Quantitative tools tend to be the most commonly used in research because they yield the type of empirical data that lends itself to inferential statistical analysis. In other words, statistical and practice inferences can be made about how one set of findings from, or characteristics of, a particular sample can be extrapolated to the larger population from which that sample is drawn, or to other samples or populations. This idea of how well one part represents the whole is referred to as generalizability or external validity. Common quantitative techniques include but are not limited to surveys, assessment batteries, and secondary data analyses in which existing data is obtained from a database and analyzed.
Surveys:
- Surveys can vary in length and usually contain more closed-ended questions in which respondents must choose from predetermined response sets as opposed to open-ended questions in which respondents can answer any way they choose.
- They can range on a continuum of empirical rigor, from formal instruments that have been statistically validated to informal instruments that have not been validated but which may still have conceptual merit for a given research question.
- They can be standardized or non-standardized. Standardization refers to an instrument or collection of instruments possessing a range of possible responses that have been normed using a norming population in order to determine where an average response would fall. A response falling within or outside the average range indicates how an individual compares to others on a given domain or characteristic. Where individuals fall on this continuum often warrants significant clinical or practice implications for an individual, group, or organization.
- Primary advantages:
- Surveys tend to be time and cost efficient. They are relatively easy to administer and can target large groups all at once.
- They can cover a wide range of information on a variety of different topics at one administration.
- Primary disadvantages:
- In-depth information is compromised for efficiency and breadth. Important nuances in the data may not be captured because of the closed-ended response format.
- It is difficult to administer surveys to hard-to-reach groups or populations in the community.
Assessment Batteries:
- Assessment batteries are packages of multiple and/or extended survey instruments.
- They usually are empirically validated and standardized.
- Primary advantages:
- They are comprehensive and can cover a topic or broad range of topics in some depth.
- Their empirical rigor allows for a good degree of confidence in the validity and generalizability of the findings.
- Primary disadvantages:
- Because they come as packaged bundles (hard copy or Web-based), they can be hefty in cost to purchase.
- Assessment batteries can require a high amount of knowledge and expertise to administer and interpret. In fact, because of their complexity and potential for misuse, certain assessments require user qualifications (e.g., specific amount or type of education, training, certification, knowledge of research, etc.) in order to administer the battery.
Secondary Data Analyses:
- A secondary data analysis uses data that other individuals or organizations have collected for their own purposes in order to run an analysis for a separate study. The existing data is often retrieved from a database for analysis to address a research question at hand.
- An example of an existing data source on college campuses would be freshmen enrollment and academic data collected by the Registrar or Student Affairs offices. This type of data is regularly collected on college campuses for funding and accountability purposes, and it can be a rich resource for persons wanting to conduct their own study or to systematically analyze important outcomes such as student retention and graduation rates. For more information on how to access and use existing data sources on campus for program improvement purposes, visit Unit 4.
- Primary advantages:
- They are extremely time and cost efficient. Because data already collected is being used, little manpower needs to be involved with conducting the research.
- They can provide a wealth of information, variables, and indicators to choose from to conduct your own research.
- Primary disadvantages:
- Because you are using data collected by others, you obviously had no control over how the data was originally collected, under what conditions the data was collected, what outside variables may have interfered with data collection thus affecting the results, etc. Validity of the raw data set you are working is assumed because there is no way to ensure that the original data was collected and processed properly.
- Access to key data within databases can be limited and difficult to obtain because of security issues and confidentiality of the data, and in some cases with outside vendors, there are costs involved to access or use the data. Fortunately, at postsecondary institutions, collaboration with divisions or offices that routinely collect data is an option that can significantly minimize this drawback. See Unit 4 for more information.
