Confound It! Or, Why It's Important Not To


Before you begin any research study — including those on the impact of Quality Matters — you’ll need to be aware of all the components involved. That includes components that you may not have thought about. These components, known as confounding variables, can have a major impact on your study, so it’s important to know what they are and how you can minimize their influence.

What Are Confounding Variables?

Confounding variables are the stowaways in a research study that can result in misleading findings about the relationship between the independent variable (IV), the input in the study, and the dependent variable (DV), the results of the study. Confounding variables are the extra, unaccounted-for variables that can stealthily have a hidden impact on the outcome being explored. The results of any study can easily be distorted due to one or more confounding variables.

An example of a study that reveals confounding variables at work (that may be all too real for many of us!) is one that seeks to find the impact of an increase in activity level (IV) on weight loss (DV). Sounds simple enough, right? But, what about study participants’ sex, age, food consumption, and any medications they take? Might any or all of these variables affect the correlation between activity level and weight loss? These are all confounding variables — and probably not the only ones that would exist in such a study.

In education, there are many studies that investigate the effect of an independent variable — or treatment — on learners. For example, student engagement in an online course (IV) will result in improved learning (DV). Might students’ prior learning, age, experience with online courses, the course content, and numerous other variables skew or cloud any results of the study that might be linked to student engagement?

Confounding variables are frequently present in studies related to Quality Matters. For example, suppose you want to design a study to find evidence that having a QM-Certified course (IV) will result in an increase in student learning (DV) the semester after the course has met Standards. Several confounding variables would be involved, including delivery, student readiness, and, perhaps the biggest one in this example: the condition of the course prior to its meeting Standards. For example, the course may have been originally designed using the QM Rubric and, therefore, did not experience many changes in order to receive QM Certification. If this is the case, an impact on student learning may not be seen, but it would be erroneous to assume that QM Certification does not impact student learning.

What Confounding Variables Obscure the Impact of Quality Matters?

The QM RubricTM is the validated instrument containing standards of quality course design. It is the bedrock from which quality in online learning can be launched within a quality assurance system at an educational institution. We know from research that online learning is impacted by a number of variables, however, the “Quality Pie” illustrates some of the prominent confounding variables categories, including:

  • Pre-condition of the design of a course related to officially meeting QM Standards (course design)
  • Teaching presence as well as other interactive features that are well described by the Community of Inquiry (course delivery)
  • Breadth and depth of the course content, especially related to learners’ anticipated knowledge of the content (course content)
  • Benign or proactive policies and practices for online learning at the institution (institutional infrastructure)
  • Technologies that enable effective and efficient interactivity between the learner, instructor,  and the institution’s learning technologies (LMS)
  • Dimensions of instructors’ online teaching experience and pedagogical approach, as well as specific online learning training (faculty readiness)
  • Pre-conditions learners bring into a course, such as online experience, educational history (student readiness)

How Can You Guard Against Confounding Variables?

The unfortunate answer in educational research is that you can’t completely guard against confounding variables. But, becoming aware of possible confounding variables related to any study you want to conduct helps. So, how can that be done? Reviewing previous research in peer-reviewed publications on your topic and those similar to yours will inform you about the range of confounding variables to account for in the design of your study. Analysis of related previous research findings will guide you to design a research question that addresses likely confounding variables.

What Else Can Be Done About Confounding Variables?

If you are reading about the results of a research study, having a good grasp of what confounding variables may be present and the fact that they may have had some impact on the dependent variable will give you a contextual, nuanced understanding of the results. A well-done study will address possible confounding variables in the discussion and limitations sections of the write-up.

If you are designing a research study, having a grasp of the possible confounding variables will help you design the study in a way that will address as many confounding variables as possible. Randomization in assigning students to one of two different groups (the control group or the treatment group) can help reduce the impact of confounding variables. But, randomization requires dedication in sample selection and access to a large number of participants so that they, regardless of their assigned group, would experience the same confounding variables.

So, does all of this mean you should throw up your hands since designing a study that will produce valid findings is so challenging? Definitely not! It does mean, however, that you’ll want to keep the possibility of confounding variables in mind as you design studies that collect and use learning data to benchmark your rigorous quality assurance process and achievements.

Want to Learn More and Practice Identifying and Addressing Confounding Variables?

When it comes to research, confounding variables is an important topic. Take time to learn more about them and other key components of a research study by participating in QM’s three-week online workshop, Designing Quality Online Learning Research. Register for the next session today.