper API be preferable to Otter.ai?
What type of task can Claude perform when given an interview transcript?
Why might a researcher ask AI to find quotes that contradict their hypothesis?
Which statement best describes qualitative research?
When interviewing a student your own age, what consent is required before recording?
What does the $0.006 per minute charge refer to in the lesson?
Why is asking Claude to 'find 5 quote-worthy moments' a useful prompt for student research?
A student is interviewing in a busy cafeteria with background chatter. Which transcription tool would be most appropriate?
How does AI transcription specifically help with oral history projects?
What does it mean to 'code' themes in research?
What is a key advantage of using AI to analyze multiple interview transcripts at once?