Education is an intricate process that involves numerous variables, including students’ personal growth, their home, community, and educational environments, and the instructional methods they encounter. To understand a student’s needs, educators and school leaders have always analyzed different types of student data to drive instruction and improve student outcomes.
For decades, AnalyticVue has helped educators across the United States navigate the question of how to analyze student assessment data, how to use it to understand students’ learning progression, identify gaps, and adjust instructional strategies to enhance learning.
So here is a primer on how you can benefit from student assessment data. We talk about the questions to ask when analyzing student data, how to collect, clean, and organize it effectively, and how to choose the right tools to help you achieve the outcomes you envision.
Understanding student assessment data
Assessment data goes beyond mere test scores and grades. It paints a picture of a student’s learning journey. This data allows teachers to understand the student’s academic progression, strengths, weaknesses, and individual learning styles.
Understanding student assessment data requires a broad perspective. It spans from high-level scores to individual question responses, encompassing results from state annual assessments, teacher-specific tests, online formative assessment tools, and other evaluations.
As educators, assessing this wide range of data sources is essential to maximizing its use. You want to know specific areas where a student has succeeded or struggled. This level of detail allows you to tailor your approach to individual student needs, leading to a more effective teaching strategy. As educational leaders, seeing the aggregates can identify patterns of where individuals and organizations are successful, and where help might be needed. But having the data is key.
This starts with the collection process.
Collecting student data
Data collection involves aggregating a variety of information from multiple sources. These varied data sources offer a comprehensive look at student progress throughout the academic year.
The method of data collection depends largely on the type of assessment. Online assessments tend to provide automatic data collection. In contrast, in-classroom assessments often require manual data entry by teachers into grade books or spreadsheets.
In the absence of specific tools like AnalyticVue, teachers have developed their own data spreadsheets, and schools have been using tools like Google Studio, Tableau, and PowerBI for data collection and analysis. However, they each have issues, and limitations that ultimately limits their ability to provide the right information, to the right people, at the righ time. For example, spreadsheets have not been standardized, making use by others, or aggregating data to get a view of groups of students difficult, if not impossible. Additionally, privacy concerns created by corporate decisions to not abide by privacy policies, and difficulty managing access to the data and reports, have prompted many to seek alternatives. AnalyticVue’s commitment to data privacy is absolute, and we’ve signed several agreements ensuring that your data is yours, and for your use only, and that we will ensure its security and privacy.
For other assessments, data sources vary, but they generally come from the assessment tool the school district uses. Popular private assessments vendors such as NWEA, or Renaissance, collect the necessary data as part of the students’ use of their tools, and usually offer automation in terms of sharing them with partner districts. The vendors for state summative assessments, such as the STAAR in Texas, or MCAS in Massachusetts, use similar methods, although there seems to be less automation in terms of exporting data to districts.
Cleaning and organizing data
Completeness and accuracy are the two pillars of data organization and cleaning. A robust data set should have all the necessary information for analysis, including the details of where students excelled and where they faced difficulties. This can include the commonly found subgroup membership information about student demographics and/or program enrollment, but can and should be supplemented whenever possible with other elements about the students, the teachers, and the school that might serve as ways to identify patterns and insights in the data.
When there are a variety of assessment tools and data sources, pulling this information together for a big-picture assessment becomes difficult. That is, unless you have a solution like AnalyticVue, that will aggregate the data for you and serve it up from one platform, allowing single views to provide data from multiple sources, enriching the depth of information available for analysis.
AnalyticVue doesn’t just enable easier access and organization of data, it offers a robust solution for ensuring accuracy and data quality with a built-in business rules engine that works on three levels:
- Field-level checks: AnalyticVue reviews individual data points to confirm they are complete and accurate. Each field in the database is checked for acceptable values.
- Record-level checks: The software examines complete records to ensure they make sense. For example, if a student’s record shows they’ve left school, there should be a corresponding exit date. Without such information, the record may generate an error.
- Validation: AnalyticVue validates data against known, approved values. For instance, if a dataset suggests an assessment result for a school year in the future or a student who doesn’t exist in the school’s records, the software marks this as an error.
By cleaning and organizing data effectively, you can ensure you’re working with reliable information, enhancing the credibility of your analysis, which is critical in ensuring confidence by your users in the data.
Analyzing and interpreting student assessment data
Traditional methods of analyzing and interpreting student assessment data often focus on identifying areas for improvement. However, AnalyticVue enhances this process by not only answering the what, who, and when but also enabling you to explore the dynamics at play to explain the ‘why.’
However, Analyzing student data isn’t merely about reviewing numbers, it’s about presenting the data in context. For instance, a score of 90 out of 100 might seem impressive, but in the context that the target score was 95, the evaluation of that score changes. Additionally, combining various data points can reveal patterns and insights that may not be visible when looking at data in isolation. For example, if a single assessment indicates that a student is struggling, but four others related to the same learning objectives indicate otherwise, seeing those side-by-side might help provide a clearer picture of the student’s progress.
By providing instant insights into status trends, gaps, and areas for improvement, and putting these data points in context, AnalyticVue allows you to focus on bigger questions such as how to improve learning outcomes and why certain patterns occur.
Questions to ask when analyzing student data
When analyzing student data, it is essential to ask the right questions. This in-depth analysis, coupled with your understanding of your students, can lead to more informed teaching strategies.
For instance, are there patterns that show a lot of students struggling with the same kind of information? If those students are grouped in a single classroom versus if they are distributed throughout your district might involve different resources to resolve the issue. Is there a correlation between student absences in the period leading to the assessment, and their performance on certain assessments? Are our students growing equitably?
Understanding these nuances can lead to effective interventions that address issues and improve learning outcomes. Educators have been doing this sort of analysis` in their heads, as their familiarity with their students has always informed their decision-making, but with the volume of data that now exists, and the number of students each is involved with, tools like AnalyticVue can help provide that clarity that can get lost in the ocean of number and information.
Tools for analyzing assessment data
There are many tools, approaches, and options educators use for analysis, to varying levels of success. AnalyticVue stands out for its in-depth data analysis capabilities, and its ability to integrate various types of data beyond the purely academic to provide a more wholistic picture of students, classes, and schools.
Because our philosophy is that the focus should be on the data, rather than the tool, AnalyticVue seeks to be intuitive, and require fewer resources. Features like predefined reports, which deploy automatically as each data type is integrated, allow for immediate views of your data, and come not only provide the expected insights but also helps fine tune processes, such as exposing that lack of standardization in the data inhibits analysis. The moment data is entered into the system, it can be utilized to generate charts, tables, comparison analyses, and more. And because we know that one size does not fit all, almost every component can be configured to meet your specific needs.
These reports can range from high-level summaries of how students performed as a group, down to detailed item analysis. For example, if data is comprehensive enough to reveal how each student responded to every question on an assessment, AnalyticVue will show various reports showing what types of questions were answered correctly, or incorrectly, by which students, broken out several ways that might provide insight as to how localized or wide-spread an issue might be.
How to use data to make better decisions
In terms of ensuring student success, data is only part of the equation. The training, knowledge and invaluable expertise that educators complement the insights by providing responses to what the data presents. This expertise needs to be applied to devise specific interventions to improve teaching and learning. This could mean changing instruction timings, providing alternate or additional resources, or implementing more personalized solutions to students.
A great example of data being used to make better decisions is the case of Framingham (MA) Public Schools, where AnalyticVue’s impact was demonstrated via the consolidation of data from academic sources, student information, and transportation systems, FPS recognized that long travel times were impacting some students’ academic performance. Presented with this, officials finetuned their proposed new school locations to minimize travel times and with that to mitigate the impact of long travel times on students’ performance.
This particular example also underscores the importance that factors external to the classroom can have on performance, and how even when analyzing assessment data, it should not ideally not be done as a silo of information about students.
Tips and considerations
As you go about using and interpreting student assessment data, there are a few important points to note:
Utilize trusted data sources
It’s crucial to use reliable data sources to ensure the accuracy of your analysis. For instance, AnalyticVue pulls data from trusted student information systems or a combination of student information and grade book data.
Consider Multiple Data Points
Considering multiple data points provides a comprehensive understanding of a student’s learning status, leading to more nuanced decisions about instruction and interventions.
Look at Long-term Trends
While it’s important to address immediate learning gaps, it’s equally crucial to look at long-term trends. This helps you understand whether a student’s progress is consistent and can lead to more effective learning strategies.
Understand the Context
Understanding the context in which the data is collected can provide additional insights. For example, knowledge of a student’s socio-economic background or commute times can inform teaching strategies and help you better meet the student’s needs.
Wrapping up
Analyzing student assessment data is not just about understanding the ‘what,’ but also the ‘why.’ By making use of tools like AnalyticVue and pairing the data with your own expertise, you can uncover insights that can be used to enhance teaching methods, improve learning outcomes, and ultimately, drive student success.
Use of the tips we have shared here for effectively collecting, cleaning, organizing, and interpreting this data, and help you make informed decisions to enhance your teaching strategies. Tools like AnalyticVue, which provide detailed analysis and insights, are invaluable in this process. Ultimately, the goal is to use this data to create a learning environment that caters to each student’s unique needs and fosters their academic growth.