Impact of Supplemental Instruction in Entry-Level Chemistry Courses at a Midsized Public University

Abstract

This paper examines the impact of supplemental instruction (SI)nonremedial workshops that support regularly scheduled courseson four different chemistry courses: General Chemistry I and II, and Organic Chemistry I and II. Differences in how SI impacts student performance in these courses are discussed, particularly in terms of whether students from underrepresented minority groups are affected differently from their peers. We found that SI appears to be most effective in courses at the beginning of the chemistry sequence and least effective in those in which students have already had to demonstrate effectiveness with the material in order to succeed in the course; its impact on performance in General Chemistry I appears to be quite high compared to a negligible impact in Organic Chemistry II. Impacts appear to be due to SI itself rather than the academic fitness of the students who opt to enroll in it. In the four courses examined, SI did not appear to have a different impact on students from underrepresented minority groups than it did on their peers.

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“…Additionally, several authors have attempted to assess the relative independent contribution of academic preparedness and/or prior academic achievement in predicting academic performance (multiple regression). Although Fjortoft et al () reported that SI attendance was not a significant predictor of academic performance, several authors have found SI attendance to be a positive predictor (Fayowski and MacMillan, ; Oja, ; Rath et al, ). Studies have also found that aptitude test scores, high school grades, and prior post‐secondary grades were positive predictors of academic performance (Fjortoft et al, ; Fayowski and MacMillan, ; Oja, ; Rath et al, ).…”

“…Although Fjortoft et al () reported that SI attendance was not a significant predictor of academic performance, several authors have found SI attendance to be a positive predictor (Fayowski and MacMillan, ; Oja, ; Rath et al, ). Studies have also found that aptitude test scores, high school grades, and prior post‐secondary grades were positive predictors of academic performance (Fjortoft et al, ; Fayowski and MacMillan, ; Oja, ; Rath et al, ). However, McCarthy et al () have suggested that since typical measures of academic preparedness (e.g., AGPA) may not be reliable predictors of academic success at university, alternative measures of a student's “academic ability in the university environment” (e.g., aggregate grade of all common courses completed by the students in the course) should be used in analyses of SI effectiveness.…”

“…Many studies have compared SI attendees and non‐attendees at baseline for measures of academic preparedness and/or prior academic achievement. Although some have reported significant differences either in favor of their SI attendees (Warren and Tonsetic, ; Malm et al, ) or non‐attendees (Congos and Schoeps, ; Hensen and Shelley, ; Peterfreund et al, ; Rath et al, ), many have reported no significant difference in such measures between their SI attendees and non‐attendees (Blanc et al, ; Congos and Schoeps, ; McCarthy et al, ; Ramirez, ; Van Lanen and Lockie, ; Congos, ; Hodges et al, ; Peterfreund et al, ; Terrion and Daoust, ). In this study, the mean AGPA of the non‐attendees was significantly lower than the students who infrequently attended the sessions and marginally lower than the students who frequently attended the sessions (Table ).…”

“…Many researchers have addressed this concern indirectly by comparing SI attendees and non‐attendees on potentially confounding variables. The literature on SI effectiveness also includes examples whereby the effects of confounding variables have been directly controlled for through the use of an analysis of covariance (ANCOVA) and/or regression analysis: e.g., the natural sciences (Kochenour et al, ; Warren and Tonsetic, ; Congos, ; Gattis, ; Hensen and Shelley, ; Oja, ; Rath et al, ); the social sciences and humanities (Kochenour et al, ; Warren and Tonsetic, ; and mathematics and engineering (McCarthy et al, ; Fayowski and MacMillan, ). Overall, this body of evidence generally suggests that SI attendance has a significant independent effect on academic performance.…”

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“…It is applied to make predictions of the dependent variable from one or more independent variables. For instance, Rath et al (13) used linear regression to explore how variables such as high school GPA and SAT scores contributed to university students' final grades in chemistry courses. In a study of examining gender differences in mental rotation tasks of chemistry representations, Stieff (14) used linear regression models to investigate the relationship between response time and angular disparity in two rotation tests.…”