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Promoting Student Engagement in an Introductory Course with the “Classify” Instructional Strategy

By Dr. Christina Moylan

As I described in last week’s post, my understanding of designing a classroom that promotes student engagement and learning has evolved during my yearlong participation in the Early Career Excellence Institute (ECEI). In addition to better defining learning objectives and selecting preparatory materials for students for each class, a key part of my learning curve was exploring the various student engagement techniques that are available. This post highlights one of those many techniques – known as “classify” – and how I used it to create a more significant learning experience for students in an introductory course, Foundations of Public Health.

The objectives of a “classify” technique are to help students recognize how concepts are organized by truly understanding the defining principles, and learning how each of the concepts can be organized to relate to the whole (Barkley, 2010). This technique offers an excellent template for creating a student-centered environment that promotes enhanced understanding of classification definitions and the application of related material. It is easy to tailor to different topics as well as different levels of sophistication of student learners.

One class learning objective requires that students are able to define and identify types of quantitative public health data, describe how that data is aggregated to monitor population health status, and make connections to how it is interrelated to the other functions of public health.

screen-shot-2017-01-30-at-1-09-08-pm

Figure 1

There are 6 types of public health data introduced – these include vital statistics, single case, survey, self-reporting, sentinel monitoring, and syndromic surveillance. Students are assigned reading to complete before class to gain a general understanding of the types of data. In class, students are organized into groups of 3 or 4 and they receive a pile of disorganized information. On individual pre-printed cards are the different types of data (e.g., vital statistic) and on others the definitions (e.g., reporting of births and deaths as well as key communicable and specially selected non-communicable diseases required by law). Students also receive a graphical display of the actual use of data or tools (e.g., a birth certificate – see Figure 1). They then work within their small groups to match the concepts and definitions with the actual examples of public health data. Once the groups are finished, students are invited to stand up and walk around the room to review the choices that other groups made, ask questions, and revise their own layout. Once this process is complete, there is a full classroom discussion, giving different groups a leadership role for each type of data, to explain why they matched certain concepts with definitions and examples.

The role of the instructor in this exercise becomes secondary, to reinforce correct analysis and redirect when errors occur. The instructor can be ready with extension materials to further enhance student learning.

Continuing with the vital statistic example, the instructor could have a slide available with a diagram that traces the process from birth to how a birth certificate is filed with the government.

This class-wide discussion time is also an opportunity to insert interpretation questions such as “If you were a health officer and saw data like this, what might be your next steps or what conclusions might you draw?

In a subsequent class, the fundamental classification exercise can be enhanced by presenting data as an informational graph, as students commonly view information (see Figure 2). Few students actually understand the source of data for such graphs or how the data is collected in constructing a graph. The extension activity encourages students to consider the data from different perspectives, and mentally trace it back to a data source and method of collection. screen-shot-2017-01-30-at-1-21-22-pm

It also facilitates a discussion about possible data weaknesses (i.e., vital statistics data assumes that you are born or die in a country that has infrastructure to actually track and report on births and deaths) and the types of questions you might need to ask about data sources. It also provides a more robust underpinning for discussions like “What does life expectancy suggest to us about health in a country?”

With better understanding of the source and limitations of data, students can see that graphs, and the data compiled to create them, can be informative but should be open to interpretation. They are not a static truth.

Stay tuned for my last post,  where these instructional strategies are applied in an upper level course. In the meantime, how might you be able to apply a similar technique to a topic in one of your courses?

References

Barkley, E. (2010) Student Engagement Techniques: A Handbook for College Faculty. San Francisco, CA: Jossey-Bass.

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