What are the benefits to digital data collection? Move into the 21st Century: From Paper to Digital Data Collection

By Patricia Wright, PhD, MPH

The world is changing, and data can now be collected electronically, on the fly with an app and a portable device such as a tablet or phone. In the last decade, we have all lived through the movement from paper medical records to digital and the medical community is reaping the benefits. Now is the time for Education to take the next step and join the revolution.

Digital data management is here to stay but as educators and school systems move from paper to digital, some are approaching this frontier with gritted teeth.

Special education is data rich especially when it comes to progress monitoring IEP goals and objectives. Special educators develop IEP documentation, including IEP goals and objectives. These documents are stored digitally, but educators must also collect data to progress monitor and evaluate student’s achievement of their IEP goals and objectives. Historically, this data has been collected by pencil and paper, graphed by hand or more recently graphed in excel – it was A LOT of work and still is!

You may be thinking: Why Should I care? What are the benefits to digital data collection? There are 5 major benefits of digital data collection:

  1. Data is analyzed instantly! With electronic data collection the data can be graphed and analyzed instantly. No more calculating by hand and moving data into a spreadsheet.
  2. More Time to spend on other projects! Every teacher wants more time, using digital data collection for progress monitoring can buy you some valuable time.
  3. Say goodbye to transfer errors! We all like to think that we are perfect but transcribing numbers from paper to a spreadsheet leaves room for error.
  4. It’s green! You won’t have endless stacks of papers that need to be shredded and recycled.
  5. Timely Instructional Decisions! Simply press the record button and data analysis is available immediately. No more waiting until the end of the quarter to adjust instruction. Instructional decisions can be made in a timely manner for maximum benefit.

Join the revolution, start collecting your data digitally!

Rethink Ed Data Recording App! Download in the app store today!

I’m a Teacher not a Data Analyst: Five Easy Steps Towards Making Data-Based Teaching Decisions

By Patricia Wright, PhD, MPH

The educational system values and uses data to inform everything from the evaluation of individual students and entire school districts to educator’s performance-based pay and the success of curriculum. Teachers play a role in every single one of those decisions, yet teachers are often not comfortable with data analysis. In fact, 72% of districts cited lack of teacher preparation as a barrier to increased use of data systems. With so many benefits of digital data collection (think less time on IEP documentation!) it is vital that teachers, specifically special educators, start increasing their understanding of data-based decision-making.

Here are 5 simple steps you can make towards becoming a data analyst AND a better teacher:

  1. Write measurable goals and objectives
  2. Develop a data collection system and collect data
  3. Represent the data visually (usually with a graph)
  4. Evaluate the data
  5. Adjust instruction as guided by the data

Step 3 is an important one: Represent the data visually (usually with a graph)

It is difficult to analyze data if it is not represented visually. Graphs help define what is happening. For example, graph one instantly demonstrates the progress and learning a student is making.

Rethink Ed Graph 1

In the graph below, we can quickly determine that the students’ performance is variable and learning really isn’t occurring. With graphs you can evaluate the data (step 4) and adjust instruction (step 5) as guided by the data to better meet student needs. In this below example, the teacher can look at the instructional experience the student is having and discern what is inhibiting his learning.

Rethink Ed Graph 2

Graph your data – become a data analyst!

Spotlight Educator of the Month: Joanna Cunningham

Spotlight Educator of the Month!

Position: Special Education Preschool Teacher
District: Shelby County Schools in Memphis, TN

Joanna Cunningham is a Special Education Preschool Teacher at Shelby County Schools in Memphis, TN. Shelby County Schools serves approximately 26,000 special education students and has an instruction force of more than 1,000 professionals. Rethink Ed’s platform, especially its data collection and professional development, the ABA training series, supports Ms. Cunningham every day in her classroom.

Rethink Ed is a valuable tool for creating IEP goals, collecting student data, lessons, and professional development. The platform assists Ms. Cunningham in developing student plans and goals. It helps her to “think through exactly what I want my students to be able to do at the end of the IEP and to ensure I’m collecting the data in the correct way. The lessons help ensure I’m delivering consistent instruction to meet these goals.” Confidently, Ms. Cunningham knows that her students are on the right path and working towards their goals.

Data collection is tricky. Often, we think we know exactly what we are collecting data on and why, only to discover that it was the wrong approach. But with Rethink Ed, Ms. Cunningham found that it “helped me look more closely at the way I’m collecting data, what I’m measuring, and to be more granular about it. By doing this, my students are benefiting from better instruction and quicker course correction (if needed).” She can work closely with her students and team to visually see where they need to focus.

Ms. Cunningham has noticed a marked difference and improvement in her students as well as with her team of teachers. The ABA series basic training has, “reconfirmed the education I have had in working with challenging behaviors and is helping me train my team to ensure we are carrying out behavioral interventions with fidelity.” They do this by independently going through the online modules and then discussing how they can better serve their students.

This is just the beginning of Ms. Cunningham’s and her team’s Rethink Ed Success. She is excited to continue to utilize Rethink Ed in her classroom and continue to track student data. She knows that this platform will assist with IEP teams going forward and is excited to “look back and see where the student has been and how far they have come.” Ms. Cunningham is ready to jump into spring with Rethink Ed at her side!

Congratulations, on being featured as our Spotlight Educator. We look forward to continuing to hear about your success with Rethink Ed.

Regression and Recoupment Data Collection and Analysis over Winter Holiday Break

By Patricia Wright

Qualifying students for Extended School Year (ESY) is a multi-faceted process. One of the considerations is regression and recoupment; is the student likely to lose skills and fail to gain those skills within a reasonable time-frame upon return to instruction. The winter break is an ideal time to assess regression and recoupment. Collecting data immediately prior to the break and immediately following the break can demonstrate the student’s performance over a two-week absence of instruction.

For example, the student below showed a significant regression and it took an entire month to recoup to the prior rate of performance. This may be a consideration in determining eligibility for ESY.

Utilizing data-based decision making for ESY eligibility can decrease the challenges created when relying on personal perspectives or opinions. Use Rethink Ed to actively collect data immediately prior and immediately following winter break and see how your students perform.

3 Tips for Making Data-Based Decisions like a Pro!

By Jennifer Bessette, Director of Professional Services

Data. Some people love it. For others, it can be a real four-letter word. Whether you love it or hate it, data is here to stay! It is CRUCIAL to student success. Without data, we have no way to objectively analyze student progress. However, simply collecting data without pausing to reflect & make decisions gets us nowhere. Check out these great tips to ensure a successful data-driven school year!

1. Collect a Baseline
Prior to teaching a new goal to your students, it is a great best-practice to begin by collecting baseline data. You can think of baseline data as a pre-test: we’re simply testing the student to see what he already knows before we begin teaching. Imagine you’re planning on teaching a student to identify community helpers. Without collecting a baseline, you likely don’t know if the student knows some community helpers, all community helpers, or no community helpers at all. This would make it difficult to know where to begin. Once you collect some baseline data, you may discover that the student can already identify the police offer, the fire fighter, and the doctor, but cannot identify the postal worker, the construction worker, or the teacher. You now know where to begin your lesson!

Baseline data also documents the awesome work you’re doing teaching your students. Without baseline data, someone might wonder if you actually taught this skill to the student or if he already had this skill to begin with. If your baseline data shows the student cannot accurately and reliably perform the skill, but after you begin teaching, he now has the skill, you are showing that it is your teaching that made the difference!

2. Be Specific
Analyzing data can be quite difficult if you were not specific during data collection. Take the example of teaching your student identify objects. If the student is not mastering this skill, why not? Take a look at the following graph:

What do you know about this student by looking at this graph? You can see student has not been able to perform this skill with more than 66% accuracy. Why? Honestly, it’s difficult to know the full story looking at this graph. Let’s take this same data, and present it in a different way:

Looking at this graph, you can now see the student is able to identify the ball and the car, but is struggling to identify the block, book, and doll. Now you have a much better sense of the student’s strengths & challenges, and know where you should focus your efforts moving forward!

3. Check for Pre-Requisite Skills
Sometimes students struggle to make progress on all aspects of the goal no matter how hard you try. This can be frustrating for educators, parents, and the student. Imagine a student has been learning to tell time, and has shown very little growth on this skill.

One question you might ask at this time is: Does the student know all of her numbers? If not (or maybe she’s forgotten), telling time would be a very difficult skill for her! This would be a great time to stop & test for the pre-requisite skill of Identifying Numbers.

Clearly, you can see the student did not have this pre-requisite skill. However, after pausing to teach this skill, it looks like the student can now identify all numbers 0-12. Let’s return to the Telling Time lesson.

There! That did the trick. Now that your student can identify all numbers 0-12 and she is able to tell time to the whole hour. Success!

What are your favorite tips for making data-based decisions? Let us know in the comments below!

Using Baseline Data to Inform Instruction

It’s no secret that data can be daunting. For some of us, the word “data” means pile-high clipboards and stacks of complex data sheets or binders of reports. Data can also feel like never-ending lists of impersonal statistics that are difficult to difficult to comprehend and cumbersome to analyze.

When we look at data through this lens, it becomes impossible to see how data can improve student performance and enhance holistic education practices, but it can. So let’s break it down.

In it’s simplest form, data is a collection of facts and statistics that can be used for planning or analysis. All educators are charged with ensuring they use data to inform instruction, so students benefit from evidence-based techniques and approaches to education. Data can also be helpful in monitoring student progress and identifying areas of need through assessments.

Pre-tests, homework, attendance, grades and test scores are all data sources that help inform classroom, school and district decisions.

What is baseline data and how is it collected?

Baseline data is a measurement that is collected prior to intervention or teaching starting. It can be collected through various measures including: percent accuracy, frequency, duration, rate and intervals. When selecting a measure of baseline data collection, it is important to consider how intervention or instructional data will be collected to ensure consistency.

Percent accuracy is collected by calculating the number of target responses divided by the total number of opportunities. Some examples of this measure of data collection include:

  • Percentage of spelling words spelled correctly
  • Percentage of correct math problems
  • Percentage of items correctly identified

You can record frequency by tracking the number of each instance of a behavior. Collect frequency data with counters, tallies or a similar technique. Some examples of this measure of data collection include:

  • Number of words read
  • Number of times a student gets out of their seat
  • Number of times students raise their hands

Duration is measured by tracking how long a behavior occurs. To record duration, start a timer when the behavior commences and stop the timer when the behavior ceases. Some examples of this measure of data collection include:

  • How long a child engages in tantrum behavior
  • How long a child engages in peer interactions
  • How long it takes to complete lesson plans for one week

Rate is calculated by recording the number of behaviors per unit of time. Some examples of this measure of data collection include:

  • Number of words read per minute
  • Number of math problems completed per minute
  • Number of tantrums per hour

Interval data can be used when tracking each occurrence of behavior is not possible, or when the start and end time of the behavior is not clear. You can also use interval data to obtain a sampling rather than an exact count. Also you can measure interval data by determining a preset time interval and then marking whether the behavior occurred during that interval. Some examples of this measure of data collection include:

  • The occurrence of body rocking
  • The occurrence of staying in an assigned area
  • The occurrence of off-task behavior

Why is baseline data important and when is it used?

Without baseline data, many educators run the risk of failing to show progress in a number of student populations, such as with at-risk students, English language learners or students with disabilities.

Baseline data should always serve as a starting point for instruction. It justifies the need for behavioral intervention plans and allows for shifts in instruction that help every student achieve progress. Also it aids in proper selection of skill acquisition activities and allows educators to determine appropriate interventions with a degree of accuracy that increases likelihood of student success.

With baseline data, educators can essentially create a roadmap for students to achieve their educational goals and gain the support they need to master skills, lessons and more. Despite growing needs and changes in the educational landscape in America, baseline data continues to be a useful tool for educators to track and analyze student progress across the country. When you use data to guide instruction, there’s no telling what you’ll discover.

But one thing’s certain: You’ll create a dynamic and individualized experience your classroom that will move your students and school forward.