Predictors of Grades in General Chemistry for Allied Health Students C. L. Craney Occidental College, Los Angeles, CA 90041 R. W. Armstrong Russell Sage College. Troy, NY 12180
Accurate prediction of student performance prior to a general chemistry course is important for advisement as well as a continuine interest of chemistrv instructors. Previous work (1-3) in the area has focused upon performance in a traditional eeneral chemistrv course for science and engineering stuients. The courses in the previous studies have used the text by Mahan ( 4 ) . These studies have used math SAT scores, high school chemistry grades, and pretest scores to predict the performance of students in general chemistry. The American Chemical Society's Toledo Exam (Form 1974) has also been used to predict success in traditional general chemistry progrr~ms(5.We sought an effective predktor of student performance in the first term of a full-year general chemistry sequence for allied health students at Russell Sage College. The eeneral chemistrv course for allied health students is a two-semester course taught in a traditional lecture-discussion format. The course involves three l-Br lectures and one 2-hr laboratory per week. The texts, course content, and mathematical emphasis are substantially different from those in a traditional general chemistry sequence. These differences mainly consist of the replacement of inorganic topics by less quantitative topics in organic and biochemistry. Nearly all students enrolled in the Russell Sage course are following a structured sequential curriculum in which general chemistry is a prerequisite for courses in other areas. Poor performance in chemistry usually eliminates the student from herhis allied health program and hence, effective advisement of these students is essential. We have administered the Toledo Exam to the students enrolling in this course for several years. The results (see below) suggested that the test alone is not very useful for predicting performance in the course. Furthermore, we found no evidence in the literature that the prediction of student oerformance in courses of this tvpe .. had previously been published. This paper describes the relationship between student perl'orm&e in general chemistry and t h e ~ o l e d oExam, the math SAT scores, and the high school chemistry grade. A multivariant linear regressionanalysis was used toidentify a group of students at high risk of doing poorly in the allied health chemistry course a t Russell Sage College. A special program was established in 1982 aimed a t improving the performance of this group of students.
-
Results Complete data were available for 304 of the students enrolled in the general chemistry course during the fall terms of 1979,1980, and 1981. Table 1shows the average results and linear correlations of the three predictors with the students' fall term grades in general chemistry. For this analysis the students who withdrew from the course late in the term were considered failures. In general, neither the math SAT (R = 0.45) nor the high schwl grade (R = 0.39) is an effective single of thr students' performance in the beginning term of general chemistry for allied health students. The Toledo
Exam is better correlated with fall term grades in the course, but a significant number of students with substantially below average Toledo Exam scores had course grades well above average. This can he seen in Figure 1where the deviation of the mean divided by the standard deviation (Z average) is plotted against fall grades.
. . . .. . . . . . . . . . . . . . .. .. .. .. .. .. . . . ................. .. .. .. ....... .. .. .. .. .. .... .................... . . . .. .. .. ......... . . . ............ ........ . . . ...............
4. 5
9. 3
-
2. 5
-
2.5-
0. 5
-
-
-
J
-0.5
Q
3
-
--I. B
--0. 6
0. 6
1.6
3.a
Z AYF.R8,GE SCDRES Obi ACS IDLKOD EYPM
Figure 1. Predictor of performance in general chemisby lor allied heaiih students.
Table 1. Data for 304 Students In General Chemistry for Allled Health Professions
+
Complete Data Standard
Variable
Mean
Toledo Exam scare parts
24.7
(1-3)" Mam SAT
Deviation
501
Scwe Grade High School Chemistry Gradebin General ~~
Regression Analysis 01 Fall Grade In General Chemistry = m(Vanabf.4 b Pearson's Correlation m b Coefficiem
2.69
2.07
~,
for Allied
Healthr Students
Volume 62 Number 2 February 1985
127
The nositive correlation between the three ~redictorsand the gra& in general chemistry led us to perfoka multivariant analysis of these data. The analysis was performed using the program "SHAZAM" written by Kenneth I. White (Department of Economics, University of British Columbia, Vancouver, BC, Canada V6T 1Y2) and adapted to the Occidental College computer by Paul Hubhard. The results of the analysis are shown in Table 2. The correlation coefficient for the standardized remession eauation was 0.61 (R2 = 0.376) indicating that Wi'of the varktion in the student performance in a e n ~ r a chemistry l is due to the predictors in Table 1. All three predictors in Table 1are positive indicators of performance in general chemistry, however, the standardized error of this prediction was 0.9 (nearly one grade level). This variation is shown in Figure 2 where the equation for the normalized multivariant fit (less the intercept value) is plotted versus the fall grades. On the basis of Firmre 2. a eroun of students was identified who had a high risk i f recdivLg alow grade in general chemistrv (C- or below). These students were counseled to participate in additional instructional activities in a weekly small eroun. settine. Initial evidence suggests a modest ~ositive impact of th& special program. 07-the eleven highest risk students in the Fall 1982 class, nine received a grade of C+ or ~~~
L
8. 5
2 . 2
-1. 3
0. 4
-0.4
1. 3
M U L T I V A R I A N T PREDICTOR VALUE
Figure 2. Prediction of performance in general chemistry f a allied health students. m i s figure is Weresult of G?e muiiivariantanalysisusiqWe v a l w ~ oTabb f 2.
Table 2.
Multivarlant Analysis
of Predictors from Table 1 * ......
UnstandardiredRegression Coefficient Standard E r m of of Variable Equation Estimate Toledo Exam Score
6.9 X 1 0 P
1.0 X
3.1 X 3.3 X
8.0 X 6.0 X
Regesslona Coefficient Standard Of Error of Equation Estimate
0.43
0.06
0.23 0.30
0.06 0.06
2.1 0.92
0.05
(Paris (1-3) Math SAT Scwe High School
lo-'
lo-'
Chemise Gra6es Intercept standardized Error Of Estimate Cwrelation Cwfficienl a
0
-2.1 0.92
0.4
0.61
0.81
Grade in general chemislty for allied h n h students is Uw depmdsnt variable. nm vvarbms were w m k w d to a a l e of relrtive sta4ard deviation horn me
mean. See Table 1 far me &talk of me numerical scale used for he analpis. 6Caveat lecta: me nomndardlzed regrs~immeniciema apply only to daoae at RvSJell Sage Collsge.
128
Journal of Chemical Education
hieher in the first semester. Onlv one failure resulted from this group. In general, grade outcomes in relation to attendance Datterns suggest that mere notification of hieh risk status mav be as significant in spurring quality performLce as is faithf2 attendance a t the extra sessions.
Discussion
The results of this study are generally consistent with previous reports. Prior studies have indicated a positive correlation between math SAT scores and performance in traditional general chemistry courses (R = 0.51 (3). The correlation is not significantly different for students pursuing an allied health-based general chemistry program (R = 0.45). The average score on the Toledo Exam (49%)appears to be about the same as renorted for science. ~harmacv.and eneineering students a t ihe University of Toledo (5):;rhe correlation coefficient for the Toledo Exam scores versus erades in general chemistry at the Cnirrrsity of Toledo was reported to he 0.54 ( 6 , in 1963. The more recent studv. .(5) . did nut renort this correl'ation coefficient. The correlation between high school chemistry grades and performance in general chemistry was the poorest of the three predictors. The correlation coefficient ( R = 0.39) is consistent with earlier results (R = 0.3766) from the University of California at Berkeley (3). These correlations should not be discounted since "educational psychologists state that the maximum correlation between placement test scores and college grades is probably 0.7, even with a perfect test battery" (6). The ~redictorsof student ~erformancein eeneral chemistw for allied health students using a multivariant analysis of thk Toledo Exam score, math SAT score, and high school grade in chemistry is as successful (R = 0.59) as the multivariant analysis of Ozsogomoyan and Loftus (3) who studied the student performance in a traditional general chemistry course at the University of California at Berkeley. Their conclusion is that the math SAT score alone is not a powerful predictor of student performance but is strengthened when combined with other predictors. I t also appears to bevalid for an allied health-based general chemistry course. As previously noted (3) a grade of B in high school chemistry makes only a small positive contribution to the value of the predictor, yet a grade of C makes a significant negative contribution. Data for students whose high school grades in chemistry were unavailable were not included in this analysis. In contrast to the assumptions of other studies (3) students who withdrew from the course were considered failures. This assumption is related to the required prerequisite character of the general chemistry course in the program for allied health students. The consideration of only Parts 1,II, and 111 of the'l'oledo Exam was based on our observation (dam not shown) of a lark of currelatiun of the scores on Parts IV, V, and Vl with performance in general chemistry. This observation amears consistent with the relatively low scores observed ;i the science enheering chemistw course at the University .general . of oled do-(5). As Figure 2 shows, the data are most effective in identifying a group of students projected to obtain below average grades in general chemistry, without special assistance. Prediction of performance at significant above average level is clearly not possible. As Pickering noted for the traditional program several vears aso "this is because zettins an A reonires more than raw aptitide" ( I ) . The com~letedata set of 304 students was not subdivided into groups based on math SAT scores (1,2) or high school
-
chemistry grades (3) due to the small size of the resultant subgroups. Nevertheless, the results shown in Figure 2 were sufficient to establish the need for a program to assist high risk students and thus preclude the future collection of equivalent data. \V'r have used the annlysis toadvise students to participate in an additional nroblem-solvindtutorial ~ession.The d o t program set up in the spring of c982 gave mixed but eniouraging results. This program was expanded in 1982-83. Due to the relatively modest number of high risk students involved, it will take several years to collect meaningful dataon the ef. fectiveness (7) of the extra assistance program.
Acknowledgment The authors are indebted to Thomas Slohko and Paul ~ ~ h ofhthe~computing ~ d center, occidental college, for their assistance in adapting the "SHAZAM program to this "+..rl.. 0,""'.
Literature Clled (1)Pickeriw. M..J. CHEM. EDUC., 52,512 (1915). (2) Andrew M.H.,and Andrew,L. J. CHEM. EDUC., 56,231 (1979). Ozsagomonyan,A.,and D., J. 56, (1979). (4) Mshsn,B.H.."Coliegc Chemistry," ~ ~ ~MA.d1966. i ~ (5) NiedzielWR. L a n d Walmsiey,F.,J.CweM.E~~~.,59,149 (1932). (6) H o v w N. W., snd Kmhn,A., J. CHEM. EDUC.,49,370 (1963). (11 Pickering, M., J.CHEM.~ou~.,54,433(19~).
Volume 62 Number 2
February 1965
~
,
129
