NIU has created an online training to help K-12 teachers to make data-informed decisions that will improve learning in their classrooms.
Todd Reeves, an assistant professor in the Department of Educational Technology, Research and Assessment (ETRA), and ETRA doctoral candidate Jui-Ling (Raye) Chiang, developed the “D5x4: Data in Five by Four” training.
More than 200 in-service teachers and pre-service teachers currently are participating in the 10-hour training, which presents participants with numerous data sets to review and dissect in search of how those numbers may inform instruction.
Five refers to the number of student levels at which training participants work with data: individual; subgroup; classroom; grade; and school. Four represents the types of questions explored by participants during the training: location/identification; strengths and weaknesses; status and growth; and instruction.
“5×4” is also an allusion to the aeronautics expression meaning “loud and clear.”
“We’re grateful for the opportunity to reach out from NIU to the community and serve current and future educators in this way,” Reeves says. “Today’s teachers are inundated with data, and their capacity to use data productively is a salient but complex skillset.”
The training is also the focus of a series of experimental research studies, Reeves says.
“Our ultimate goal is to study the impact of the training on teachers’ actual classroom practices and their students’ learning,” he says. “But it’s important to first verify that the training is having an impact on more proximal outcomes, such as the teachers’ knowledge, skills and self-efficacy.”
Chiang, who’s currently teaching an undergraduate course at NIU, says she looks at data “every day.”
“Data tells me, ‘This is how I need to change my instruction,’ or ‘This is when I need to call in an individual student for an assessment or intervention, or to look at resources at NIU to help students improve their performance,’ ” Chiang says. “Data impacts me in my teaching, and if other teachers can look at their data in this way, they might do different things.”
Participants in the asynchronous “D5x4” training are required to engage in online discussions with others and both Reeves and Chiang; they also are encouraged to pose data-related questions from their own classrooms to gather ideas and advice. The training incorporates a mechanism by which feedback is automatically provided to participants as well.
Although trainees can move through the material at their own pace, each of several modules must be completed within a set time frame. They also will find the tasks growing in difficulty as they progress; for example, Reeves says it is generally easier to locate and interpret a data point than to select a suitable instructional method based on data.
Participating in the “D5x4” training should benefit every teacher, Chiang adds.
“We’ve got a pretty good framework. We feel this is a very solid way to train teachers,” she says. “Everything is lined up systematically, and the knowledge is transferable.”
Reeves and Chiang eventually will make their own data-informed decisions. Their next step is to analyze the results of their study of the current D5x4 training, before tweaking its design and carrying out further studies of its impact.
“Going forward, our goal is to offer this to as many educators as possible,” says Reeves, adding that he and Chiang also plan to write a paper and deliver several presentations regarding “D5x4.”
Their work has enjoyed financial support from an NIU College of Education Dean’s Grant for Partnerships. Kappa Delta Pi, the prestigious international education honor society, also graciously assisted with recruitment for the training.
