This document summarizes a presentation on examining longitudinal data to advance institutional effectiveness and student completion. The key findings were that socioeconomic status (SES) is the main factor influencing student achievement outcomes, with low SES resulting in lower outcomes. Resource allocations differ between low and high SES institutions, with low SES schools spending more on administration and student support, and less on instruction. Higher spending on instruction and lower proportional spending on administration and student support relate to better student outcomes. The implications are that SES accounts for most achievement variation, and colleges should focus improvement efforts on the modest area outside SES impacts through establishing internal research institutes to conduct input-environment-output studies using tailored longitudinal data.

1. A Framework for Examining Tailored Longitudinal Data
to Advance Institutional Effectiveness
and Student Completion
Center for Research on Educational Access and Leadership
2015-2016 Colloquium Series
October 7, 2015
Dr. David El Fattal
Vice President of Business Services
Cerritos Community College District

2. 1
Topic Background
 Public scrutiny of colleges and universities has escalated to a high
level as taxpayers, students, and policymakers alike want to know
they are receiving quality, value, and institutional effectiveness for
the price they pay (Alfred, 2011; Bailey, Jenkins, & Leinbach, 2005; Boggs, 2011;
Ewell, 2008a, 2011; Head, 2011; Shulock, Offenstein, & Esch, 2011).
 Increasing core student completion outcomes such as certificate,
transfer, and graduation rates is a critical public policy goal (Assembly
Bill 1417, 2004; Douglass, 2010; Ewell, 2011; Gansemer-Topf & Schuh, 2006; Little
Hoover Commission, 2012; Obama, 2009; Senate Bill 1456, 2012; Shulock & Jenkins,
2011; Titus, 2006; Tschechtelin, 2011).

3. 2
Topic Background
 A limited number of higher education studies have examined the
relationships between institutional expenditures and student
achievement outcomes (Hamrick, Schuh, & Shelley, 2004; Pike, Smart, Kuh &
Hayek, 2006; Pike, Kuh, McCormick, Ethington, & Smart, 2011; Ryan, 2005; Scott, Bailey, &
Kienzl, 2006; Walpole, 2003; Webber & Ehrenberg, 2010).
 To What Degree Does Money Matter for Student Success?
Dissertation research was first study of California Community
Colleges examining the relationships between institutional
expenditures and student attainment milestones outcomes
(El Fattal, 2014).

4. 3
Purpose of the Research
The purpose of the research was to identify whether, or to
what degree, the allocation of institutional expenditures for
instructional, student support, administrative, and total
educational and general activities influenced the student
success outcomes and indicators of SPAR, thirty-unit
completion, and persistence at the 72 districts and 112
institutions that comprise California Community Colleges
(California Community Colleges Chancellor’s Office, 2010).

5. 4
Research Methodology and Design
 Conducted a quantitative, non-experimental, correlational study
with an explanatory research design and post-positivist theoretical
foundation.
 Highly skewed data resulted in a series of bivariate analyses
instead of the initial plan for hierarchical linear regression.
 Underlying research focus was to better understand the
relationships between institutional expenditures and student
attainment outcomes.
 Sought to identify the nature, direction, and strength of the
associations between 46 pairs of variables.
 Utilized Astin’s (1993) Input-Environment-Output (I-E-O) model as
conceptual framework.

6. 5
Input Variables
Mediating
Environment Variables Output Variables
1 Socioeconomic status
Instructional expenditures
per FTES
SPAR—student progress and achievement
rate
2
District Type
– Single-college district
– Multi-college district
Student support expenditures
per FTES
Thirty-unit Completion—percentage of
students who earned at least 30 units
3
Administrative expenditures
per FTES
Persistence—persistence rate
4
Total educational and general
expenditures per FTES
5
Ratio of instructional cost to
total cost
6
Ratio of student support cost
to total cost
7
Ratio of administrative cost to
total cost
8
Ratio of instructional cost to
student support cost
Research Methodology and Design

7. 6
Research Methods
Data collection and management
 All source data were publicly available from the U.S. Census
Bureau (2013), or the California Community Colleges
Chancellor’s Office (2010, 2011a, 2011b).
 All data were accurately combined into one dataset of records
for individual colleges and college districts.
 Multi-college district SES and outcomes variables were
computationally weighted from the values of individual
colleges.
 Highly skewed data resulted in a series of bivariate analyses
instead of the initial plan for hierarchical linear regression.
 All data (except district type) were transformed into ordinal
variables of low, middle, and high status.

8. 7
Research Findings

9. 8
Key Findings and Interpretations
(a) SES was the key influencing factor for the attainment of each
outcome: SPAR, thirty-unit completion, and persistence. Low SES
resulted in low outcomes. High SES produced high outcomes.
(b) Resource allocations for administrative, student support, and
instructional expenditure categories were significantly different for low
SES and high SES institutions.
(c) Low SES districts spent comparatively more than high SES districts on
administrative functions and student support activities, and
comparatively less on direct classroom instruction.
Meanwhile, high SES districts did the inverse and spent comparatively
less than low SES districts on administrative functions and student
support activities, and comparatively more on direct classroom
instruction.

10. 9
Key Findings and Interpretations
(d) Higher proportional spending on instructional cost was related to high
outcomes.
(e) Higher levels of spending on student support activities or administrative
activities in relation to total costs were related to lower levels of SPAR
and thirty-unit completion.
(f) The SES of the student population drove the allocation of resources
among expenditure categories.
(g) Low SES institutions typically serve large populations of underprepared
students and have reason to allocate resources differently than do
higher level SES institutions.

11. 10
Abridged Implications
 Substantially changing student demographics will continue to bring an
influx of underprepared students to community colleges (Crisp & Nora, 2010;
Prescott, 2013).
 Annual budgets of California Community Colleges will continue to be
intermittently impacted by potentially volatile revenue swings, providing
crucial opportunities to reprioritize spending in alignment with legislative,
system, and institutional imperatives.
 State and federal governments, and other stakeholders, will continue to
pressure institutions to increase student completion outcomes,
especially degrees, through the efficient and effective use of finite
taxpayer dollars.
 SES may account for 60%–70% of student achievement (Coleman et al.,
1966; Marion & Flanigan, 2001), leaving little room for other variables to have
much impact on the attainment of outcomes.

12. 11
Abridged Implications
 SES is widely accepted as a leading influencing factor for student
achievement. In studies that have examined SES as a variable of
interest, the impact of SES on outcomes has been considerable
(Astin, 1993; Coleman et al., 1966; Marion & Flanigan, 2001; Pacheco, 2012; Titus, 2006).
Future research should purposefully and consistently integrate SES
into quantitative and qualitative student attainment research.
 Astin’s (1993) I-E-O model has been a durable, prominent, and
influential research framework utilized for decades to study
the impact of college on the outcomes of how students grow or
change, cognitively and non-cognitively. Traditionally, this framework
has not been used to examine the allocation of expenditures or
completion outcomes. Future research should consider doing so.

13. 12
Central Recommendations
 The modest zone outside the impact of SES is where researchers,
policymakers, and practitioners should focus improvement efforts to
increase student attainment.
 Each college, on its own or through a consortium, should become a
self-directed I-E-O (Astin, 1993) research institute to gain a tailored,
longitudinal, empirical basis for improving institutional effectiveness,
cost effectiveness, student development, student completion, and
other self-identified outcomes that are important for fulfilling the
mission of the organization.
 The California Community Colleges Chancellor’s Office should provide
start-up funding through a grant process to establish up to 10 internally
focused I-E-O research institutes for interested and capable districts.

14. 13
I-E-O Framework

15. 14
Input Variables
Mediating
Environment Variables Output Variables
1
2
3
4
5
6
7
8
9
10
Longitudinal Data Discussion Guide