Assessing Student Learning in Higher Education
In the simplest
definition, quality data:
The Assessment Loop
Do you know what really works in your teaching,
counseling, student service, etc.? The assessment loop is a data-driven
method of decision-making based upon a learning paradigm, in which we
are learners about our own methods and institutional processes. The loop
begins with questions posed concerning what works and what does not,
what enhances student learning and what does not. To determine the
answer to the questions an assessment or investigation is initiated. The
investigation generates data to answer the question. When
carried out as an integrated part of the educational process it is often
referred to as the scholarship of teaching. By analyzing our teaching
methods and learning outcomes, we can improve the process based on
information gleaned through assessment, rather
than running on intuition. The goal is to create a culture of evidence
for institutional decision-making.
The key to this process is quality data. You may have heard these quotes
about statistics and data:
In this material, quality data are defined as :
Valid - the data accurately represents what you are trying to
measure. For instance the number of people that graduate don't
necessarily represent good data on what has actually been learned.
Authentic - the assessment simulates real-life circumstances. Also see the link to Grant Wiggins article on authentic assessment.
Relevant - the data answers important questions, and is not generated simply because it is easy to measure.
Effective - the data contributes to improving teaching and learning.
Resources and Links
Using Data from
Program Improvement: How Do We Encourage Schools To Do It?