Learner data can be used in the creation of class and individual goals. To effectively build a classroom culture of blended learning, goals created from classroom data must be within reach of all learners. However, individual goals can be set as a motivator for learners working to achieve specific standards in which they may have under-performed.
Software generated learner data can also effectively inform instructional methods and implementation fidelity. Using the data to target specific standards that the classroom or individual is struggling with can allow the educator to review or allocate more instruction time and practice for that concept. In addition to performance within the classroom, learner data can be used to determine program implementation effectiveness on a school and district level when compared to grade level peers by incorporating classroom factors that don’t just target the instructor.
Outlier learner data and program flaws are also identifiable through examination of learning data. Changes in learner scores or data that doesn’t make sense can serve as a learner intervention screening tool for a specific focus or could show a flaw in the program itself. Additionally, data from one software can be compared to another software to identify consistencies or discrepancies in those programs.
Data utilization and processing can be overwhelming and difficult for educators new to blended learning approaches. Shared ownership and value of data within the school is critical, and teachers must be supported as they become more fluent in their data analysis. The creation of goals and learner-lead tracking can encourage learner involvement and share accountability for progress. In an adaptive and learner focused blended environment that requires monitoring, we want to use data to not only pin-point problems or discrepancies, but solutions to where improvements can be made.