Data-Driven Decisions: How to Help Teachers Choose EdTech Tools

With the recent ubiquity of technology available to teachers, especially following COVID as well as many states adopting changes and adding new expectations to technology standards for learning, it can be intimidating to decide which tool best suits you, your teachers, your students, and your school site. The easiest way to begin your search is to start with the same resource you use to make other decisions for instruction: data. 

Student performance data is important when driving instructional practice and approaches to learning, so why not use data when choosing technology for the classroom? You can leverage your instructional coaching insights as data to determine the technology needs of the classrooms you visit. In addition to needs-based data, you will also want certain demographic data such as student age/developmental appropriateness, content area (i.e. STEM, Literacy, Fine Arts, etc.), the ratio of student to device access, and an at-home internet connection, and student privacy protection policies (COPPA) to inform your decisions and/or purchases. When possible, survey teachers for their interests in educational technology. Teacher “buy-in” data may contribute to multi-classroom use and/or school-wide adoption. All of these data points ultimately narrow your search for the right technology tool. Once these tools are in place, it’s important to establish consistency, fealty, and clarity in how to use these tools to determine long-term effectiveness. 

While the following may not offer an exhaustive list of tools, remember to prioritize what the data divulges through your coaching efforts.  

Classroom Management

If the teacher(s) you work with struggle with classroom management, choose the areas the data reveals they need the most support with, for instance setting expectations with Class Dojo; establishing procedures with a wireless doorbell or color-changing smart lights; or transitioning between activities using visual cues on Classroom Screen. While many educational technology tools can be facilitated through a quick test-and-trial micro-coaching cycle, these tools and strategies require a multi-week cycle and subsequent data to truly determine efficacy in individual classroom settings. 

Formative Assessment

Many teachers express a need for meaningful and intentional formative assessment methods. While many online curriculum programs tout their tool as “the best” for formative measures, sometimes assessment efforts are all in the approach. This is why looking at the data from your coaching cycles is important, to concentrate on the areas in the classroom that need support. For example, if the teacher needs formatively assess during instruction, students can easily respond to a digital exit slip with an emoji of how their grasp of the lesson is best represented, tap a designated color push-light at their workspace, or respond to a quick live poll like Poll Everywhere. Many teachers need students to “show what they know”, in which students have the opportunity to create or apply what they have learned through interactive platforms that offer interactive and demonstrative tools including video, audio, and graphics such as SeeSaw, Explain Everything, Loom, or Kami, all of which allow teachers to provide real-time formative feedback. Of course, when post-instruction data is needed, teachers can deliver digital quizzes available with Google or Microsoft Forms as well as utilize competition or game-based quizzes with Kahoot or Blooket.  

Student Engagement

One thing to bear in mind: just because it looks engaging does not mean it’s what is best for students. This is where teachers often feel inundated with options for implementing technology. Again, the selection technology tools will need to come back to data. For example, competition-based engagement tools like Kahoot which require speed and accuracy will not work well for a classroom that has students with processing disorders. Similarly, programs that allow students to “move on” to the next phase/level after guess-and-check “attempts” is not demonstrating true mastery and will only continue to frustrate the learning process; whereas, a program like NoRedInk will not allow students to progress until they have demonstrated mastery three times consecutively. In addition to data, consider what the learning intention is behind the decision to implement the technology. If the coach notes that student participation is low, then being able to interact with the content delivery materials in real-time to avoid “sit-and-get” fatigue would lend itself to Nearpod or Peardeck. If teachers want students to work on collaborative skills as well as show competency in the lesson task or concept, try Goosechase or BreakoutEdu. If observational data shows students need more real-world authentic, yet safe, writing experiences, then try Storybird or Kidblog. If accommodations require students need more hands-on or tactile learning experiences, younger grades could turn to Beebots and Osmo while older students can attempt Coding programs or Virtual/Augmented Reality devices with a multitude of applications to their learning experience. If students are having difficulties synthesizing texts or concepts, advocate for a multi-genre or project-driven research assignment online which allows student choice and opportunities to explore Open Access Research Libraries, digital libraries, story-boarding, video/movie creation or slide/presentation creation, graphic design, and more. Student engagement opportunities with technology are almost limitless today which is why we, as educators, need to choose what is best for learning with specific evidence to support that choice.

Data is the Deciding Factor

Technology is everywhere and it’s definitely not leaving schools. With the drastic changes in educational technology expectations since 2020, it can feel daunting and all-consuming. Please remember, a device screen with kids clicking and poking around or a website with flashy graphics and fun videos does not mean the technology in front of the student inherently contributes to the learning process. Collect and evaluate coaching cycle data, student performance outcomes, classroom observational notes, educator anecdotal records, teacher-interest survey results, administrative insights, state standards technology requirements, and even student input (when applicable or permissible) before introducing or purchasing technology for the sake of teaching and learning. 

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