Factors that impact data-based decision making in educational settings

April 27, 2022

Key Takeaway: The study explores factors that affect data-based decision making (DBDM), which has been established as an essential part to student progress, particularly for those with learning differences. The article outlines the importance of effective, frequent training to allow educators to build confidence and experience in analyzing data and transforming this data into meaningful adapted instructions for their students to ensure progress. The lack of training and universal rules of application hamper the potential of DBDM in education. —Frankie Garbutt

In this study, Oslund, Elleman and Wallace (Middle Tennessee State University) argue that to evaluate the effectiveness of “tiered instructional systems,” one must essentially rely on the correlation between frequent assessment of students with academic difficulties and educators’ skills to “make decisions using student data.”

In most states across the United States, it is legally mandated that schools implement multi-tier instructional systems. However, “data-based decision making is being adopted worldwide, yet relatively little research exists on the relations among variables impacting teachers’ ability to read, interpret, and inform instruction,” argue Oslund, Elleman, and Wallace. In their research, they analyzed teachers’ ability to interpret “student progress-monitoring data presented graphically (i.e. graph literacy).” They also investigated whether a teacher’s confidence in interpreting data, experience, or targeted pre- or inservice training on data-based decision making (DBDM) impacted their graph literacy to improve student achievement. 

In their findings they discovered the following:

• Teacher experience had impacted their graph literacy, yet did not impact their confidence in analyzing data. 
• Training had a large effect on teacher confidence, which confirmed previous studies referred to in the article. Professional Development “is one possible way to directly influence their confidence and potentially indirectly influence their use of data.”
• Training increased teacher confidence “but had no impact on their assessment knowledge.” 
• “Teachers who are skilled at DBDM are more likely to adapt instruction to meet student needs.”
• “Unless and until teachers are properly equipped with DBDM knowledge, the effectiveness of tiered instruction may lag behind its potential.”

Therefore, the study suggested further research into what format and frequency of training would be required to increase effective use of data-based decision making.

The results of the findings also highlighted the limitations of the research. Admittedly, the data collected was “susceptible to bias” and “sample size is too small to examine differences beyond basic descriptives” relating to implementation of tier support systems within or across states. Moreover, the lack of universal rules for DBDM can result in two different teachers looking at the same graph and making different decisions.

Overall, it was concluded that “the promise of DBDM is established, but the need to further develop models and create consistency is an urgent and productive step toward increasing its effectiveness.” 

Article summarized: 

Oslund, E. L., Elleman, A. M., & Wallace, K. (2021). Factors Related to Data-Based Decision-Making: Examining Experience, Professional Development, and the Mediating Effect of Confidence on Teacher Graph Literacy. Journal of Learning Disabilities, 54(4), 243–255. https://doi.org/10.1177/0022219420972187

Summary by: Frankie Garbutt—Frankie believes that the MARIO Framework encourages students to become reflective, independent learners who progress at their own rate.