 |
|
|
|
1. Calculate statewide average cost of instruction of the Subject Code
Level combinations assigned to each subsidy model. This is input
to the subsidy process.
2. Provide data for the subsidy consultation for managing the relationship
between the cost of instruction in the various categories and subsidy models.
3. Provide campus representatives and other stakeholders with comparative
data about the cost of instruction.
In particular, the group discussed the following costs:
1. Fee waivers are sometimes compensation (I & G) and sometimes
scholarships (not I & G). Some of the inconsistency is based on the
relationship between fee waivers and taxable income.
2. Charge back of POM services. It is important to keep the POM part
of I & G consistent and separate from the rest of I & G because
it is a separate cost category in subsidy.
3. Charge back for computer services.
An upcoming release of the accounting manual may help to define proper coding of expenses.
The recommendation of the consultation was to poll the institutions to find out the magnitude of inconsistencies.
In Step 4, which allocates Funding Unit overhead, staff recognized that a possible misallocation of cost could happen. When a Funding Unit with large costs offers just a few courses, the large overhead of this Funding Unit may be focused, inappropriately, on too few combinations of Subject Code and Level. Lechler suggested that Regents may want to provide some upper limit of Funding Unit overhead, and when exceeded, move the excess costs to the campus level for broader allocation. Gutowski suggested that if the Funding Unit in question is an academic unit then this large overhead is appropriate. Moreover, DeYoung suggested that administrative units would not likely appear as Funding Units.
The case of an administrative unit (such as the library) offering a course should be cause for splitting its costs into a special unit for the course offering part of the administrative unit.
Lechler wondered about the large number of Funding Units that currently appear in the Funding Unit Inventory and the fact that less than 10 percent of them offer any courses. The consultation suggested that these Funding Units would likely not have any Funding Unit expenses.
There was also a discussion of the other data to display in addition to the allocated costs.
Student FTE, broken down by Student Rank was discussed and is obviously needed.
Faculty data associated with the instruction is more problematic.
Lechler suggested reporting Faculty (instructional) FTE broken down by Faculty Rank, based on an FTE derived from the instructor's teaching load. In addition, class size would be reported. He argued against reporting head count due to its varied meaning based on different instructional relationships and the operational problems associated with providing unduplicated head counts at the higher levels of aggregation. However, unduplicated head counts are calculable at all levels of aggregation.
Dalton suggested reporting the number of Course Credit Hours associated with the instructors in the aggregation broken down by the Rank of the instructor (with Part Time appearing as a Rank). These credit hours would be real data rather than a derived FTE. In the case of team teaching, the Course Credit Hours would be prorated among the instructors the same as in Step 1 of the cost allocation.
A second suggestion of the consultation was to show class size as a frequency distribution, rather than average class size. This suggestion was in response to a discussion of the various interpretations of course sections that are really individual instruction. There is a code for Individual Studies course sections in HEI. However, there have been many courses with one or two students not coded as Individual Studies and vice versa.
The problem of class size is confounded by dual listed courses and the various configurations of lecture/lab classes. Lechler pointed out the UIS requirement for dual listed courses to accommodate varying levels of instruction is not present in HEI. However, there remain campus requirements for dual listed courses and sections.
HEI could also have a variety of statistics displayed to aid interpretation. A link should be provided to the definition of these statistics in order to facilitate understanding.
The group reviewed the suggested list of Subject Fields from the CIP Code Subcommittee.
Based on the HEI data, Lechler suggested refinements in the Subject Field definitions in an e-mail to the consultation dated December 11, 1998. All of these refinements were approved by the consultation including the ones relating to new Subject Fields within Engineering and Business.
How to Carry Data to Subsidy Consultation?
The group discussed an apparent dilemma in the ongoing responsibility of the Subsidy Consultation to manage the relationship between cost of instruction and Subsidy Models.
In UIS this information was given as a cost per combination of Program and Level. In HEI Subject Field and Level was designated as the unit of measure. A problem is that during the UIS to HEI transition Regents chose a particular model for every combination of Subject Code and Level. Regents did that to minimize movement of FTE from model to model in the transition. As a result, some Subject Codes in a Subject Field currently map to a different model than the majority of Subject Codes in the Subject Field.
The group reviewed the spreadsheet that was attached to the sixth question (e-mail dated April 5, 1999). It has a row for every combination of Subject Code and Level and shows FTE in that combination using spring and summer 1998 enrollments. It also shows the Subject Field and model to which it belongs. Finally it shows misplaced FTE for Subject Codes in a different model than the majority of the Subject Codes in the Subject Field.
The group identified that these "misplaced FTE" fall into several categories:
1. They may be a carry over from the UIS practice of relating courses
to their source of funding rather than subject matter. In this case the
Subject Codes should probably be reassigned to the predominant model for
the Subject Field.
2. They might reflect differing costs of instruction. In this case
they should remain an exception for the Subject Field.
3. They might represent an unusual selection of Subject Code for particular
courses. In this case a different Subject Code should be used.
Jones suggested that this issue should be brought to the attention of the Course Inventory Peer Review Committee. Gutowski suggested that the group study the results of cost allocation in the first biennium of HEI and consider some basic relationships between cost of instruction and subsidy models. He reminded participants that the number of models has varied over the years of enrollment-based subsidy.
Lechler suggested that when HEI first runs the RA programs in production,
there will likely be problems related to any of three causes:
1 Programs won't work.
2 Cost allocation algorithm produces unexpected results.
3 Data anomalies requiring changes to the programs.
Testing the programs with realistic data ahead of time will be helpful. HEI already has enrollment and facilities data in production. Moreover, financial data is in practice. If an institution could practice with estimated FY 1999 financial data HEI could use it together with the production enrollment and facilities data for testing. Alternatively, if some institution practices with FY 1998 financial data and the Funding Unit taxonomy doesn't change between FY 1998 and 1999, we can use the FY 1998 data adjusted for inflation for testing. Lechler encouraged institutions to test the financial data.
Return to Resource Analysis Home Page
http://regents.ohio.gov/hei/RA/notes/ranotes05201999.html
Last updated May 26, 1999