Evidence and Data
SCC is gearing up to write the Self-Evaluation for our next accreditation visit. Many of you will hear that
we are looking for “evidence” to support our evaluation of our work here at the college. We thought
that it might be useful to define that term, “evidence”, and put it into a bit of perspective with respect
to accreditation.
Why are we collecting evidence and data?
1. To give us a better understanding what we’re doing. This provides clarity of “view” and a shared
understanding of process, trends, etc.
2. To ensure program effectiveness and support program planning, including resource allocation.
3. To respond to internal and external organizations that asks us to be accountable for our work, for
example – Accreditation.
What counts as evidence?
Evidence can be: descriptive evidence, qualitative data, or quantitative data. Evidence isn’t the same as
casual observations (anecdotes). It does include systematic observations, indicators, and pattern
analyses.
Systematic Observations: This includes counting things and noting events. It is used to look for possible
patterns; the key word is “systematic”. This is a key part of what we report to ACCJC. Examples include:
• Direct observation of student skills or behaviors (such as SLO assessment)
• Indirect measures of student attitudes, behaviors and perceptions (e.g. surveys of students)
• Systemic descriptions of actions by committees, senates, etc. In this case, evidence can be
the minutes from meetings or other descriptive evidence.
• The results of surveys can be used to show if people believe that processes work well.
• An analysis of the results of those processes can provide data. E.g. the results of our
planning processes, such as unit plan achievement report results provide that type of data.
Indicators: These are single numbers that can be affected by many factors. They don’t give us
answers, but do tell us when to start asking more questions. Examples include:
• Indicators for college goals
• Overall student course success rate, number of students completing degrees/certificates or
transferring, etc.
• Indicators of program effectiveness in student services
• Indicators reported as quarterly or annual achievements
Pattern Analysis: This is designed to find patterns in a set of data. It may be based on careful
systematic observations. We often look for trends over time or comparisons between groups. In some
cases, we may find predictors of outcomes (note predictor isn’t the same as establishing causation).
Pattern analysis is important for planning. Examples include:
• Prerequisite analyses
• Trend analyses of use of services
• Analyses of achievement gaps in student success
• ARCC Scorecard metrics
What’s the link between Accreditation and evidence?
ACCJC notes that good evidence:
• Is intentional and purposeful
• Informs dialogue and has been reflected upon
• Has been interpreted and is presented in a context
• Is corroborated by multiple sources of information
• Is coherent and complete and provides guidance for improvement
• Its service area
ACCJC requires that data should demonstrate the institution knows about:
• The needs of incoming students
• The needs of enrolled students
• What students are achieving
• What students are learning
• How students are being supported