Factors Influencing Student Usage of
Supplemental Instruction and Grade
Achievement
Eric Rabitoy
Ed.D. Candidate
California State University, Fullerton


Supplemental Instruction (SI)

Initiated by Deanna Martin at the
University of Missouri, Kansas City
(Martin,
1980)

Provides support for students enrolled in high-risk courses

Intent of SI


SI Pedagogy

Relies on regular out-of-class group interactions focused on integrating reasoning and study skills
(Arendale, 2004; Van
Lanen & Lockie, 1997)


SI Pedagogy



Open to all enrolled students
Students work with the SI leader in small groups to discuss course content and learn to integrate effective skills
(Arendale, 1994; Congos,
2002)
Participating students take an active role


Studies suggest that students participating in SI benefit in a number of ways over non-participants:


 final course grades (Commander, Stratton, Callahan & Smith, 1996;
Fayowski & McMillan, 2008; Moore & LeDee, 2006) cumulative GPA (Fayowski & McMillan, 2008) graduation rates (Arendale, 1998; Bowles, McCoy & Bates, 2008)



Student populations are diverse

Ethnicity, academic preparation, gender
SI environment is diverse

# SI sessions attended, gender/ethnicity of SI leader, gender/ethnicity of course instructor

Each of these variables may have an impact on final course grade and cumulative GPA


This study evaluated the effect of these multiple independent variables on one another, as well as on final course grade and cumulative GPA, for community college students enrolled in math and science courses


Input – Environment – Outcome College
Impact Model
(Astin, 1993)

Input – characteristics students possess upon entrance to college


Environment – programs, people, and cultures that students experience as a result of their participation in college
Outcome – skills, knowledge, values, and beliefs that students obtain as a result of their college experience.

Input
Student of Color
Student Gender
Prior GPA
English P. S.
Math P. S.
Environment
SI Leader Student of Color
Gender SI Leader
Gender Course Instructor
Course Instructor Faculty of Color
Outcome
# SI Sessions Attended
Course GPA
Cumulative GPA


Data originated with student and faculty participation in an SI program in STEMrelated disciplines at a single community college campus district in Southern California

Spring 2009, fall 2009, winter 2010, and spring
2010 semesters (N = 3,443)


Data analysis relied upon a multivariate path analytic approach (AMOS)
 account for the simultaneous influence of multiple variables acting together within a model
(Ewert & Sibthorp, 2000)
 determine the influence of individual variables on overall effect
(Graham, 2007)


Structural Equation Modeling (SEM) enables researchers to develop, estimate, and evaluate complex multivariate models and study both direct and indirect effects associated with variables

Causal relationships between variables are depicted with arrows; indicating the influence of one variable on another
(Ewert & Sibthorp, 2000)

The resulting diagram consists of a series of paths that indicate the effect of one variable on another within a model
(Raykov & Marcoulides, 2006)

Large Effect Size*
Medium Effect Size*
Small Effect Size*
* (Cohen, 1988)
X 2 = 1,715.74, df = 31, N = 3,443 p < .001

Females
Males
X 2 = 983.759, df = 25, N = 1,956, p < .001
X 2 = 634.437, df = 28, N = 1,424, p < .001

SOC
White students
X 2 = 740.848, df = 26, N = 1,659, p < .001
X 2 = 385.860, df = 8, N = 768, p < .001

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