Method Overview
Survey is a structured way to collect data.
There are 2 major types of surveys:
1) Questionnaires:
- Mail Survey – a survey is sent to random samples through the mail
- Group Administered Questionnaire – a random sample is asked to fill out the questionnaire in person
- Household Drop Off – the researcher goes to the respondent’s home and gets the survey filled out there.
- Online Questionnaire – the researcher conducts the questionnaire through electronic means i.e. internet.
2) Interviews
- Personal Interviews – interviews are done in person
- Telephone interviews – interviews are conducted over the telephone
Procedure
The time to complete a survey depends on survey type, survey instruments, and sample size.
- Survey Preparation and Questionnaire Design – The first step involves preparatory activities, including designing the sample and developing the survey questionnaires to meet specific needs. Outlining the objectives of the study and how the questions will relate to the objectives and scope.
- Training and Fieldwork – The second stage involves training field staff and conducting fieldwork. Eligible target samples and respondents are identified and interviewed. Collection of survey data is done by both males and females to prevent bias.
- Data Processing – The third stage involves data processing, including editing, coding, and entering and verifying the data as well as checking them for consistency. Data entry and editing take place simultaneously with data collection, allowing for quality control of the data collected and for the provision of preliminary results one month after the end of data collection.
- Final Report, Data Preparation and Dissemination – The final stage involves analyzing the data, preparing the final report, and disseminating the survey results. This stage usually begins following the completion of fieldwork.
Advantages
- Surveys are relatively inexpensive (especially self-administered surveys). Although, mail surveys can especially get expensive because of posting costs.
- Surveys are useful in describing the characteristics of a large population. No other method of observation can provide this general capability.
- They can be administered from remote locations using mail, email or telephone.
- Consequently, very large samples are feasible, making the results statistically significant even when analyzing multiple variables.
- Many questions can be asked about a given topic giving considerable flexibility to the analysis.
- There is flexibility at the creation phase in deciding how the questions will be administered: as face-to-face interviews, by telephone, as group administered written or oral survey, or by electronic means.
- Standardized questions make measurement more precise by enforcing uniform definitions upon the participants.
- Standardization ensures that similar data can be collected from groups then interpreted comparatively (between-group study).
- Usually, high reliability is easy to obtain–by presenting all subjects with a standardized stimulus, observer subjectivity is greatly eliminated.
Disadvantages
- A methodology relying on standardization forces the researcher to develop questions general enough to be minimally appropriate for all respondents, possibly missing what is most appropriate to many respondents.
- Surveys are inflexible in that they require the initial study design (the tool and administration of the tool) to remain unchanged throughout the data collection.
- The researcher must ensure that a large number of the selected sample will reply.
- It may be hard for participants to recall information or to tell the truth about a controversial question.
- As opposed to direct observation, survey research (excluding some interview approaches) can seldom deal with “context
- Online surveys often lose track of survey target.
Recommended Usage
Surveys will be used to collect most of the data for SERA. We will be using group questionnaires the most. Also, we might be using some questionnaires during person or group interviews. Surveys will be the easiest and fastest way to obtain a large amount of data.
