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Collecting Data

By collecting data systematically, we are able to improve our programs and the unit as a whole.

As reflected in the Data Collection and Reporting Process, we collect data around the main transition points (admission, advancement to culminating experience, and exit). We do so through a variety of means, including signature assignments, surveys, focus groups, and examinations.

These data are used at the program, department, and unit levels (with student learning data aggregated at the unit level around the Conceptual Framework, CSULB, and NCATE standards) to inform changes in policies, practices and services-all with the goal of support student learning and success.

Over time, the Assessment Committee has articulated a series of expectations regarding the collection of student learning data. The committee has said that program faculty should:

  • Collect data on student performance via signature assignments in all sections of the course and each time the course is offered.
  • Use rubrics to collect student performance data related to signature assignments, as a way to ensure fairness, accuracy, and consistency.

While there is some variation, the signature assignment data collection process in the College is largely centralized:

  1. Faculty collect data on student learning via signature assignments and report these data to the Assessment Office via either TaskStream or specially formatted Excel worksheets.
  2. The Assessment Office compiles and analyzes the data around:
    1. Individual program-level learning outcomes (over one or more years based on each program’s assessment plan)
    2. Elements of the College’s Conceptual Framework, CSULB learning outcomes and NCATE Standard 1.
  3. These data are then shared with:
    1. Individual programs to show student performance on various learning outcomes.
    2. The College Assessment Committee, Faculty Council and other bodies, using tables that show student performance across programs.
  4. These groups review these data in data discussion meetings, making interpretations of the data and determining actions needed for program improvement.