PrOF Training Brad Brazil Kathy McLain Norv Wellsfry

The role of PrOF The role of PrOF An overview of the PrOF process An overview of the PrOF process Overview of data analysis techniques Overview of data analysis techniques Suggested timelines Suggested timelines Resources Resources Outline

Role of PrOF

Course SLO Assessments Program SLO Assessments PrOF (Program Overview and Forecast PrOF (Program Overview and Forecast UNIT PLAN Program Level Data The Role of PrOF

UNIT PLAN CAPITAL OUTLAY CAPITAL OUTLAY CLASSIFIED STAFFING FACULTY PRIORITIZATION OTHER Links to Budget

UNIT PLAN GRANTS AGENDA SHORT TERM FACILITIES PLAN EDUCATIONAL MASTER PLAN STRATEGIC PLAN MANAGEMENT GOALS AND OBJECTIVES Links to Planning

Overview of PrOF Process Section I – Part A

PrOF Overview Section I, Part A – Assessment/brainstorming Program Identification Program Identification Looking Back (summary of accomplishments – linked to Strategic Plan Goal) Looking Back (summary of accomplishments – linked to Strategic Plan Goal) Data Review (Trends, Differences, Strengths and Opportunities) Data Review (Trends, Differences, Strengths and Opportunities) –Instructional program data Instructional program dataInstructional program data Generation of planning ideas Generation of planning ideas –to build on strengths/accomplishments –in response to the opportunities

A Guide to Analyzing PrOF Instructional Data Packets

Student Access and DemographicsStudent Success Available Data The PrOF data packets graphically and numerically represent each of the demographic and outcome measures listed above. The past four academic years are analyzed and displayed in the charts to allow you to track trends over time. Departmental Student Enrollment by: Age group Age group (collapsed) Gender Ethnic group Educational goal Educational level Instructional mode Course level Freshman status English primary language Departmental Average Course Success Rates by: Age group Age group (collapsed) Gender Ethnic group Educational goal Educational level Instructional mode Course level Freshman status English primary language Semester-to-semester persistence rates Departmental WSCH/Instructional FTE/Productivity Degree and/or Certificates Awarded

GLOSSARY OF TERMS Course Success Rate - the average percent of students who successfully complete a class with a grade of "A", "B", "C" or "CR" compared to the overall number of students enrolled in the class. (Students who dropped out before the fourth week of classes are automatically excluded from the calculation.) Numerator = Number of students (duplicated) with A, B, C, CR Denominator = Number of students (duplicated) with A, B, C, D, F, CR, NC, W, I Persistence - the percentage of students who enroll in a particular department (regardless of course outcome) for a given semester that enroll at the college in the subsequent semester.

GLOSSARY OF TERMS (cont.) Duplicated Enrollment - the number of total enrollments in a particular department. A student is counted for every individual enrollment in a particular department during a given term; in other words, if a student enrolls in three courses in a given department for a given term, they are counted three times. WSCH – acronym for Weekly Student Contact Hours. This is the total student contact hours for the semester. FTE – acronym for Full-Time Equivalent. A professor teaching a full load would be considered to be 1.00 FTE. Professors teaching overload or having a reduced teaching load for a given semester are adjusted accordingly. Productivity – the result of dividing the total FTE into the total WSCH.

Departmental dataCollege-wide data Differences, Changes and/or Commonalities “Looking back” at what happened Overview of the Data Analysis Process The PrOF data packets are arranged so you can look at trends within your departmental data and compare it with the College as a whole. In many cases, you might find that your departmental trends closely mirror overall College-wide trends, but you may see that your departmental trends differ greatly from the College-wide data. This may have implications for departmental planning.

Identifying Trends Within your data Within your data –Increases over the past four years (upward tendency in the graph) –Decreases over the past four years (downward tendency in the graph) –Cycles in the data (an up and down pattern in the graph) –Noticeable changes over a shorter time period may warrant further investigation, particularly if present on multiple slides Examples Examples

This graph shows that the department is experiencing an increase in the percentage of African American and Hispanic students and a corresponding decrease in the percentage of Asian/Pacific Islander and White students. A Guide to Data Analysis for Instructional Programs

This graph shows that course success have improved for both modes over the past two years. Course success rates in online courses were slightly higher than other types of classes in 08-09, something that was not true in previous years. It should be noted, however, that a small number of online classes in the department may exaggerate observed trends. A Guide to Data Analysis for Instructional Programs

Identifying Differences Within your data Within your data –Look for group(s) for which the data exceeds or is below the data for other groups –Look for years where the data differs from the other years –Look for data points that don’t follow an observed trend When comparing your data with College-wide data When comparing your data with College-wide data –Look for trends that differ from College-wide trends –Look for situations where program data exceeds or is less than College-wide data Examples Examples

The fluctuation between the Fall 07 and Spring 08 headcount is much smaller than the other fluctuations, a pattern that did not continue during the next academic year.

This graph shows the department’s course success rates by the student’s enrollment status (whether or not the student was a “first-time” freshmen). Course success rates have varied over the four years. However, first-time freshmen course success rates were slightly lower compared with other students for all years prior to A Guide to Data Analysis for Instructional Programs

Comparing the department data with college-wide data shows that the department is serving a younger student clientele compared to the rest of the college (note that the scales on the two graphs are not the same). Department College wide

The department’s course success rates for African American student are greater, and have increased more, than college-wide course success rates for the same group. In addition, departmental course success rates for White students have increased, whereas college- wide course success rates have decreased. The variation in the departmental data for American Indian students may reflect the low number of students from this group taking classes in the department, which may exaggerate observed trends. A Guide to Data Analysis for Instructional Programs DepartmentCollege wide

Making Meaning from the Trends and Differences

Implications of the Data Program strengths can be identified from Program strengths can be identified from –Increases/upward trends within the departmental data (overall or in one group) –Areas in which the departmental data exceeds college-wide data –Differences within the departmental data Opportunities can be identified from Opportunities can be identified from –Decreases/downward trends in the departmental data –Areas in which the departmental data is below college-wide data –Differences within the departmental data –Factors that might be limiting the growth and/or the success of students in the department.

Generating Planning Ideas Extending or expanding programs and/or changes that may have contributed to program strengths or improvements Extending or expanding programs and/or changes that may have contributed to program strengths or improvements Identifying and addressing the factors that might be negatively affecting growth or success in the department Identifying and addressing the factors that might be negatively affecting growth or success in the department Identifying and planning to implement best practices within the department or from other institutions that are similar to CRC. Identifying and planning to implement best practices within the department or from other institutions that are similar to CRC. After analyzing your Department’s Program Review Data Packets, you may be able generate planning ideas by:

Overview of PrOF Process Section I – Part B

PrOF Overview Section I, Part B – SLO/SAO and curriculum* PSLO/PSAO development/updating PSLO/PSAO development/updating –Definitions and difference –Relationship to Degree, Certificate and Course Outcomes Relationship to Degree, Certificate and Course OutcomesRelationship to Degree, Certificate and Course Outcomes PSLO/PSAO Alignment – development or reviewing/updating PSLO/PSAO Alignment – development or reviewing/updating PSLO/PSAO Assessment – reviewing/planning PSLO/PSAO Assessment – reviewing/planning * Instructional Programs Only

PrOF Overview Section I, Part B – SLO/SAO and curriculum* Curriculum Review and Planning Curriculum Review and Planning –Identification of courses that need to be reviewed/updated Identified by last review date Identified by last review date Identified by SLO status Identified by SLO status –Scheduling of course review/updating Timelines Timelines * Instructional Programs Only

Overview of PrOF Process Sections II and III

PrOF Overview Section II – Forecasting Identifying up to 5 short-term specific planning agendas to be done in the next four years Identifying up to 5 short-term specific planning agendas to be done in the next four years –Description –Rationale –Desired Outcomes –Links to Strategies in the Strategic Plan Links to Strategies in the Strategic PlanLinks to Strategies in the Strategic Plan Identifying longer term/broader planning agendas and related strategies from the Strategic Plan Identifying longer term/broader planning agendas and related strategies from the Strategic Plan

PrOF Overview Section III – Resource Needs Section III – Resource Needs –Curriculum (instructional programs only) New courses/ programs New courses/ programs Course deletions Course deletions Program Deletions Program Deletions –Related Resource needs Type/Description Type/Description Approximate Cost Approximate Cost Priority Priority

Suggested Timelines

Resources Data Analysis Data Analysis –PowerPoint presentations PowerPoint presentationsPowerPoint presentations –Podcast (in process!) Appointments/consultation/department training Appointments/consultation/department training Examples (Coming soon!) aff/Planning/Program_Review.htm Examples (Coming soon!) aff/Planning/Program_Review.htm

Relationships Between Outcomes