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An In-Depth Look at Student Perception Surveys

A student perception survey represents a powerful source of feedback for educators and administrators. As student surveys play a greater role in classrooms, schools, and districts, it’s integral to understand the ways that survey instruments can (but don’t always) reflect nuanced differences in student perceptions.

Visit the Panorama Student Survey to view the full set of student survey questions

In trying to determine what makes one student survey instrument a more valuable measurement tool than others, two critical questions are:

How well does the survey capture variability in student perceptions?How well does the survey distinguish important aspects of teaching and learning?

Interactive Graphic: Explore how scales on the Panorama Student Survey correlate with others using our interactive graph. View the graphic →

Since introducing the Panorama Student Survey as a free student perception survey instrument last year, we’ve found that these two questions are crucial elements of a survey’s success in classrooms and schools.

In this post, we’ll outline our findings after analyzing 229,674 student responses from the Panorama Student Survey across a range of diverse school districts. In doing so, we can better understand how surveys reflect student perceptions at a larger scale.

To ensure the anonymity and representativeness of the data, we employed several sampling methods.

Variability

Students have a wide range of experiences in classrooms and schools, so a student survey instrument must be capable of capturing these diverse experiences. When educators analyze survey results, these differences should highlight both strengths and weaknesses. Educators will not learn much about their schools and classrooms if all survey responses score in the top 10% of possible answer choices (e.g. “93% of students feel engaged in their classes”).

Such overwhelmingly positive results may present a false premise to educators that there is little room to improve. But in an ideal case, student survey data reflects adequately varied feedback across all possible answer choices. An effective survey instrument is capable of capturing differences in student perceptions wherever they exist.

 

How do most students respond on the Panorama Student Survey?

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The graph above represents the distribution of survey results across the Panorama Student Survey’s classroom scales. The median is shown as the darkest green bar, with each green shade reflecting roughly 20% of results. You will notice that each scale captures adequate variability (ranging from 30% to 90% favorable) in student survey results.

 

By using “scales” (groups of survey questions) and by phrasing each survey item as a question (e.g. “How much does this teacher encourage you to do your best?”), the Panorama Student Survey works to minimize the measurement error of individual questions.

While other survey instruments may only reveal a narrow range of responses, our analysis shows the Panorama Student Survey captures an adequate range of variability in student perceptions.

Distinct Measures

As any practitioner will tell you, there are many aspects of effective teaching and learning. But how can you understand the differences between aspects like classroom climate, student engagement, and rigor?

Many student surveys only show how satisfied or unsatisfied students are with their school experience. These surveys often fail to differentiate among the discrete areas of teaching and learning that comprise students experiences in the classroom.

Ideally, a student survey should assess each topic area independently. When measuring student engagement, survey results should reflect the essence of a student’s attention to and investment in their classroom experience. This measurement is distinct from students’ perceptions of classroom climate or teacher-student relationships.
Example 1:  Top 20% of survey results on Pedagogical Effectiveness

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In the graph above, view how results in the top 20% for questions relating to Pedagogical Effectiveness correlate with scores on other survey topics. As you will notice, when students respond most favorably on Pedagogical Effectiveness (e.g. “How clearly does this teacher present the information that you need to learn?”), they may also respond with lower scores in Classroom Environment and Student Engagement.  View the interactive graphic →

 

Example 2:  Bottom 50% of survey results on Classroom Environment

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In this second example, view how the bottom 50% of responses on Classroom Environment correlate with scores across other Panorama Student Survey scales. Here you’ll see that students who respond less favorably on Classroom Environment (e.g. “On most days, how pleasant or unpleasant is the physical space in this classroom?”) may still respond favorably on questions relating to Expectations and Rigor and Supportive Relationships.  View the interactive graphic →

 

These graphs are intended to detail how the Panorama Student Survey distinguishes important aspects of teaching and learning through actual survey data. As shown in these two examples, students who respond high on one topic may respond lower on the next, while others might score low on the first one and higher on the next. The Panorama Student Survey is designed so that each scale measures aspects of teaching and learning independently.

Why is this important? As a teacher, it’s less helpful to receive student survey results that relay “you scored high on every topic” or “you scored low on every topic.” Instead, the Panorama Student Survey can highlight both a teacher’s strengths and areas for improvement, which can be used to guide growth in teaching practice.

Wrapping up

As educators use student surveys in their classrooms, schools, and districts, it’s critical to understand how survey instruments can best reflect student perceptions. That’s why we believe the Panorama Student Survey is a valuable measurement tool for educators, as it’s capable of capturing variability in student feedback across several distinct measures.

Interested in learning more?  Join our monthly newsletter or email our team at info@panoramaed.com


Jack McDermott is a Product Marketing Manager and Won Suh is a Data Scientist at Panorama Education. Follow us on Twitter @PanoramaEd

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