v1n3 Constructing A Data Base: Perspectives, Principles and Practice
The need for a common data base for all levels of education has been a pressing theme in both state and federal agencies for the past decade. A common data base occupies
a position of central importance in the trend toward scientific management in higher education. Although the nature and scope of such activities begin with the collection of data, the fact is that colleges and universities are beginning to their problems carefully -- beginning to develop all types of data regarding students, facilities, cost, and operations -- for the purpose of making informed decisions.
The pressures of declining enrollment and budget retrenchment no longer allow colleges and universities the luxury of trail and error in their management procedures. The management science techniques now available permit an objective comparison of alternatives in terms of specified goals and thereby permit institutions to achieve greater efficiency in their external/internal operations.
Greater attention must be given to identifying,defining
and collecting, on a systematic and timely basis, the data needed for informative decision making and planning.
The primary purpose of data collection and analysis is to base the decision making process on reliable information, gathered and analyzed over a period of time. It is assumed that institutional decision making will rest on factual and objective foundations, rather than a figment of someone's imagination.
The trick to data base construction is to find a limited number of key factors upon which the data can be organized and updated over a period of time on a systematic basis. It will soon be discovered that as data is collected and analyzed, many new data needs will arise leading to the gathering of still more data.
THREE NEEDS SERVED BY DATA BASE CONSTRUCTION:
1. There are the day-to-day needs of various institutional
components -- some independent, some interdependent.
For these, the data collected and the data required
will vary from component to component and from month
to month, after including such routine items as class
grades, loads, etc.
2. The system will also contain general reporting information
on individual components and program needs with data
related to sources of students, projections -- serving
the kinds of reports that are developed independently
for state and federal offices, and the university administration.
3. The information system will be instrumental in institutional
decision making, planning and management.
KEYS INGREDIENTS OF A SUCCESSFUL DATA BASE:
1. Establishment of a comprehensive master plan including
a clear set of time specified goals and objectives
approved by the institution's executive managers.
2. Adequate resources to support the development and
implementation of the system over a two or three year
period.
3. Clear evidence of personal and professional commitment
by all levels of institutional management throughout
the period needed to achieve an operational system.
4. Organizational placement of the data base component
at an administrative level which will reflect commitment
to the activity.
5. The development of a specially designed and equipped
information center.
BASIC CHARACTERISTICS OF A FUNCTIONAL DATA BASE:
1. Provision of improved information system support to
chief administrators, enabling more effective and efficient
performance of their duties.
2. Provision of a more comprehensive and complete information
base to strengthen the three basic administrative processes
within the institution: planning, management and evaluation.
3. Provision of a comprehensive (i.e. accurate, timely,
integrated) yet economical information support system
to improve institutional administration and operation
-including institutional research and planning activities
- in accordance with established institutional priories.
4. Minimization of routine information processing by
chief administrators, supervisors and unit managers
in order to maximize time allotted for planning activities
by these key officials.
5. Strengthening of professional abilities of the institution's
staff, wherever possible, through utilization of more
advanced information technology.
GENERAL DESIGN REQUIREMENTS OF AN OPERATIONAL DATA BASE:
1. Provide an organizational - wide data base to
strengthen planning, management and evaluation.
2. Assist in the routine processing of data and information.
3. Provide information to support the institution's management
officials in executing their (day-to-day or long range)
responsibilities.
GUIDELINES FOR DATA BASE CONSTRUCTION:
1. Select a model. ( a typical data base model )
2. Determine implementation priorities,.
3. Determine system management.
4. Determine resources.
5. Prepare master plan.
COMMON MISTAKES AND PITFALLS IN DATA BASE CONSTRUCTION
1. Lack of an approved institutional master plan.
2. Failure to promote an understanding of its potential
impact on the institution.
3. Failure to allocate adequate resources.
4. Placement in a lower level position of the administrative
organizational structure.
5. Lack of sustained identification with the activity
by all levels of management.
GUIDING PRINCIPLES OF DATA BASE CONSTRUCTION
1. Information must be basic.
2. Information should provide a picture of institutional
components, students, staff, instruction, facilities,
etc.
3. Data from all institutional components should go to
one central location.
4. Data collected should be made available for common
use and analysis.
5. Data should have common definitions.
6. The system should be practical in terms of purpose,
time and money.
ENVIRONMENTAL DATA NEEDS SERVED BY DATA BASE CONSTRUCTION.
1. Describe the available internal and external data.
(avoid using jargon)
STEP ONE: Determine categories and sub-categories for
data. These categories should be organized around the
organizational structure of the institution.
STEP TWO: Identify questions that require answers --
the purpose for which data is needed.
1. Collect questions from all institutional components
2. Develop a common set of questions (compile list)
3. Develop uncommon set of questions (compile list)
4. Code questions which are common to all components
5. Code questions which are specific to certain components
Identify the data elements that will be needed to answer
each question.
1. Survey current data elements collected and match with
common and uncommon questions
2. Develop a review process for current data collection
instruments
3. Develop new data collection instruments, or revise
current instruments
The elements of a data base can be combined in a great
many ways to answer questions at the institution.
For example, the data base consisting of a student's
address, race, standardized test scores, proportion
of grades by class, degrees and credentials held by
faculty, space assignments, types of space and maximum/minimum
capacity can provide answers to the following questions
among others:
1. What is the student's potential?
2. How qualified is the faculty?
3. Do students who reside in one area of the state or
country perform any better in English than students
from another?
4. How adequately are we using our classroom space?
Based upon a student's standardized test scores in math,
English, and reading, what is the probability that
he/she will earn a given math or English grade?
STEP THREE:Decide which data re primary (or basic) and
which are secondary.
1.Primary Data - that which is required constantly,
each quarter or year. It is reoccurring.
2.Secondary Data - that which may be unique to a given
institution. (something nice to know - not absolutely
essential information)
STEP FOUR:Define each data elements operationally.
1. Establishes common meanings as does the Handbook
of Data and Definitions in Higher Education.
STEP FIVE:Determine the best means of collecting data.
1. Identify data sources
2. Identify instruments for the collection of data
3. Identify the methods used to analyze data -- key punch, scanner, etc.
