An Introduction to Survey Research

An Introduction to Survey Research

Copyright: © 2022 |Pages: 22
DOI: 10.4018/978-1-7998-8283-1.ch003
OnDemand:
(Individual Chapters)
Available
$37.50
No Current Special Offers
TOTAL SAVINGS: $37.50

Abstract

The purpose of this chapter is to provide an easy-to-understand overview of several important concepts for selecting and creating survey instruments for dissertations and other types of doctoral research. This chapter includes information on instrument selection, survey validation, and survey instrument creation. A review of survey scale types and important definitions and concepts related to survey research is included. A sample conceptual framework that can be used to link research questions, relevant literature, and survey questions is also provided.
Chapter Preview
Top

Introduction

The creation and selection of an instrument is one of the most important tasks a doctoral student will complete in the formulation of his/her dissertation or applied dissertation if he/she plans to use survey research. The results in a dissertation depend both on an adequate sample and a valid research instrument. Unfortunately, selecting and creating an instrument is perhaps one of the most confusing aspects of the dissertation. Although doctoral students may be aware of what survey instruments are and how they are used, what they often do not understand is how to find or create an instrument that actually answers the questions the student is seeking through the use of statistical methods.

Before getting into the topic at hand, I would like to relay a personal story which provides context as to why I wrote this chapter. Many doctoral advisors will caution students not to create their own dissertation instruments. My own advisor told me this, but there were no instruments available for what I wanted to measure. My topic was a new area of study. I disobeyed this advice, and was glad I did. Learning how to create an instrument and develop something that answered my research questions myself was the by far the most valuable part of my doctoral education. For me, it was like a light bulb came on and everything I had learned suddenly made sense. I have chaired over 80 doctoral dissertations in education and healthcare and the majority of my students successfully created their own valid instruments for their research. In addition to having students create survey instruments, almost all of my students also included open-ended questions so they would learn how to analyze qualitative data and understand concepts of qualitative validity such as saturation.

The choice is truly that of the student and advisor. However, if a student creates her own instrument in the dissertation process, it is the only time the student will have others helping her through the process step-by-step. This provides the doctoral student an important skill set if she wants to do research in the future or if she desires to go into academia.

The purpose of this chapter is to provide an easy guide for doctoral students to evaluate or create their own survey instruments for mixed methods survey research. The objectives of this chapter are as follows: a) to review concepts of validity and reliability in survey research including both qualitative and quantitative methods, b) propose a process for existing instrument evaluation, and c) provide an easy-to-follow process for survey instrument creation including creating a conceptual framework using relevant literature.

Key Terms in this Chapter

Validity: A survey instrument that is reliable, accurate and measures what it is supposed to measure.

Saturation: The point at which further qualitative data collection is unnecessary and likely to yield any additional data.

Survey Scale: A technique that uses indexes to measure variables in a survey by designating levels of agreement/disagreement or other measures of attitudes, perceptions, and beliefs. Types of scales include the Likert scale, the Likert-type scale, the Guttman scale and the Mokken scale.

Cronbach’s Alpha Statistic: A measure of internal consistency of a survey. The closer this statistic is to 1.0, the more consistent the survey.

Reliability: Indicates a survey will measure values consistently; also called repeatability.

Content validity: The extent to which the survey represents all important facets of a construct.

Survey: An instrument used to collect a participant’s attitudes, beliefs, perceptions, and/or practices. Another name for a survey is questionnaire.

Complete Chapter List

Search this Book:
Reset