Interview and Transcription (300 points)
Assignment Description: In this assignment, students demonstrate their ability to conduct, transcribe, and assess/revise three (3) semi-structured audio research interviews. Using their approved research proposal, students conduct and prepare their first interview for data analysis by creating a verbatim (aka orthographic) audio transcription which transcribes spoken words (and other sounds) in recorded data. The student’s verbatim/orthographic transcription follows Braun & Clarke’s transcription system. For each of the three interviews, the assignment also includes a written honest self-assessment of the student’s interview performance and a statement of plans for improvement in the subsequent interview. Each interview, transcription, and self-assessment are worth 100 points for a total of 300 points.
Orthographic transcription records what was said. When we speak, we don’t use punctuation to make ourselves understood. We use pauses and intonation; we vary our speech in pace (faster, slower), volume (louder, quieter) and many other ways. Spoken (natural) language is ‘messier’ than written language: we hesitate when we speak, we stumble over our words, start a word or phrase and don’t finish it, and say the same word or phrase a number of times.
It’s important that your transcripts are thorough and of high quality. A transcription notation system allows you to clearly and consistently translate spoken language into written language, meaning your approach to transcription is thorough and meticulous.
WHAT MAKES A (QUALITY) TRANSCRIPT?
A quality transcript signals what is said and who is speaking. A good orthographic transcript records in written form all verbal utterances from all speakers, both actual words and non-semantic sounds – such as ‘erm’, ‘er’, ‘uhuh’, ‘mm’ and ‘mm-hm’. Your aim is to create as clear and complete a rendering of what was uttered as possible.
Do NOT ‘correct’ or change anything – for example, don’t translate slang or vernacular terms into ‘standard’ English (if a participant says ‘dunno,’ it should not be transcribed as ‘don’t know’). If you ‘clean up’ or edit your data, your participants will sound more fluent and more like they are using written language. The whole point of collecting spoken data is that we capture how people express themselves.
Schedule time to time to transcribe the interview as soon as possible (ideally the following day).
Verbatim/Orthographic Transcription Is Expected To Follow Braun & Clarke’s Transcription System:
Anonymizing transcripts: Any data that could identify the participant has been removed or changed. This includes changing participant names and names of other people mentioned in the data by giving them a pseudonym (fake name). Beyond this, remove or change other information that could potentially make the participant identifiable (e.g., occupation, age, identifying personal information – for instance has three older sisters).You can change identifying information such as people’s names and occupations, places, events, etc. in one of two ways. By changing details and providing unmarked, appropriate alternatives (e.g. ‘Bristol’ to ‘Manchester’; ‘my sister is 14’ to ‘my sister is 12’; ‘I’m a really keen knitter’ to ‘I’m a really keen sewer’). By replacing specific information with marked generic descriptions (indicated by square brackets, so ‘London’ might be replaced with [large city]; ‘Michael’ with [oldest brother]; ‘running’ with [form of exercise])
Identifies the speaker for each turn of talk: The speaker’s name, followed by a colon (e.g., Anna: ) signal the identity of the speaker (use Interviewer/Int for when you are speaking). A new line is started for every time a new speaker enters the conversation. The first word of each new turn of talk begins with a capital letter.
Identifies Laughing, coughing, etc.: ((laughs)) and ((coughs)) is used to signal a speaker laughing or coughing during a turn of talk; ((General laughter)) signals interviewer and participant are laughing at once
Identifies Pausing: ((pause)) is used to signal a significant pause (i.e., a few seconds or more; precise timing of pauses is not necessary).
Spoken abbreviations: When someone speaks an abbreviation, that abbreviation is used (e.g., TV for television) but abbreviations are not used unless a speaker uses them.
Overlapping speech: Type ((in overlap)) before the start of the overlapping speech Use ((inaudible)) for speech and sounds that are completely inaudible;when you can hear something but you’re not sure if it’s correct, use single parentheses to signal your best guess or guesses as to what was said – for example (ways of life) or (ways of life/married wife)
Non-verbal utterances:Render phonetically and consistently common non-verbal sounds uttered by your participants. For English-as-a-first-language speakers, these include ‘erm’, ‘er’,‘mm’, ‘mm-hm’
Reported speech: Reported speech is when a person provides an apparent verbatim account of the speech (or thoughts) of another person (or reports their own speech in the past).Signal this with the use of inverted commas around the reported speech (e.g. … and she said ‘I think your bum does look big in that dress’ and I said ‘thanks a bunch’…)
Margins: Format the transcript using transcript margins. 2 inch margin on the left-hand side and 1 inch margins on the right, top, and bottom margins.
Line numbering: Line number the transcript, continuously.
Audibility Check: Evidences that an audibility Check Performed (e.g., Auto-transcription software errors corrected (e.g., homophones) ** Audibility checks ensure the veracity of a transcript. Perform by playing back the recording while reading the transcription, pausing the recording to improve the accuracy of the transcription.
DU offers students access Zoom and Kaltura automated transcription services
- Students conducting face to face interviews should audio record their interviews and upload their recording to Kaltura My Media within Canvas or DU MediaSpace. “All video and audio files uploaded to Kaltura My Media within Canvas or DU MediaSpace will have an auto-generated closed caption file. As the video owner or editor, you can edit the auto-generated closed captions to improve accuracy.” Information provided courtesy of the DU Ed-Tech Knowledge Base: https://otl.du.edu/knowledgebase/kaltura-editing-closed-captions/
- Students conducting remote interviews should conduct their interviews using Zoom. “Our DU community ZOOM enterprise license now allows for real-time closed captions and live transcription” & ” if the ZOOM meeting was recorded to the Cloud, the host of the meeting can access the meeting record and edit the transcript.” Information provided courtesy of the DU Ed-Tech Knowledge Base: https://otl.du.edu/knowledgebase/zoom-closed-captioning-and-live-transcription/
- “Audio transcription automatically transcribes the audio of a meeting or webinar that you record to the cloud” Additional Instructions for automated transcription post-Zoom recording: https://support.zoom.us/hc/en-us/articles/115004794983-Using-audio-transcription-for-cloud-recordings-
Self-Assessment
For each of the three interviews, the assignment also includes a written honest self-assessment of the student’s interview performance and a statement of plans for improvement in the subsequent interview. Revisions to subsequent interviews can include, for instance:
- Rewording interview questions that did not work particularly well
- Changing the order of questions
- Adding more prompts and probes to encourage participants to talk more
- Plans to keep the next interviewee more on track
- Changing the location of the interview to somewhere more quiet or private
- Better use of silence
- Better management of nervousness
- Better opening or closure of the interview
