Data Model (cont.)

The goal is to expand this model, linking students to each individual who has an impact on their learning. The final goal is to then link the standards and assessments with the instructional practice and resources that are responsible for a particular student outcome (see the figure below).

 

 

The expanded system of data collection allows one to look at a student's learning experience over time and determine how much proportionally each individual invests into that student's learning during a given period. The ideal system should also provide information about what was taught and what was learned during the particular period. One way of thinking of this is that teaching quality is as important as, or even more significant than, teacher quality.

The data collection system should also capture information about learning objectives at the course section level, if not at the syllabus, or term/semester, level. Such data could help to identify the effectiveness of teachers so that the best can be identified and copied and the underperforming provided with the help they need to improve.

 

Combining student outcomes with course objectives could assess the effectiveness of pedagogy, instructional content, and accompanying supports for learning, providing feedback to the multiple educators connected to the particular period of student learning.

 

In order to do this systemically, one needs best practices and thoughtful, clear definitions along with policies and processes for implementing and managing unique teacher and student identifiers. These processes need to align with classroom rosters and with individual student outcomes to establish a valid and reliable TSDL.