Design record forms for paper recording or computerised data loggers Flashcards
Whether data is gathered from interview or observation, successful recording is vital to the research process. This section describes a range of methods for recording data to reduce errors and facilitate analysis
Data recording can be divided into two groups:
• those structured at point of collection – usual for data collection in natural science (for example, proforma for data collection in field experiments, vegetation surveys, laboratory analyses etc) and also in quantitative social science (for example, questionnaires, observation schedule)
• data not structured at point of collection – social research employing a qualitative or interpretative approach (tapes and field notes from semi-structured interviews, life history, or participant observation).
Use of proformas
The careful design of proformas for the collection of data is very important. Proformas can help to reduce error by:
• ensuring data is collected in a standardised format
• aiding consistency in data collection when more than one data collector is involved
• providing a template for transfer of data to a spreadsheet or database for storage and retrieval.
Use of numeric codes
The use of numeric codes greatly facilitates the simple and accurate recording of responses on data forms or questionnaires (see 4.2.1). 1 = flush toilet 2 = latrine pit etc
Structured data part 2
Whether using manual or computerised methods for recording raw data, it is essential that the data are recorded accurately and with the desired degree of precision. However, it may not be possible to enter data directly into the database for the following reasons.
• Direct data entry may be impractical. The data are being collated in the field and it is not possible to record the data on a portable computer or data logger. In such cases, data are recorded in a notebook or a manual form and subsequently transcribed into the documentation system.
• Data analysis is required before documentation. In certain cases the characters are not recorded directly, but they require some collation and analysis before entry into the documentation system, as in the case of ratios.
Structured data
Raw data are often recorded on paper, usually using standardised forms, record sheets/forms, or questionnaires, especially if the data are being recorded in the field. If data are recorded by hand (in field notebooks or using standard forms) they will require transcription into a computerised format (eg SPSS, Microsoft Excel or Access). Data transcription is a common source of errors if not performed with great care. For this reason, the number of different manual transcriptions should be kept to a minimum.
Situations where one may use non-numeric codes
There are, however, occasions where non-numeric, letter codes can be used. An example is the three letter codes for country names recommended by the statistical office of the United Nations. Also, ecological surveys often use letter codes, in these cases the codes are specified on the data sheet – they are not shorthand given by the recorder. In the survey in 4.2.3, three types of code were used, numeric, letter, and shorthand
Points to consider in questionnaire preparation
Questions should be written out in full to be read out by the interviewer.
Questionnaire should include precise definitions of key concepts to be referred to by interviewer.
Coding scheme should be consistent across questions.
It may be useful if probe questions are written out.
If respondents have been told that information is confidential: how will respondents’ anonymity be assured?
More on use of codes
In any survey where codes are used it is imperative that an effective documentation system is in place; without this, data can be rendered meaningless. Documentation should include full descriptions of data sources, variables and codes; plus an ‘audit trail’ or logbook noting all changes and decisions made relating to the data.
Design of questionnaire forms
Some basic rules for the design of all data sheets and questionnaires can be outlined.
• Clear layout – presentation must be user friendly
• Spaces for time, date, interviewer name, location
• Cover sheet (the top sheet can easily be lost)
• Questionnaire or schedule number on each sheet (for the reason above)
• Each sheet numbered
Avoid letter codes
Numeric codes should always be used in preference to letter codes, for example, avoid using ‘vs’ for very short, ‘grn’ for green, ‘mkt’ for market, ‘I’ for irrigated, and so on. The problem with shorthand codes is that, while they might be obvious to you, they are not always obvious to other people − especially if you use shorthand codes for many descriptors or observational categories
Unstructured data - Select effective means of recording data in semi-structured interviewing.
In many research activities, data are not collected according to pre-determined categories. This includes data from semi-structured interviews, participatory research, focus groups, and participant observation. In some cases, a proforma may be appropriate for summarising information, for example, a debriefing document for a PRA exercise. Recording data in qualitative research involves making a detailed record of what people say or do; there are a number of options to consider here (Laws et al, 2003).
Unstructured data - Making notes during the interaction
Making notes during the interaction
This is sometime unavoidable but not always the best option when recording interviews. It is rather difficult to have a conversation with someone and write at the same time; some information will always be lost, it is difficult to be writing, listening to what is said and thinking of the next question or probe at the same time. However, in some circumstances where the purpose of the interview is to gain factual information this may be acceptable. However, where qualitative analysis of responses is anticipated it will not be adequate. Making notes as an observer may be less of a problem; however, it may still make the research subjects uncomfortable.
Unstructured data - having an observer take notes
Having an observer take notes
This is one solution to trying to make notes and interview or moderate an activity (focus group, participatory exercise) at the same time. The observer is also in a position to note context outside the interview and non-verbal cues that may aid interpretation of data. Working as a team an interviewer/observer pair can learn from each other, the observer can advise the interviewer of problems with leading questions, probes etc. In addition, the observer can pick up points for follow-up that the interviewer has missed
Unstructured data - Making notes after the interaction
Making notes after the interaction
For a number of reasons it may not be desirable to make notes during the interview or observation; in these circumstances it may be preferable to write notes after the interaction. This may take the shape of a session at the end of the day writing up a field diary or taking detailed notes after an interview. If you are using participant observation your scribbling may be off-putting to the people being observed or may become an accepted part of your role and not generate any anxiety; each scenario has to be assessed individually.
Unstructured data - audio recording
Audio recording
Recording interviews has the advantage of freeing the interviewer so that he or she can engage with the interviewee and is not struggling to record what is said accurately. The record of the interview is also far more accurate. It should be remembered that the work involved in transcribing interviews is often underestimated, (for example, one hour of interview may take several hours to transcribe). However, it may be possible to use the tapes to take notes, and limit verbatim transcription for themes that you are directly interested in. In some circumstances people will not be comfortable being recorded.
