Welcome to the Graduate Data Collection System which tracks data at a concept based, rubric level, providing means for measuring Student Learning Outcome (SLO).

The system has been developed to provide a repository for programs and faculty to store pertinent data related to A&E and End of Phase (P1-P3) assessments/courses. The system provides faculty the ability to easily visualize and analyze their data to determine students’ mastery of SLOs. An example of how the system can be used is that it may be useful to review your students’ performance on their P1-3 assessments by courses and indicators to explain the areas that need more attention to master the learning outcomes expected. An individual student’s performance can easily be displayed and used while meeting with the student.

The system contains three modules:

Module 1: Build a rubric that defines the parameters including the descriptors and indicators primarily.

Module 2: Enter scores by selecting a semester, course, and a specific rubric that was built in “Module 1” and then begin entering scores per student based on the parameters defined. Once the data is submitted, the data sources are updated.

Module 3: This module is where the data captured becomes worthwhile. In addition to the above, we can develop customized visualization tools specific to your needs and requirements.

Our Graduate Data Collection System can use multiple data sources to provide a single visualization view, also known as a dashboard. The dashboard is most valuable when the Software and Data Analysis Team can work with faculty from each program. Visualization views should ultimately specific questions.

Dashboards may also integrate, combine and compare collected in “Module 2”, with examples including data from Banner, comprehensive test results, and measurements from state and federal agencies. Faculty from each program should drive the design, collaborate with the Software and Data Analysis Team to define the specifications including what to compare, what types of dashboards (e.g., graphs, charts, reports, detail). Other specifications include who may have accessibility permissions, de-identification of any data, groupings, sorting, slicing and dicing, filters, and custom calculations to output specific information.

Caveat: It is crucial that faculty clarify accessibility of program, student and course data. Based on their instruction to meet FERPA guidelines, the Software and Data Analysis Team, will implement accessibility and security rules to the dashboards.