Neil R. Colev
Chobot College Hoyward, California 94545
I
1
Prediction of Success in General Chemistry in a Community College
Since 1642, when the first entrance requirements were instituted for American higher education, a continuing debate has raged over what constitutes a sound curriculum for education. Those advocating implementation of a position that anyone who can profit from the co?lege process is welcome also express concern that an inst~tutionis ohligated to aid the student in his selection of courses. To perform such a task required that methods of measurement of individual potential for college work be made available to the student. The information derived in prediction studies can enhance the purpose of instruction by reducing the element of chance of possible failure in guiding students toward academic success. The Problem
were developed and used to create expectancy tables designed to assist the student in course selection. Two samples of similar size were randomly selected from the total group and for cross-validation purposes to determine whether prediction equations developed with one of the samples could successfully predict for the second sample and vice versa (3). Sample Groups
Data was collected over a 6-yr period, starting in the Autumn Quarter, 1966, from 336 students included in the study. The samples were selected from those students receiving a grade of C or better in the prerequisite course, Chemistry 31, and then enrolled in Chemistry 1A. This group included all those students who received a grade in Chemistry 1A and finally those who continued through the entire three-quarter sequence and completed the ACS standardized first-year general college chemistry examination. This particular method included those students who: had TCPE scores above 50 and may or may not have taken Chemistry 31 before attempting Chemistry 1A; had TCPE scores below 50 and may or may not have taken Chemistry 31 before attempting Chemistry 1A; had taken Chemistry 1A hut did not continue in the sequence; and had taken Chemistry lA, received a grade of C or better and completed the remaining two quarters of the yearlong course and received a score on the ACS standardized first-year general college chemistry examination.
All students majoring in the sciences must take and successfully complete the first-year general college chemistry course. This course is basic in the sciences and becomes a screening device for many science majors. Experience has shown that all students may not be prepared t o begin general college chemistry upon their entrance to college. Due to widely differing reasons, students may not have completed properly, or a t all, high school chemistry, or high school first- and second-year algebra (with knowledge of the slide rule and logarithms). This means that not all students are prepared for a mathematical treatment of chemistry in the first-year course. Thus, i t is required that all students a t Chabot pass the Toledo Cbemistry Placement Examination (TCPE) with an arbitrary raw score of 50 to be eligible for general college chemistry ( I ) . Those students who are not successful must then enroll in a prerequisite chemistry course. The problem is to determine as soon as possible which chemistry course to take. What is the relationship of previous grades in chemistry (if any), of high school algebra grades, of college entrance test scores, and of the chemistry placement examination scores in predicting success in general college chemistry?
Ten independent variahles were selected as possible predictors: Chemistry 31, Toledo Chemistry Placement Examination (TCPE), ACT scores (composite, mathematics, natural science, English, social science), high school chemistry and algebra courses. Two dependent variables were used to determine success: Chemistry 1A grades and the American Chemical Society General Chemistry Examination scores.
The Purpose
Findings
The purpose of the study was to find the best predictor or combination of predictors which could be used to predict a student's probability of success or failure in general college chemistry courses provided in a community junior college and to derive expectancy tables for values determined from multiple regression equations designed to aid counselors in guiding students toward a choice of appropriate academic goals.
For those who took Chemistry 31 in Group I (research sample), the only predictor variable found to have any significance with Chemistry lA, as the criterion of success, was Chemistry 31. When Chemistry 31 was entered as the best predictor, it obtained a multiple R of 0.43, R squared of 0.18, and a standard error of the estimate of 0.94. This showed that i t accounted only for about 18 per cent of the total variance. When the TCPE was entered as the second best, it only increased the total variance to 19 per cent, thus not even needing it in the regression equation. Then the first equation was found to be
The Procedure
The strategy of this descriptive research was to acertain the extent to which variables were related. Multiple correlation techniques were used in examining the degree of relationship hetween several variables in combination to predict a single variahle. I t was hoped that additional predictor variables would add something that was independent of the first predictor variable and could still he correlated with the criterion of success variahle. Stepwise regression was then applied to determine differential weightings of the predictor variables (2). Various prediction variahles were used against the dependent variable success in Chemistry 1A. Multiple regression equations
Variables
Y = 0.42
+ 0.63 (Chemistry 31 grade)
This equation was used later for predicting grades with Group I1 data. Table 1 shows the summary for the entire group. The variance, shown as R squared, accounts for only 22.7 per cent of the total. The relative contributions of each variable, as it is entered, is shown. The data for those who did not take Chemistry 31 in Group I shows the only predictor variable found to have any significance with the criterion of success was the Volume 50, Number 9 . September 1973 / 613
Table 3. Prediction of Chemistry 1A Grades Based Upon Data of Group I1 tor Those Not Taking Chemistry 31 and Scoring Above or Below the Mean on TCPEn
Table 1. Summary Table for All Predictor Variables with Dependent Variable Chemistry,1A for Group I Taking Chemistry 31
".*
Variable
MultipleR
RSquared
R Squared Changed
SimpleR
Zhemiatry 31 EPE HighSchool Algebra1 Hieh Schml Alsobran ACT-Natural science ACT-Composite ACT-English ACT-Social Science ACT-Math Hieh Schml Chemistry Number ofstudents = 108. a ~ e p r e s i o nmuation: Y = 0.42 n
D or
Number ofcases
0
C
lam
BarA
Totalnumbor ofstudents = 58.
Table 4. Prediction of Chemistry 1A Grades Based Upon Data of Group I I for Those Taking Chemistry 31 and Scoring Above or Below the Mean on TCPE"
+ 0 . 6 3 ( ~ b m i 8 t m 3 grade) 1
Table 2. Summary Table lor All Predictor Variables with Dependent Variable Chemistry 1A for Group I Not Taking Chemistry 31"
'
-
Chemistcy LA Grades -.
D or
Numhr of Cares Above Mean 0150.82 ( N = 371 &law Mean 0150.82 ( N = a31
lass
C
BarA
0%
99%
0%
99.5%
61%
3.4%
~ o t anumber l of students = 120.
Table 5. Group II Data in Chemistry 1A for Those Taking Chemistry 31 a Chemistry LA Grades TCPE
score3
TCPE. When the TCPE was entered as the best predictor, i t obtained a multiple R of 0.39, R squared of 0.15, and a standard error of the estimate of 1.17. This showed that i t accounted for only about 15 per cent of the total variance. When the high school algebra I scores were entered as the second best variahle, it accounted for 19 per cent of the total variance. This restricted the second equation to one variahle also Y = -1.47
+ 0.06 (TCPEvalues)
This equation was then used later to predict with Group II data. Tahle 2 shows the summary for the entire group. The two predictors, Chemistry 31 and the TCPE, were not found to increase the significance by combining them. All other variables were not found to aid in the prediction of success. The entire program was rerun a second time, hut ACS scores were substituted forchemistry 1A as the criterion of success. By making this substitution, i t was found that comparisons were in order in relating grades in Chemistry 1A with success achieved at the end of the year-long course. The correlation between the two criteria of success was found to he between 0.7245 (56 per cent of the variance) and 0.8172 (58 per cent of the variance) for the various groups. Expectancy Tables
After preparation of the multiple regression equations for both groups, the statistical results were used to derive expectancy tables (4-6). The TCPE arbitrary cut-off score of 50 was used as the dividing line for predicting success in Chemistry 1A for Group 11 who also took Chemistry 31 first. Then it was repeated for Group I1 for those who did not take Chemistry 31 first. Tables 3 and 4 show that the chances of receiving a grade of A or B in Chemistry 1A are 67 per cent for those who scored ahove the mean on the TCPE. The chances d r o ~to 32 per cent for those individuals who did not take c h e m i s t 6 31 first. The chances of eettine a made of A or B for the person in either situation who scored below the mean are almost nonexistent, hut the chances of getting a grade of C are very high. It also shows that the chances of receiving a D or less are nonexistent for both groups.
- - -
614 /Journal of Chemical Education
Leis than 50 Greater than 5"
Numberofstudents= 109. 0 Figure8 in parenthesea represent rumulative percentages.
Table 6. Group I I Data in Chemistry 1A for Those Not Taking Chemistry 31"
-
Chemistry l A Gradas
TCPE Score8 lassthan SU
Greeferfbsn 50
D 12% ~lOO%ib 12% (109%)
C
B
A
63%
25% (25%) 23%
0% 10%) 21% (21%)
(:E'
(38%)
(44%)
N u m b r ofstudents = 51. 'Figures in psrenfbese. reprelent evmvlafiv~pereentsges.
Additional nominal data found was the tallying of actual grades of Group I1 in Chemistry 1A. In Tahle 5, for example, if an individual scored less than 50 on the TCPE, but took Chemistry 31, he had a 2 per cent chance of receiving a grade of A, a 34 per cent chance for a grade of B, and an 85 per cent chance for a grade of C in Chemistry 1A. Comparing the ahove data with the data of the student who took Chemistry 31 and scored higher than 50 on the TCPE, it is found that the chance of receiving a grade of A went up to 32 per cent; receiving a grade of B went up t o 73 per cent, and the chance of receiving a C went up to 97 per cent. Tahle 6 illustrates the possibilities of receiving a specific grade in Chemistry 1A for those who scored less than or higher than 50 on the TCPE, hut did not take Chemistry 31. The data shows that the student who scored less than 50 on the TCPE had no chance of receiving a grade of A, only a 25 per cent chance of receiving a grade of B, and an 88 per cent chance of receiving a grade of C in Chemistry 1A. The student who scored higher than 50 on the TCPE (without taking Chemistry 31) has the chance of receiving a grade of A increased to 21 per cent, the chance of receiving a grade of B is raised to 44 per cent, hut the chance of receiving a grade of C is comparable a t 88 per cent with the individual who took Chemistry 31.
Discussion
The findings from this study suggest that Chemistry 31 appears to be the best predictor of success in Chemistry. It shows that a student who takes Chemistry 31 has a 67 per cent chance of receiving a grade of A or B, while the student who does not take Chemistry 31 finds his chances decreasing t o 32 per cent. If initially he scored below the cut-off on the TCPE, his chances of achieving a grade of A or B are zero and 3.4 per cent for those who took Chemistry 31 and did not take Chemistry 31, respectively. The study supported the literature by not determining specific TCPE cut-off values (73). Those students scoring above 50 on the TCPE have a much better chance of receiving grades of C or better than do those individuals scoring below 50. In attempting to explain the lack of significance when using the other predictor variables, the study was in agreement with the literature in that course areas and GPA are better predictors than specific course grades. The use of ACT scores also correlates with freshman GPA's
rather than with a specific course grade (9). Each institution must develop its own unique prediction equations and methods (10). Based upon the total variance determined by each predictor variable, there is something else that contributes to success in chemistry. I t may or may not be academic in nature, however. it is very significant! Literature Cited (1) Houey.N. W.,andKmhn,A., J. CIIEM.EDUC.,40.370(1963). (2) Dixon, W. J., (Editor), "BMD Biomedical Computer Pmgrams," University d CalilomisPress, %rhcley, Ism, p 233. (3) Dixon, W i h d J.. and M-y, Renk J.. "lntmdudion to Sfatistied Analysis," 3rd ed., McGraw-Hill Bmk Co., New York, 1969, p. 40.446. (4) Bittner, R. H.. and Wilder. C. E., J. E z p Edue., 14.245 11916). (5) Blai. B.. Jr. Coll. J., 56, 27(1966). (6) Sehrader, W.B.. J Edue. Meas., 2,29(1965). (7) Hein, M., and Reitmyder. H.. "Grades in Chemistry lA Related ta Toledo Chemistry Plseemenf Examination Scores." Reportd to NDEA Chemistry Worhhap a t Orange Coast College, 1962. (6) Houey, N. W., end Kmhn A., J. CHEM. WUC., 35.48 (1956). (9) Lindquist, E. F., "lnte rating the 1961 ACT Research Reports," Science Research Aaaaiatea. Chicago. 'Pg61. (10) Munday, L.,Edu. Psy. Me=.,27,401(1967).
Volume 50, Number 9 , September 1973 / 615
