A Brief Word about Labeling Students

As much as educators dream of a school day free from references to student assessment data or achievement scores, the reality is that we all must learn to use data in our daily planning and instruction. Research shows that doing so will help educators to better shape our instructional goals and teaching strategies. In fact, if you’re lucky enough to work in a building where you’ve already received student achievement results from the previous spring, then you’re likely knee-deep in some type of data analysis right this minute. I know I am, but that’s because I’m eager to see what I’m up against this coming fall where my student learning groups are concerned. 

That said, with the recent release of student achievement scores and the data analysis that comes along with, for many of us, it’s also time to begin thinking about our curriculum and lesson planning. As you begin planning, please do keep in mind that the data you have right now may be very raw, so be cautious. If you begin to make assumptions about your students’ abilities based on what you have at this moment, without having drilled down to the details about each student, you are setting yourself and your students up for failure. This early data is designed to give you a glance at what you are up against as you move into classrooms with new kids in the coming school year. Separate this data as you may–by class period, by grade level, whatever–but, do be careful that you are not formulating judgments based on the one number you have in front of you on this day. Instead, use that data to begin laying the groundwork for the learning objectives you will form for student groups within your class. For example, with my early data, I develop pie charts that delineate the percentages of students in each scaled score range so that I can begin to define entry points for learning for each subgroup. Later, when I start to expand my curriculum, I will use more detailed data to differentiate learning segments in order to meet the needs of all students, regardless of their subgroup.

Use DOK & Mastery Grids to Supercharge Your Planning

So, if you’ve had a look at your students’ achievement scores and you are already thinking about your curriculum as I am, I’d like to share with you the details of two critical elements of planning I can’t live without: Norman L. Webb’s Depth of Knowledge (DOK), a hierarchical model for measuring rigor, and Chad Ostrowski’s student-centered, standards-based planning tool, the Grid Method. These tools allow me to consider and incorporate a variety of student data types to develop achievable objectives for my students throughout the school year.

Unfortunately, it wasn’t until I attended a local teaching workshop in the middle of the 2017-2018 school year where I was introduced to DOK and the Grid Method as a pair of planning tools. Sure, I’d been given that DOK “wheel” way back when I first started teaching in 2000-whatever-it-was, but I honestly never looked at it after the first glance. In my opinion, the wheel didn’t offer me much more than Bloom’s Taxonomy already had: learning verbs that had students doing, doing, doing, and that was the teaching game I played for the next 5 years. As for the Grid Method, it’s a fairly new planning method, so in my earlier years of teaching, all I ever relied upon were daily lesson plans and my planning calendar. Then, in 2018, in that cozy little workshop on teaching strategies for gifted learners, I learned that I (and my students) had really been missing out! Educational Consultant, Karen McKinley introduced our group to the ways in which DOK and Bloom’s Taxonomy complement one another in learning objective development, and how the Grid Method is the perfect platform to combine these two hierarchical models. Below are some tips and tools related to DOK and the Grid Method that have helped me help students grow into successful learners.

About Depth of Knowledge

• Depth of Knowledge, simply put, provides teachers with a framework for analyzing how critically a particular lesson, activity, or goal requires a student to think. In essence, DOK asks teachers to pay attention to the level of thinking involved in student learning to ensure they are setting forth rigorous standards for learning in their classroom.
• Some teachers may be familiar with the DOK verb wheel I mentioned previously, but John R. Walkup says to ditch it! Instead, Walkup asserts, context is EVERYTHING, and the DOK wheel provides none of that. The wheel simply represents groupings of verbs that are sometimes repeated within the different DOK levels.
• To ensure a focus on context, Maverick Education’s DOK Ceilings chart provides clarity on how to use DOK stems to construct learning objectives that involve higher order thinking that can be tied directly to your content. These stems are critical when framing student learning objectives so that you are sure you have the right level of rigor within the context of your content for each DOK ceiling.
• In her article, Blooms Taxonomy and Depth of Knowledge (DOK), Barbara Bray encourages teachers to,  “use Bloom’s Taxonomy as a guide for teaching and designing instruction and Depth of Knowledge as a guide for developing skills and encouraging deeper thinking and learning.”
• We can’t completely forget verbs though! No Grid or learning target is complete without them! To make learning objective development a little easier, try to think about it in this way: Blooms covers the doing portion of the learning objective, while DOK covers the thinking portion of the objective. Using this template, you can create your own objective by filling in the blanks with your specific doing/thinking/mastery combination: Students will    (Bloom’s, aka “doing”)    in order to    (DOK, aka “thinking higher”)    by   (demonstrating mastery)_ ., for example, 

Students will produce a creative analysis of a novel (Bloom’s) in which they synthesize their interpretation (DOK) by compiling evidence in a choice project that reveals details of the novel’s plot, setting, characters, or theme (Mastery).

• For further help with using Bloom’s and Webb’s to construct lesson objectives, Karen Hess’s Cognitive Rigor Matrix demonstrates how DOK works as an extension of Bloom’s Taxonomy when constructing learning targets that focus on both concepts and skills in context.

About the Grid Method

• In short, the Grid Method is a planning strategy that uses tiered learning targets to help students work through a series of tasks that will allow them to show mastery on the standards-based objectives you create. The key element of using the Grid Method is that all activities in the Grids you design build upon one another. Students may only progress to the next level of learning and thinking when they have demonstrated mastery of the targets within the current DOK level. It is also important to understand that where a student enters into learning on a Mastery Grid may not be the same as his or her peers, nor will they progress through Grid activities at the same pace. For more about how to manage learners entering at different skill or knowledge levels, read Ian Byrd’s article, To Differentiate: Lower Floors and Raise Ceilings.
• Chad Ostrowski is the creator of the Grid Method and his website teachbetter.com provides detailed information about how Mastery Grids work, how to develop them, and access to related training.
• While Grids are standards-based, they do not have to be used with standards-based grading. There are some elements of planning that are similar to SBG, but the Grid Method is much easier to develop, implement, and it allows for much simpler tracking of assessment data than standards-based grading.
• Each of the learning objectives in your Grids should contain both Bloom’s Taxonomy verbs and DOK stems. 
• The Grid Method does NOT replace carefully designed lesson plans. Lesson plans still need to be facilitated daily.
• NOTE: I do create my grids  from top to bottom, as opposed to Chad’s way, from the bottom up. For example, I build my rows starting with the lowest DOK level at the top of my Grid and work down to the highest DOK level as the bottom row. At the end of each DOK row on my Grids, students will have reached the ceiling for that level and can proceed to the next level after they have shown mastery. This is purely my preference and I can’t say that it has any bearing on my success with the Grid Method.

Numbers Don’t Lie

So, why all this raving about DOK and the Grid Method? Well, since we started out talking numbers, this is where I will let the numbers speak for themselves. The 2018-2019 school year was the first year I fully incorporated the use of both DOK and the Grid Method into my lesson planning and instruction. From the 2017-2018 school year, before full implementation of Grid and DOK, to this past school year, students’ scaled achievement scores increased nearly 20% on the Ohio state standardized test for 8th grade ELA! If that isn’t convincing enough, I don’t know what is! Mind you, I do understand that achievement, i.e. passing the test, is not the end all-be all of educating kids and that growth is as, if not more, important than straight up achievement; however, I do fully anticipate seeing increases in student growth as I continue to incorporate this dynamic duo into my curriculum planning.

Using DOK and the Grid Method together allows teachers to develop rigorous learning segments for their students.  They also allow every student, despite their ability, to find the perfect entry and exit point for learning. Mastery Grids and DOK provide you and your students a path to achievement and growth throughout the year.

I look forward to your comments about how you might incorporate the Grid Method and Depth of Knowledge into your planning in the coming school year!

Happy sowing and growing successful learners!

1. What type of data should I use to examine student growth?
2. What should I do with the data once I find it?
3. How will the data help me inform my practice to ensure students are growing?

Plus, I’ll even post a bonus section afterwards that will provide you with some tips on using calculations and formulas, and that will show you how to prepare  your data for sharing, so that your results can be easily understood.

I hope you will join me as I share my personal approach to data gathering and analysis. I look forward to your comments and suggestions below, as I love hearing about the ways in which others are using their data, too!

The Good Old Days…Before Data Was a Dirty Word

A few weeks ago, while joyfully reminiscing about former students between bells, my friend and I shared similar sentiments as we recalled the days “when school was fun for kids and teachers…when kids used to like coming to school before all this testing and data.” That conversation really got me thinking about the ways in which I interact with my own students’ data and what that means for them and for me. On top of that, my evaluation was just around the corner, and my use of data would be at the forefront of the discussion, I was sure. My head began swimming with questions: Was I looking at the right kind of data and would that data be able to demonstrate student growth? How would I determine what to look for in my students’ performance via the data? How will that knowledge help me to grow them further? Panic and mania simultaneously set in, all from the mere mention of the word “data!”

In recent years, all this talk of data, as it pertains to student achievement, has influenced significantly the way many teachers think about their own performance and their impact on students in the classroom. Looking at data can be very discouraging–even downright depressing–especially when Big Data says our kids are failing. However, by keeping a few simple ideas in mind, data no longer has to be a thing of dread, but instead, it can give you tremendous insight into what is working in your classroom, and thus, will give you confidence about how you are doing as you guide your students towards growth. The key to pain-free data analysis is to make sure you are looking at the right data in the right way. Here are a few tips that will help you mine your data “gold,” and that will put you in control of the data, instead of allowing the data to control you.

There’s Gold in Them Thar Hills: Finding Your Data Source

Analyzing student performance data can be a daunting task, especially if you aren’t highly skilled at it, or if you don’t understand exactly what it is you are searching for amidst all those numbers. Even with years of previous experience in data analysis, when looking at student data, I often feel like Julia Roberts in that scene from Pretty Woman when Vivian is in the hotel manager’s office explaining how she has “all this money” and she has to buy a dress, but no one will help her, tears streaming down her face. Except in my case, I’m shouting “I have all this data and I just want to know what’s going on with my kids and I can’t figure it out!” Tears streaming down my face. Yes, data sometimes makes me want to cry.

Big Data or Little Data?

What I have discovered in my love/hate relationship with data, is that in order to avoid those data-driven tears, it is important to know, first and foremost, what type of data will benefit you and your students most. You will see much more clearly  what is happening with students in your classroom when you look beyond Big Data and drill down to the individual student level. This means putting your school’s overall performance data aside, for the moment, and asking yourself which classroom assessment data is the most important for you to evaluate in order to establish whether growth is taking place. Remember, data analysis for classroom teachers isn’t about analyzing yourself against the performance of the entire school, or even how your student population is performing as a whole, but rather about each individual student’s performance as one part of said whole. In fact, education guru, Alfie Kohn, warns against the use of Big Data as a predictor of student success. In his article, When Big Data Goes to School, he cautions us about using scores that are “lousy representations of learning” simply due to the fact that they are readily available. He also challenges his readers to be wary of data that has been “repackaged” as formative, i.e., some forms of standardized testing and benchmark data. Having a clear of idea of exactly what formative data consists of will help you to overcome this. So, for now, leave that Big Data to those administrative Big Dogs, and instead, focus on the data that is in your control. I’m talking about Little Data.

So, Which Little Data Should I Use?

It may be clear, as classroom teachers, that Little Data is, indeed, what we should be analyzing; however, with ever increasing class sizes, wide ranges of learners in every class, and with more access to a variety of resources, including tech, even Little Data is widely abundant. That means when you are determining your data source, you should seek data that will give you the biggest bang for your buck. In other words, don’t just go to the gradebook and pick out an assessment and have a go at it. Instead, you’ll need to choose the kind of data that will allow you to provide students with qualitative feedback about their performance, so that, at some point, they are able to show growth if they aren’t currently. Here are two types of Little Data that might just help with that:

Formative Assessments That Connect to Higher Level Depth of Knowledge Skills

If your end-of-unit summative assessments consist of upper level Depth of Knowledge (DOK) concepts and skills [1] that involve students accessing prior knowledge to construct some new product or demonstrate some new skill–and they should–then it is imperative that the activities and smaller formative assessments taking place prior to summative assessment lend to the successful completion of those end-unit assessments. That said, look for formative assessments in your unit that include skills your students must absolutely be able to show mastery on before they can successfully complete the final summative assessment. Use that as your Little Data set. Knowing whether or not a student is proficient on a formative assessment whose skills will be put to use later in a higher level DOK assessment is imperative to predicting student success on that final summative assessment. Analyzing data in this way will help you determine if it is time for you to move on to the next level of assessment, or if you need to hold back and provide a bit of reteaching in order to prepare students for the higher level DOK assessment they will engage in later.

What does this process look like? I’m glad you asked! In our current unit, 8th graders are reading The Outsiders by S.E. Hinton. At the end of our unit, students will participate in two DOK Level 4 activities, one of which is the creation of a two-voice poem. This summative assessment requires students to take their learning from the novel and other newly acquired  knowledge of literary devices, including allusion, and turn that into something brand new, a.k.a., a two-voice poem that compares two characters using allusion and student-generated dialogue based on details from the novel. In order for students to be able to succeed at writing their poem, they must first be able to demonstrate that they have command of the concept of allusion as a literary device. In planning the unit, formative assessments were designed to help students acquire this skill and, as such, will provide those data nuggets that will allow us to determine whether or not students have mastered the skills necessary to write their two-voice poem. Analyze the results of those types of formative assessments and you will have some insight as to how students will perform on the final summative assessment. It’s that simple! Using Little Data can be a great predictor of how students will perform later where there is connected learning built into your assessments.

Summative Assessment Designed to Help Students Demonstrate Mastery

As we begin planning units for learning, thinking forward to summative assessment results is just as important as our initial planning, as those results will serve as the indicator for whether or not our students have mastered the content we presented to them. When looking for Little Data, unit-level summative assessment that helps educators to determine mastery levels is a great source for evaluating student growth, as well the effectiveness of our own instructional practices. Summative assessment data can provide us access to very specific types of data. For example, you could conduct an individual item analysis of particular questions, or, if you’re really nerdy (like me), you might want to evaluate standard deviations within the assessment to see the range of your students’ scores. These types of analyses can provide you with valuable insight as to where and how reteaching needs to happen, and whether or not you provided students with a sound assessment. Perhaps, you might find that the test was the problem, and not your teaching or your kids’ skill sets.

On a side note, if you are not presently engaging in backward design of your lesson planning and assessment, it may be worth your time to do some research on the topic. For more information on the process of identifying desired results prior to the development of assessments and lesson planning, as opposed to at the end, check out the work of Grant Wiggins and Jay McTighe. Their book, Understanding by Design, outlines the importance of beginning your planning for assessment with the end in mind, after the wisdom of educator and life coach, Stephen Covey. They encourage educators to think, first, about what it is that we want students to achieve before we plan a single portion of a unit.

What’s Next?

So, that brings this week’s post to a close. Now that you have an understanding of the differences between Big Data and Little Data and where you can find your own Little Data, in the next post, I will share with you exactly how you will turn that data into something meaningful so that you can more readily identify student growth. In the meantime, go out and begin your quest for informative classroom data–open your grade book, scour your lesson plans, pull out the stack of assignments on your desk right now. Have your raw data ready when you join me next time to find out how begin mining that classroom data into teaching gold!

[1] To learn more about using Depth of Knowledge in your planning and assessment, check out this helpful link.