By Matthew McCrea
Data inundates educators. Whether it’s assessment data from the latest formative quiz or attendance data from the last month, we rarely say that we need more data. With the recent rise of technology platforms aiming to aggregate data, even the organization of it has simplified. Thus, our challenge is no longer how to collect data but rather how to collect and use the right data to answer the questions that will drive our schools to the next level.
Quantitative and Qualitative Data
Broadly speaking, the data we collect fall into two camps: quantitative and qualitative. Quantitative data is anything that can be organized numerically. Assessment results are the most common type of this data. Qualitative data captures just about everything else, from observation during class time to interviews or conversations with students to informal notes we take when grading essays. Oftentimes, we look at these types of data as being mutually exclusive. When considering the whole child, we even favor our qualitative methods over the quantitative ones, judging, perhaps rightly in many cases, that quantitative methods simply miss out on too much.
Quantitative methods, however, can have a powerful influence on how we work with our students, especially when combined in a meaningful way with qualitative data. In the field of education research, a practice known as “mixed methods” aims to accomplish just that. Recognizing that quantitative and qualitative methods have their strengths and weaknesses—for example, quantitative data can be too sterile and qualitative data can take significantly longer to collect—the mixed methods technique aims to combine the two in a systematic manner in order to leverage their strengths while minimizing their weaknesses. The result? A plan of action that is backed by two streams of data and provides a much more robust picture than can be afforded by using either in isolation.
Mixed Methods in Action
Let’s consider what this might look like for a middle school reading class in my school. Several times throughout the year, my teachers give a writing diagnostic that assesses the writing skills of their students. They grade the essays using a standard rubric based on the PARCC assessment and then use our district’s data tool to aggregate the numerical results. Using this approach, we’re able to find broad trends that lead to areas of further inquiry. For instance, we might determine that the lowest scores for students were in the area of reading comprehension and written expression, and the average score was 1 point (out of a possible 4 points) on that component of the rubric. With this, we will also be able to establish peer reviewers, with the highest scoring students engaging in a mentor-type relationship with their lower-scoring peers or working on an enrichment activity while the teacher gives more direct support to the rest of the class.
What this quantitative data does not provide, however, is the thought process behind each student’s writing. This is where the qualitative data assists with planning the strongest next steps for instruction. Teachers might jot observations into a graphic organizer to help them collect their thoughts, noting which students have strong thesis statements but suffer from larger organizational issues in their essays and which need assistance with citing textual evidence. These two groups might have similar numerical scores, but they need very different support in order to grow their writing skills, and it’s the combination of the quantitative and qualitative methods that combine to bring those insights to the table.
The Big Picture
Mixed methods can have an effect outside of the classroom as well. Suppose you are beginning a character education program in your school. You will certainly want to collect quantitative data—that is, the number and types of disciplinary write-ups over time, the number and types of positive incentives given out for students displaying strong character, etc. To get a full sense of the program, however, you will also want to collect qualitative data by observing students interact in the hallway with other students and teachers and interviewing members of the school community to hear their perceptions of the program and how it is going.
On their own, qualitative and quantitative methods reveal important insights into our schools and our students, but they both have their weaknesses. By utilizing mixed methods to investigate the wide variety of educational phenomena we experience each day, we are able to get to the heart of the matter with a depth that would not be possible with each method on its own. Armed with these insights, we can ensure that the whole child is developed each day in our schools.