PrOF Training

1. PrOF Training Brad Brazil Kathy McLain Norv Wellsfry

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

3. Role of PrOF

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

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

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

7. Overview of PrOF Process Section I – Part A

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

9. A Guide to Analyzing PrOF Instructional Data Packets

10. Available Data Student Access andDemographics Student Success Departmental Student Enrollment by: Departmental Average Course Success Rates by: Age group Age group Age group (collapsed) Age group (collapsed) Gender Gender Ethnic group Ethnic group Educational goal Educational goal Educational level Educational level Instructional mode Instructional mode Course level Course level Freshman status Freshmanstatus English primary language English primary language Semester-to-semester persistence rates Departmental WSCH/Instructional FTE/Productivity Degree and/or Certificates Awarded 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.

11. 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.

12. 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.

13. Overview of the Data Analysis Process “Looking back” at what happened Departmental data College-wide data Differences, Changes and/or Commonalities 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.

14. Identifying Trends • 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

15. A Guide to Data Analysis for Instructional Programs 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.

16. 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.

17. Identifying Differences • 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 • Look for trends that differ from College-wide trends • Look for situations where program data exceeds or is less than College-wide data • Examples

18. 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.

19. A Guide to Data Analysis for Instructional Programs 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 08-09.

20. College wide Department 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).

21. A Guide to Data Analysis for Instructional Programs 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.

22. Making Meaning from the Trends and Differences

23. Implications of the Data 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 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.

24. Generating Planning Ideas 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 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:

25. Overview of PrOF Process Section I – Part B

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

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

28. Overview of PrOF Process Sections II and III

29. PrOF Overview Section II – Forecasting • 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 • Identifying longer term/broader planning agendas and related strategies from the Strategic Plan

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

31. Suggested Timelines

32. Resources • Data Analysis • PowerPoint presentations • Podcast (in process!) • Appointments/consultation/department training • Examples (Coming soon!) http://www.crc.losrios.edu/Faculty_and_Staff/Planning/Program_Review.htm

33. Relationships Between Outcomes