Teachers everywhere recognize the need to be clear. It’s one of those parts of effective instruction whose importance almost goes without saying. An unclear explanation causes confusion and prevents learning. By the 1970s, there were already more than 50 studies that explored and documented the connection between teacher clarity and student learning. And research interest in clarity continues. Two recent meta-analyses (reference below), using different analytical approaches, integrated results from 144 and 46 studies respectively.
“Despite continued interest in the topic, research on clarity has seemingly become mired in issues of how to define and operationalize clarity. . . .” (p. 386) It’s not that clarity is all that difficult to define—it’s simply “being clear and easy to understand.” (p. 388) However, a definition like this operationalizes clarity at a high-inference level. Writing of the early research, the researchers explain, “Clear teaching was defined as an observer’s broad impression that a teacher was either clear or not clear in a given situation.” (p. 388) Said differently, high-inference definitions describe what teachers are, in this case “clear,” not how they do it. Definitions that involve high-level inferences make phenomena difficult to study empirically. They also make developing the skill challenging.
What works better for research and instructional improvement are low-inference definitions that identify concrete, observable behaviors, in this case the things teachers do that make them clear and easy to understand—things like taking time when explaining something and using examples to illustrate what they’re describing.
Research on clarity since the 70s includes work that has attempted to identify the teacher behaviors that make up clarity, and out of that work have come a number of different instruments and scales that have been used to measure the extent to which a teacher is clear. The work has also revealed that clarity is not as simple and straightforward as the high-inference definitions make it appear. For example, one study done in two different states and Australia identified 29 “prime discriminators,” which were classified into four dimensions of clarity: 1) assessing student learning, 2) providing time to think, 3) using examples, and 4) reviewing and organizing.
In addition to occurring in a wide range of behaviors, clarity is embedded in other aspects of instruction. For example, a graph in a PowerPoint slide or an email message from the instructor may be clear or confusing. How do these artifacts play into overall assessments of a teacher’s clarity?
In spite of the complexities involved in understanding what clarity is, these researchers observe that “while a single definition of clarity might be elusive, research across fields has consistently shown positive relationships between teacher clarity behaviors and student learning.” (p. 386) And these two meta-analyses add still more support for this strong and consistent connection between clarity and learning.
“Meta-analytic studies are useful for aggregating effects across a body of literature. Unlike vote-counting approaches, where studies are tallied as either significant or not significant, meta-analyses allow researchers to aggregate information about the relative magnitude of an effect.” (p. 396) And in the case of the first meta-analysis, “across the data set, a strong positive average correlation was observed for the relationship between clarity and the two outcome variables [affective learning and cognitive learning]. . . . Thus, overall clarity accounts for approximately 13% of the variance in student learning outcomes.” (p. 399) In this analysis, clarity had larger effects on affective learning than on cognitive learning. Results of the second meta-analysis were similar. This collection of studies, analyzed using a different methodological approach than the first, “combined for an average correlation of .53 with a 95% confidence interval ranging from .48 to .58 (p < .001).” (p. 404) “Despite strong average effect sizes observed in the data sets, those effects are heterogeneous, which suggests that considerable variability exists in the observed correlations across the studies.” (pp. 406-407) Researchers suspect these differences are the result of a lack of agreement on exactly what clarity is and how the behaviors associated with it are enacted in classrooms.
It seems more intuitive to expect that clarity would have a great effect on cognitive learning, but in both of these analyses the effect on affective learning was larger. The researchers offer several possible explanations. Again, the difference may be the result of how, in this case, cognitive learning is being operationalized. Like clarity, it has been defined differently in various studies. It’s also possible that the affective response comes first. “Clarity could trigger emotional reactions in students that then prompt them to pay attention and, in the end, learn more.” (p 409)
The work on clarity still leaves many important questions unanswered. Does what it mean to be clear depend on what is being taught? Might clarity be different in different fields? Is clarity always positively related to achievement? An overabundance of clarity (repeating and repeating, offering example after example) might cause frustration and annoyance. How exactly clarity helps learning is still not known.
“Instructors are well advised to continue using clarity to foster students learning.” (p. 411) Beyond the frequent question on student rating forms that asks for a general assessment of an instructor’s clarity, teachers could use one of the several instruments described and referenced in the article for more specific, behavior-focused feedback on this all-important aspect of instruction.
Reference: Titsworth, S., Mazer, J.P., Goodboy, A.K., Bolkan, S., and Myers, S.A. (2015). Two meta-analyses exploring the relationship between teacher clarity and student learning. Communication Education, 64 (4), 385-418.
