January 31

Tips for Identifying, Analyzing, and Utilizing Student Data – Part II

Backside of a Backpacker standing in front of a deep dark cave, staring in.

In the previous post, we discussed the difference between Big Data and Little Data and what each of those mean to us as educators who seek to use classroom data to inform our instructional practice. You can find the link to Part I of the series here. In this segment, we will delve into the process of finding the exact data we need, then mining it so that it serves a greater purpose for both teachers and our students.

So, Where Do I Begin My Analysis of Classroom Data?

When it comes to data analysis in your classroom, it might help to think of yourself like a prospector after precious gems, because, in essence, you will be taking similar steps in order to obtain big payoffs from the data you’ve found. After you’ve located your data source, mining it is the next and most vital step!

But, why do I need to mine my classroom data? And what does that even mean?! Well, first off, understand that data mining is a term usually linked to the analysis of big data; however, data mining is important when we are sifting through little data, too. Mining your classroom data can help you in several ways. It will…

  • Allow you to discover which data is worth your while and which isn’t.
  • Help you quickly and easily cash in on the information your data provides.
  • Provide you with the data that is the most relevant in order to make sound instructional decisions.

Again, please know that you are not mining data in the technical sense. Teachers typically aren’t using complex algorithms and we don’t have teams set up in our learning spaces to analyze mass volumes of data. However, since we do know that classroom data is more plentiful and increasingly more complex than ever, we have to figure out how to identify that which will quickly and easily give us much needed information about our classroom practice and student growth. There is still a lot you’ll need to sift through though, because you won’t be looking at data as simple scores, per se. Rather, your ultimate goal is to discover the reasoning behind the scores, i.e., what caused a student’s growth or decline. This is where mining is essential and why it is a key element of data-driven instruction.

Okay, So What Is My Data Going To Show Me?

Well, that depends on the kind of information you’re looking for. I usually begin by asking myself these questions:

  • Do I need to pre-assess which skills need attention and which will provide support as I plan for new learning? (Diagnostic Assessment Data)
  • Do I wish to determine when it’s time to move forward to the next learning segment? (Formative Assessment Data)
  • Do I want to see an overall representation of student growth across a unit that identifies individual student strengths and weaknesses and that reveals the impact of my teaching strategies? (Summative Assessment Data)

Each of these are great places to jump into data analysis and we will examine each of them separately below, but, before I outline the steps I take when mining classroom data, I want to mention that the English teacher in me deliberately chose the word show as opposed to tell for this section header. You see, I explain to my students often that when they are writing, it is their job to show readers the events in their story, not just tell them what’s happening with the characters or their plot. I feel the same way about data. Data may be able to tell you all sorts of things, but what you really want is for your data to show you where you, the teacher, need to focus your attention. When discussing data, educators and administrators often talk about what it is they “look for” in the data, as in, what is the data showing them? As the data prospector, you are on a path to discovery, searching for the remarkable things your students have accomplished while you have served as their learning guide, and you won’t be able to see that until you’ve sifted through all the rubble! Now that that’s out of the way, let’s have a look at each of the questions above to determine what classroom data can show us when we handle it properly.

Diagnostic Assessment Data: Use Right and Wrong Answers To Build Effective Lessons

Prospect It

First, you’ll need to determine how you are going to gather your diagnostic assessment data. You might use a program like Plickers, Quizlet, or others to identify where your learners are with regard to future content. When prospecting for diagnostic assessment data, remember that you are often searching for what students don’t know about a topic, or better yet, what they do know already. Your goal in analyzing this type of data is that you will end up with an inventory of student strengths and weaknesses that will tell you where to start with the learning you have planned or will be planning. Be aware that diagnostic assessment, generally speaking, should occur prior to unit or lesson development with the plan being that data from diagnostic assessment will provide you with a starting point for learning and will help you as you build your lessons and units. This might also include the need for lowering floors and/or raising ceilings for learning, as the data may demonstrate a range of knowledge and skills at the outset, thus demanding an always certain need for differentiation.

Mine It

If you’re using multiple choice or true/false assessment tools like those offered with interactive technology such as Plickers and Quizlet, get in the habit of looking at what students got right, as well as what they’ve missed. It’s obvious that the items missed are areas to be targeted for development, but what about the areas students didn’t miss or that they mastered? Don’t just throw that strength data out right away. Utilize it to support mastery of the skills students didn’t grasp as well. Let’s say you want to plan a unit that involves writing poetry and you would like your students to be able to include allusion and simile in their future poems. When giving your diagnostic assessment, if students demonstrate an understanding of simile, but not allusion, then figure out how students’ knowledge of simile will help them gain confidence while learning to master allusion. Using all of the data from diagnostic assessments will allow you to develop a spiraling curriculum that connects learning concepts so students are using prior knowledge to build new. This kind of data analysis ensures you are not just looking at wrong answers to develop a single learning goal, but instead using both right and wrong answers to create a rigorous learning plan that includes higher order thinking skills and a variety of depth of knowledge levels.

Formative Assessment Data: Deciding When It’s Time To Move On

Prospect It

Okay, so how often have you found yourself in this situation: you are in the middle of  a unit and you need to know if your students are ready to move on to the next learning segment? Chances are, pretty often, right? But, do you also sometimes feel yourself moving past assessments even though you know, in your heart, some students haven’t mastered the concepts? This is a struggle for many teachers, including me. But, assessing mastery is extremely important if we want to make sure students are prepared to move on to learning a new concept or skill, especially when you’ve deliberately made learning interconnected. This process doesn’t have to be difficult and you can begin by simply grabbing your lesson plans. Start by taking a look at your current formative assessment. If you are using spiraling planning, and in most cases you will be, then ask yourself, do students need to show mastery on this particular assessment in order to be successful on the next learning segment? You may be tempted to look at your student scores’ holistically, but resist that temptation. Instead, look within the actual assessment to find the real data gold.

Mine It

Holistically speaking, whether or not 80% of students passed an assessment is important to know, but the question you should seek to answer is what portions of the actual assessment, 80% average or not, did students not quite grasp? Before you hand back that stack of assignments, take note of which items your students struggled with the most. For instance, in a recent classroom activity, my kiddos were asked to identify a theme from our classroom novel and locate dialogue from the text that supports the theme they decided upon. Students needed to be able to demonstrate mastery in three areas:

  1. Determining a theme;
  2. Citing relevant textual evidence in the form of theme-related dialogue; and
  3. Making connections between what characters said and the their chosen theme.

From this formative assessment, I had to make three very important decisions:

  1. If students weren’t able to establish a viable theme at the outset of this activity, the rest of their work, although it may have been completed, would not help them to reach their overarching goal: to make meaningful connections in literature. These students had to re-explore theme-related concepts and skills right away.
  2. If students did not correctly cite dialogue, as conventions would dictate, but they did identify relevant dialogue to support their chosen theme, I then had to decide if it was worth the extra focus on proper citation skills. Or, would I simply be happy with the fact that students landed on some great evidential dialogue minus the proper, formal citation? For the time being, relevant dialogue was good enough.
  3. If some students were not able to make adequate connections between the dialogue and the theme despite using correct citation methods and an appropriately developed theme, I needed to understand why. This was the real hinge-point for determining whether to move on to the next chunk of learning with all students. This was the learning that would potentially make or break a students progress towards mastery of the end goal. Since all learning in the unit is connected and mastery of this is necessary to complete the summative assessment later in the unit, this component of the formative assessment had to be addressed before we could move on together as a whole.

Summative Assessment Data: Discovering Where To Go Next

Prospect It

Now that you have finished your unit, it’s time to see what students have really learned so that you know where to take them next. Personally, this is my favorite data to analyze because, at this level, the rewards are usually plenty. When your unit is done, the final assessment you give students should provide them with the opportunity to demonstrate mastery in all or most skills presented throughout the unit. Analyzing summative, unit-level assessments can provide you with a clear look at how both you and your students performed while engaging with a series of learning objectives. At a minimum, you will be able to identify three key pieces of information:

  1. You will reveal areas for reteaching.
  2. You will identify focal points for targeted interventions.
  3. You will discover whether your instructional strategies proved effective over the course of the unit.

Mine It

There are several ways to approach mining your summative data. Below are a few ways to gather information from one data set to address all of the needs listed above.

Note: if you are not administering assessments utilizing a tech tool that will deliver your summative assessment data in an automated format, then input your assessment results into a spreadsheet using a program such as Microsoft Excel or Google Sheets.

Reveal Areas for Reteaching

Begin by assembling your summative data so that you can see each students’ performance results at the question level across each row of a spreadsheet, ending the row with the student’s final summative score. You can conduct an individual item analysis by indicating each right or wrong answer to the question numbers across each row, student by student. In this analysis, you are simply looking for the percentage of incorrect answers at the bottom of a question column, which should align with a learning objective. When you calculate the percentage of incorrect answers by question, you are able to immediately see the areas of weakness that need to be included for reteaching in future lesson planning.

Identify Focus Areas for Targeted Intervention

In the same data set, you can evaluate the final summative score for each student to determine where it is necessary to establish individual intervention protocols. As you look at each student’s proficiency level at the end of their row, low scores will force you to go back and look at each student’s incorrect answers to determine focus areas. When time is available for students to engage in intervention, you will have a set of standards or skills that they can work towards developing when the whole class may have moved passed this standard or skill.

Evaluate Effectiveness of Instructional Strategies

Still working with the same data set, add notes to each question that indicate the instructional strategies you utilized to teach that particular standard or skill. Where you see proficiency on specific items, it is a good indicator that your teaching strategies worked there. Where there are deficiencies, you will need to evaluate the effectiveness of your chosen strategies by asking yourself questions such as:

  • Was the strategy implemented with fidelity?
  • Do I really understand how to use that strategy?
  • Did the strategy take into consideration the needs of individual learners?
  • Was that strategy the right one to use with that particular standard or skill?

The answers to these questions and others will help you to make different, and hopefully better, instructional choices the next time you teach that skill.

A Word On Benchmark Assessments

While I would categorize the results of benchmark assessment as Big Data on most occasions, I can’t emphasize how important these results can be when we need to provide administrators (and ourselves) with data that will feed their need for information about student achievement. In your classroom, your number one concern should be student growth. If it is, then achievement will eventually follow. While you manage the use of assessment data in your classroom to inform your instruction, benchmarking and other standardized testing results will be the evidence–in the form of student achievement–that what you are doing in your classroom is working and that it was accomplished by routinely analyzing your own little data! Whatever you do, don’t let benchmark data get you down. Use it as a motivator to keep you and your kiddos focused on the actual progress that is being made in your classroom every day.

Without continual growth and progress, such words as improvement, achievement, and success have no meaning.

~Benjamin Franklin

I hope Part II of this series has helped you to see how much data can show you about your students’ personal learning and the impact of your classroom practice. Now that we have figured out how to prospect and mine those classroom data gems, the final segment in this series will provide you with some handy tools that will help guide you in your task of polishing up that data so you can share it with others: administrators, students, peers, and even parents!

If you wish to explore more about data driven instruction, check out Engage NY’s Data Driven Instruction Library. There you will find documents, presentations, videos, and more that will help you dive deeper into data analysis for teaching.


Benchmark Assessment, Data Analysis, Data Driven Instruction, Data Mining, Diagnostic Assessment, Formative Assessment, Instructional Best Practices, Summative Assessment

Dawn Harris

Dawn Harris

I am a Secondary English Educator in SW Ohio & Associate Professor at Wright State University in the Graduate Teaching Program. I enjoy writing and presenting about all things education.

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