Survey Forms for Data Collection: Key Considerations

Introduction

To keep pace with the demands of the time and to continually improve performance and achievements, uncovering answers to specific and important questions regarding operations and services plays a significant part in any industry’s quest for progress. Data collection through surveys is one way that a business or organization can make informed decisions. These days, surveys can be found almost everywhere. Organizations and companies continually request feedback on a variety of aspects of their operations, including satisfaction with services and/or goods, questions about future behavior, and other areas useful for evaluating specific facets of an industry.

In the academe, feedback and suggestions from stakeholders are regularly sought through various collection methods, including surveys done face to face, online, and/or over the telephone. Surveys are usually the ‘go-to’ method of collecting information or data in academic institutions. One obvious reason for this is that it is possible to generate or obtain numerous types of information from varying samples of the population (Glasow, 2005). In addition to this, surveys can be easily developed and administered compared to other alternatives. In terms of resources and time requirements, surveys require minimal costs and a relatively shorter period of time to develop, deploy, and analyze results. Moreover, with the Covid-19 situation where almost all academic activities are conducted virtually, online surveys prove to be the perfect choice for carrying out monitoring and evaluation. For example, in terms of collecting feedback on teaching and learning, a majority of academic institutions send survey links to students to facilitate feedback collection. In doing this, evaluation still takes place even when respondents are not physically present on campus.

However, there are issues and limitations when conducting surveys. For example, Bell (1996) as mentioned by Glasow (2005, pp. 1-2) noted that some biases may occur in surveys due to respondent factors that include non-response, misreporting of behavior, and the difficulty of doing an objective self-assessment. These factors are obviously beyond the control of the data gatherer; however, there are certain important considerations that can be undertaken to minimize, if not eradicate, these survey limitations. These concerns include the choice of the correct method of getting feedback or data, tool development, deployment approach, and the use of robust data analysis techniques.

In deciding to deploy a survey, there are several factors that must be considered before choosing the deployment method. One of the most important factors is to have a clearly defined construct to be evaluated. Having a clear construct will help survey designers to decide on the best method of getting feedback, instead of being misled by other factors, such as the ease of development or deployment. According to Rickards, Magee, and Artino (2012), “Surveys are good for gathering data about abstract ideas or concepts that are otherwise difficult to quantify, such as opinions, attitudes, and beliefs” (p.407). They also underscored that when gathering information about behaviors that are not explicitly observable, the most useful method would be surveys. Thus, survey designers must think carefully about the kind of data evaluation they want. In addition, even the design of the survey form may cause respondents to misinterpret questions or lead to a lack of response. It is then imperative that when choosing the method, the design and type of questions must be taken into account before deploying any type of survey in order to get usable data.