Engineering and Applied Sciences (CEAS) students were ..... course. Very good chance. 44.8%. 32.4%. Some chance. 38.6%. 35.2% ..... with the computer.
Retention: Are Students Good Predictors? Mary R. Anderson-Rowland College of Engineering and Applied Sciences Arizona State University Tempe, Arizona 85287-5506 Abstract - The retention rates of engineering students, in general, are much lower than they should be. Of particular concern is the fact that women and underrepresented minorities are not only recruited in small numbers, but their retention rates are also low. Research has shown that there are many actions that can be done to help retain students. In order to better understand our students and to design intervention programs that would improve their retention, we surveyed students enrolled in the ECE 100 class (Introduction to Engineering Design) at the end of the Fall 95 semester. The survey requested demographic data, reasons why engineering was chosen, recruitment participation and evaluation, and predictions about the student’s academic future and success. College of Engineering and Applied Sciences (CEAS) students were asked to give their best guess about their chances of graduating from the CEAS and of failing one or more classes. Approximately 70% of the students volunteered their student ID number enabling the survey data to be analyzed with corresponding academic records. The analysis includes contrasts of women and men, minority students and non-minority students, and CEAS students who have been retained for at least one year versus those who have left. The results of the survey showed that students were quite good at predicting that they would likely be leaving the CEAS and whether they would fail at least one course. Men were more confident of graduating from CEAS than women. An analysis of grades of the students who had left the CEAS after one semester or one year showed that most of those students had difficulty with their math class their first semester, with most getting a D, E, or a W. This study reinforces the need for more student intervention. Particular student intervention programs are suggested. Additional study is needed to understand if the retention of CEAS freshmen is actually enhanced by the taking of the Introduction to Engineering course during their first semester, rather than their second.
Introduction It is well known that women and the minority groups of African Americans, Hispanics, and Native Americans,
are severely underrepresented in engineering schools and in the engineering workplace. This is a severe loss of potential to the field of engineering and, in particular, to the diversity that can enhance the problem solving done by engineers. For a variety of practical and moral reasons, steps must be taken to attract and to retain more women in engineering curricula. [1] This statement holds equally well for underrepresented minority students. In addition, academia is now under pressure to become efficient and cost effective. Short-term thinking concentrates on getting the students in the front door. Longer-term thinking includes the concept of recruiting for graduates. By concentrating on the factors that make for success on a campus, this more focused approach of recruiting, that includes retention efforts, can result in long-term benefits [2]. Investing in student retention may be the most cost-effective outlay an institution can make [2]. Lost students mean lost revenue. The minimum potential losses can easily be estimated and are often staggering. For example, if the university loses 10% of its freshman class after the first semester and an additional 20% after the second semester, for every 100 students at least seven semesters of tuition are lost for 10 students and at least six semesters of tuition are lost for 20 students. Let us assume that resident fees are $1,000 per semester and non-resident fees are $3,000 per semester. If 30% of the students were non-residents, then the tuition lost would be over $360,000 (per 100 beginning freshmen). This loss does not include any other related revenue associated with student enrollment. We have a compound problem with graduating engineering majors. In the fall of 1995, the interest of freshmen students in engineering careers reached its lowest point since 1975. Only 6.4 percent of these students (11.7 percent of men and 1.9 percent of women) planned to become engineers. In 1982, 12.0 percent of the freshmen students planned to become engineers [3]. In addition to the poor initial interest, the engineering curriculum is very demanding and students may leave due to poor academic performance or conclude that the heavy demand of the curriculum is not worth a continued effort. For a more complete discussion on the retention of engineering students, see [4]. The retention rates of engineering students, in general, are much lower than they should be. For example, at Arizona State University (ASU) in the
College of Engineering and Applied Sciences (CEAS), we retain approximately 90% of our full-time, first-time freshmen for their second semester, but only 60% of these students return to our college for the beginning for their second year. An additional 10% of these students do return to ASU for their second year, but have transferred out of our college. A full-time, first-time freshman (FFF) is a students who in their first semester at ASU carries at least 12 semester credit hours and has transferred in less than 12 credit hours. This categorization is done on the twenty-first day of the semester [5]. Since we receive many transfer students (our junior class is larger than our sophomore class), retention and graduation rates must be qualified by identifying the cohort group being considered, namely FFF. The CEAS retention rates are not inconsistent with those of other similar engineering schools. In a study “Why Undergraduates Withdraw from ASU during a Semester,” the three primary reasons were employment demands, financial problems, and family problems [6]. Approximately two-thirds of ASU undergraduates in the study were employed at the time they withdrew. In that same survey, 24% of the students said that employment demands played a very important role in their withdrawal from ASU [6]. A study designed to determine the relative importance of factors contributing to career choice and persistence in undergraduate education, surveyed students on seven college campuses. Seymour and Hewitt [7] included students in their study both that had switched out of Science, Mathematics, and Engineering (SME) and students who had not switched. The top five factors ranked by importance among students who switched majors were: (1) Reasons for choice of SME major prove inappropriate; (2) Poor teaching by SME faculty; (3) Inadequate advising or help with academic problems; (4) Non-SME major offers better education/more interest; and (5) Lack of/loss of interest in SME: “turned off science”. In addition, minority students placed more of the blame for switching on themselves, while white students more often indicated institutional factors as reasons for switching majors [7]. The “poor teaching by SME faculty” and instructional methods are areas that are being addressed by many researchers such as Johnson, Johnson, and Smith [8] and Felder [9]. Of special interest to this paper is that three of the five reasons listed above have to do with an “understanding of" or an “attitude about" engineering. The National Action Council for Minorities in Engineering, Inc. (NACME) conducted a study on the retention of minority and non-minority students. In their study selectivity was found to be the most important predictor of degree attainment for both minority and nonminority students. Selectivity ratings are self
assessments made by each college based on three criteria: percentage of applicants accepted, high school class rank, and standardized test scores of freshmen who actually enrolled in the institution. However, the NACME researchers went further than demographics and interviewed the administrators at the most successful institutions to suggest other factors that impact retention. Six key actions were identified including a strong institutional commitment as measured by attitudes of faculty and staff, integral minority engineering programs, and allocation of resources; and a focus on removing barriers to student success. Other actions include special attention paid to the early success of freshmen and the delivery of special programs designed to help make the institution more supportive [10]. Noel and Levitz assert that the most powerful retention strategies are based on using existing resources, not using large infusions of new resources. Four strategies that they suggest are: (1) Strong emphasis on freshman success/orientation/individualized plans; (2) Campus wide ownership and management of retention; (3) Transferring admissions relationships to teaching/advising relationships; and (4) Emphasis on student-centered service excellence [2]. Blaisdell asserts that the theory of self-efficacy, one’s belief about how well she or he can perform a given task or behavior, should be used to design recruitment and retention programs for women in engineering [11]. One builds self-efficacy through four sources of information: past performance accomplishments, vicarious learning (seeing others model the behavior), encouragement and support, and physiological arousal (such as lowered anxiety) [12]. Felder’s research on engineering student performance and retention supports the importance of self-efficacy for women engineering students. Even though the backgrounds and preengineering academic credentials of the women in his study marked them as more likely to succeed than men, the women entered the engineering curriculum with greater anxiety and lower confidence in their preparation than did the men. They began the first course in chemical engineering with higher expectations of themselves, but by midpoint of this course, their expectations were lower than those of the men. As they proceeded through the curriculum, the men consistently expressed higher self-assessments of their abilities to solve basic engineering problems, problems that required creativity, and computer problems [1].
The Survey Clearly, if we are to help retain more of our students through effective programs, we need to understand more
about our students. ASU is a commuter school with 42,463 students on the Main campus during Fall 96. About 80% of the students commute. Nearly 5,200 of the ASU students are in the CEAS. The CEAS includes Chemical, Bio, and Materials Engineering; Civil and Environmental Engineering; Computer Science and Engineering, Electrical Engineering; Industrial and Management Systems Engineering; Mechanical and Aerospace Engineering; and Construction. In Fall 95, the CEAS, as described above, had 3,326 undergraduate students and 1,730 graduate students [5]. The beginning engineering and construction students in the CEAS were surveyed in order to better understand them and to design interventions that would improve their retention. The survey was given to the students enrolled in the ECE 100 (Introduction to Engineering Design) at the end of the Fall 95 semester and near the beginning of the Spring 1996 semester. During the Fall 95 semester, CEAS had 459 first-time freshmen and 114 new freshmen or sophomore transfers. Most of the new students took ECE 100 in either Fall 95 or Spring 96. This paper’s discussion will focus on the new students surveyed in Fall 95. Of the 251 student responses, 220 were students in the CEAS and 89 were transfers. Of the CEAS survey students, 22.0% were women and 14.5% were underrepresented minorities, representing roughly the proportion of women and underrepresented minorities in the CEAS, namely 19.2% and 13.2%, respectively. The 32 underrepresented minority students included 5 African Americans, 23 Hispanics and 4 Native Americans. The survey requested demographic data, reasons why engineering was chosen, recruitment participation and evaluation, and predictions about the student’s academic future and success. For more information on the demographics, the role model factor, when engineering was chosen, why ASU was chosen, recruitment participation and effectiveness, and employment and retention, see [13]. Of special note is that 55% of the engineering students we surveyed were employed. The students were asked to give their best guess about their chances of: (1) Graduating from CEAS; (2) Graduating from ASU in another college; (3) Changing their major within CEAS; (4) Failing one or more classes; (5) Obtaining tutoring help in specific courses; (6) Needing more than four years to complete their college degree; and (7) Transferring to another college or university before graduation. For each situation the student was asked to indicate their best guess of each of these things happening to them during their time at ASU: A-very good chance; B-some chance; C-very little chance; and D-no chance. A discussion and analysis of the responses to these seven areas follows.
Survey Results Of the 220 CEAS students completing the survey, 146 reported valid ids enabling their survey data to be analyzed with their academic records. The sample size of particular groups varies since not all of the students answered each question in the survey. Since the report of an id was voluntary, it is of interest to know if the 146 id students were typical or atypical of those that did not report an id or gave an invalid id. In particular, we wanted to know if there was self-selection by the groups to certain responses. Since there is no statistical difference at the .05 level between the responses of these groups, we can conclude that the results for the 146 should be generally true for the whole survey population. In fact, only two of the seven categories showed a p-value of less than .28. (See Table 1.) Here, and unless noted otherwise, the Chi-Square test for homogeneity was used with these populations, with cells usually pooled if an expected value was less than two. A slightly larger percentage of the students with good ids reported that there was a very good chance or some chance that they would change their major field with the CEAS. The largest difference between the two groups was shown on the fifth item: obtaining tutoring help in specific courses. Of the 146 CEAS students with ids, 113 of them were still enrolled in the CEAS during the Fall 96 semester. Of the 33, who had left, only two were still at ASU in another college. Ten of these students left after their first semester. Twenty-six (23.6%) males in this group were not retained after a year, as were seven females (20.0%) and four minorities (18.2%). It is interesting to note that only 23% of the students with ids were not retained after one year, as compared with approximately 40% of all full-time, first-time freshmen, as reported on average by university data. Of the 65 fulltime, first-time freshmen identified among our 146 id CEAS students, 17 (26%) were not retained after one year. We should note that this survey was taken near the end of the semester and thus represents a slightly different count than that obtained on day twenty-one of the semester, that the university uses to calculate retention rates. Of the seven prediction areas used in the survey, two can be partially analyzed based on the students’ records through Fall 96. These two are the prediction of graduation from CEAS and the failure of one or more classes.
ID (n= 145) 1.
2.
3.
4.
5.
6.
7.
No ID (n = 71)
Graduation from CEAS 74.5% 74.6% Very good chance 19.3% 16.9% Some chance 4.1% 4.2% Very little chance 2.1% 4.2% No chance Graduate from ASU, no CEAS 7.6% 7.0% Very good chance 17.9% 14.1% Some chance 44.1% 39.4% Very little chance 29.0% 39.4% No chance Change major within CEAS 15.2% 18.3% Very good chance 36.6% 22.5% Some chance 33.1% 38.0% Very little chance 14.5% 21.1% No chance Fail one or more classes 14.5% 15.5% Very good chance 20.7% 19.7% Some chance 38.6% 28.2% Very little chance 24.8% 35.2% No chance Tutoring help for specific course 44.8% 32.4% Very good chance 38.6% 35.2% Some chance 12.4% 22.5% Very little chance 3.4% 8.5% No chance Need more than four years to graduate 68.3% 59.2% Very good chance 17.2% 26.8% Some chance 8.3% 5.6% Very little chance 5.5% 8.5% No chance Transfer to another college or university 7.6% 11.3% Very good chance 21.4% 16.9% Some chance 46.9% 43.7% Very little chance 23.4% 28.2% No chance Table 1. Predictions by Id and No Id Students * - "very little chance" and "no chance" pooled
All Student Graduation Predictions
p
The students were asked to predict if they would graduate from the CEAS. Obviously, we will not know for six or seven years how many of the students surveyed actually will graduate from the CEAS. However, at this time we can compare the predictions of the students with ids, who are still enrolled after one year with those who have left the college before the beginning of their second year. We can also look at the confidence of the students in their eventual graduation in engineering by gender and minority status. We should first note that the percentage of female CEAS students who gave an id (24.6%) is not significantly different (p=.22) from the percentage of female CEAS students who did not give an id (17.6%). Similarly, the percentage of underrepresented minority CEAS students who gave a good id (15.1%) is not significantly different (p=.75) from the percentage of underrepresented minority CEAS students who did not give an id (13.5%). So again, we should be able to use the predictions of the women and minority groups with an id as representative of the survey students in their group. Men were more confident (“very good chance”) than women of graduating from the CEAS. (See Table 2.) However, if we consider those students who thought there was a “very good chance” or “some chance,” then the percentages are almost the same for men and women. Six of the males and none of the females thought there was “no chance.” The minority students were more confident than non-minority students that there was a “very good chance” of their graduation, but there was no statistical difference between the two groups.
0.78*
0.52
0.19
0.34
0.06
0.28
0.63
Good id Student Graduation Predictions From this point on, the discussion will focus on the 146 CEAS students who gave a valid id in the survey. The
Graduation from CEAS Very good chance Some chance Very little chance
Women (n=48) 64.6% 29.2% 6.3% 0.0%
Men (n=168) 77.4% 15.5% 3.6% 3.6%
p
0.10*
Minorities (n=32) 78.1% 15.6% 3.1% 3.1%
Non-Minorities (n=184) 73.9% 19.0% 4.3% 2.7%
No chance Table 2. Prediction of Graduation from CEAS by Women vs. Men and Minorities vs. Non-Minorities * - "very little chance" and "no chance" pooled
p
0.88*
groups. The minority students, who were no longer in the CEAS after one year, were somewhat more accurate predictors of their future in the CEAS than the nonminorities, but overall there was no significant difference in their predictions.
current academic record was used to determine enrollment in the CEAS after one year, failure of one or more courses, grades earned in ECE 100 and math classes, the GPA and academic status. This additional academic information was used with their predictions (n=145) in the survey. The predictions of graduating from the CEAS were very highly significantly different for those who were still in CEAS in Fall 96 and those who had left by that time. (See Table 3.) The predictions of the women students who were still in the CEAS after one year were very highly significantly different from the women who had left. In fact all of the women who were still in the CEAS predicted that there was either a “very good chance” or “some chance” that they would graduate from the CEAS. The minority students were highly significantly different in their predictions of graduating from the CEAS depending on whether or not they were still in the CEAS after one year. There was also a significant statistical difference in predictions between the men still in CEAS and the men who had left. Unlike the women still in CEAS, 4.8% of the men still in CEAS had predicted “very little chance” or “no chance” that they would graduate from the CEAS. The women, who were no longer in the CEAS after one year, were better predictors than the men, who were no longer in the CEAS. None of these women said that there was a “very good chance” of them graduating from the CEAS, while 61.5% of the men said that there was a “very good chance.” However, the difference in predictions between the two groups was not significant and the sample sizes were small. The minority students, who were still in the CEAS after one year, were more confident of their chances of graduating from the CEAS than were the nonminority students. However, there was no significant difference in the predictions overall between these two Graduation from CEAS: Id Students
p
Women (n=28)
Men (n=84)
92.9% 7.1% 0.0% 0.0%
25.0% 75.0% 0.0% 0.0%
p
Still in CEAS NonMinorit Minorit y (n=18) y (n=94) 94.4% 79.8% 5.6% 16.0% 0.0% 3.2% 0.0% 1.1%
p
Still CEAS (n=18) 94.4% 5.6% 0.0% 0.0%
p
Minorit y (n=4) 25.0% 75.0% 0.0% 0.0%
Minority Left CEAS (n=4) 25.0 75.0% 0.0% 0.0% Left CEAS NonMinority (n=29) 51.7% 31.0% 10.3% 6.9%
p
p
0.60b
61.5% 26.9% 3.8% 7.7%
Still CEAS
Men Left CEAS (n=26) 61.5% 26.9% 3.8% 7.7%
0.01b
0.0% 71.4% 28.6% 0.0%
p
Still CEAS (n=84) 84.5% 10.7% 3.6% 1.2%
0.25c
Men (n=26)
Over 70% of the students still in the CEAS after one year with no E’s predicted that there was “very little or no chance” for the failure of at least one class. (See Table 5.) Of the students receiving at least one E during their first year, 74.3% predicted that there was a “very good or some chance” that they would fail at least one course. These prediction differences are very highly significant. Consistent with this question, 85.7% of the students who did not receive an E during the first year, predicted that there was a “very good chance” of their
0.39c
Women (n=7)
Semester Still CEAS (n=112) Left CEAS (n=33) F'95 7 6.3% 10 30.3% F'95 - S'96 14 12.5% 16 48.5% F'95-F'96 33 29.5% na Table 4. CEAS Id Students receiving at least one E
0.042a
Left CEAS
Women Left CEAS (n=7) 0.0% 71.4% 28.6% 0.0%
The students were asked about the chances of failing one or more classes. Again we will not know the answer to that for some students until they graduate, but we can look at the students who failed at least one class during their first three semesters while in the CEAS. (There were no failing grades (E’s) earned during the summer after the first year.) Fourteen of the 112 CEAS students, who gave predictions on the survey, received at least one E during the Fall 95 and Spring 96 semesters. By the end of Fall 96, a total of 33 of these students had received an E. (See Table 4.) Close to half of the students who were no longer in the CEAS had received at least one E.
0.0005b
Very good chance Some chance Very little chance No chance
p
Still CEAS (n=28) 75.0% 25.0% 0.0% 0.0%
0.28b
Graduation from CEAS: Id Students
All Left CEAS (n=33) 48.5% 36.4% 9.1% 6.0%
0.0004a
Very good chance Some chance Very little chance No chance
Still CEAS (n=112) 82.1% 14.3% 2.7% 0.9%
Class Failure Prediction
Table 3. Prediction of Graduation by Id Students Still CEAS vs. Left CEAS based on F96 status c- with Yates Correction for b - two-tailed Fisher's Exact Test for 2X2 tables 2X2 table
a - with categories pooled
Very good chance Some chance Very little chance No chance
No E's (n=96)
Fail Class At least one E (n=14)
7.3% 18.8% 42.8% 30.2%
42.9% 21.4% 28.6% 7.1%
Graduation At least one E (n=14)
No E's (n=98)
p
0.0004
85.7% 11.2% 2.0% 1.0%
a
57.1% 35.7% 7.1% 0.0%
p
0.025b
Table 5. CEAS Id Students with no E's vs. at least one E for F95-S96 a - last two categories pooled b - with Yate's correction, last three categories pooled
Still CEAS (n=96) Very good chance Some chance Very little chance No chance
7.3% 18.8% 42.8% 30.2%
Fail Class Left CEAS (n=17) 11.8% 23.5% 35.3% 29.4%
p
Still CEAS (n=98)
0.85
85.7% 11.2% 2.0% 1.0%
Graduation Left CEAS (n=17) 47.1%% 23.5% 17.6% 11.8%
p
.0001a
Table 6. CEAS Id Students with no E's for F95-S96 a- last two categories pooled
graduation from the CEAS. The graduation predictions of these two groups are also significantly different. The students receiving no E’s gave consistent predictions within the two groups of those still in the CEAS after one year and those who had left the CEAS. (See Table 6.) As would be expected, there was no statistical difference between the groups in their prediction of failing one or more classes. Also consistent with the decision to still be in CEAS or to leave, the predictions of graduating from the CEAS were very highly significantly different between the groups. There was no statistical difference between the students who received at least one E and were still at the CEAS and those who had left the CEAS with at least one E in predicting the chance of a class failure or graduation. Finally, if we look at the students who left the CEAS, there was no statistical difference between the predictions of graduation and the predictions of class failure between those that received no E’s and those who received at least one E.
ECE 100: Introduction to Engineering Still CEAS (n=113) Left CEAS (n=33) 43.4% 48.7% 6.2% 0.9% 0.9% 0.0%
33.3% 27.3% 24.2% 12.1% 3.0% 0.0%
p
Still CEAS (n=99) 31.3% 26.3% 24.2% 4.0% 5.1% 9.1%
Table 7 - Comparison of Grades of Students Still CEAS vs. Left CEAS a - last three categories pooled
Math Classes Left CEAS (n=31) 6.5% 12.9% 22.6% 9.7% 25.8% 22.6%
p
0.0004
A B C D E W
In analyzing the receipt of E’s by the survey students with ids, the failures in mathematics classes stood out. The distribution of ECE 100 grades earned by the CEAS students with ids was very highly statistically different for those students who were still in the CEAS during Fall 96 and for those students who had left. (See Table 7.) The proportion of A’s in each group was somewhat similar, but the percentage of B’s was much lower for the students who left. Consequently the students who left had a much larger proportion of grades at C or lower than the students who stayed in the CEAS. In addition, the distribution of grades, including W’s, earned in the math classes during the first fall semester was very highly significantly different for the two student groups. Among the 33 students who left the CEAS by fall 96, 30 took 31math courses their first semester. A grade of D, E, or W was earned in eighteen
0.0001a
Grade Earned Fall 1995
Grades in the ECE 100 and the Math Classes
(58.1%) of those courses. In Fall 95, the 113 students still in the CEAS, collectively took 99 math classes (9 students took two math classes). Only 17.7% of their math grades were below a C or a W. The 10 students who left the CEAS after their first semester received one A, one B, one C, three E’s, and four W’s. (Four of these students were on probation or dismissed after the first semester. Two of them received an E and two of them a W for their math class.) Therefore, 70% of the students who left the CEAS after one semester received a grade lower than a C or a W. By the end of the first year, 35 (31.0%) of the students still in CEAS in Fall 96 received math grades lower than C or a W. By way of contrast, 28 (84.8%) of the students who were no longer in the CEAS had received a grade lower than a C or a W. During their second semester, the 16 of the 23 students who did not return for Fall 96 received at least one D(4), E(9), or W(9). Nine of these 23 students were on probation or dismissed at the end of the semester.
Discussion There was no significant difference between the predictions of the students who gave a correct id and those that did not. However, the students who gave their ids may be more conscientious about doing well as students and thus also more willing to cooperate with a suggested response on a survey. The one-year retention rate for the students identified in this survey is much higher (about 75%) than that in general for first-time, full-time freshmen (60%). It may be that the better new students, and ones that would more likely persist, have pre-registered early and are able to enroll in the ECE 100 class in the fall semester of their first year. More research will be done on the two groups of students, those taking ECE 100 in the fall and those in the spring. Another factor to consider is that those students who took ECE 100 in the fall semester learned about engineering during their first semester at ASU. Understanding more about engineering up front may have reinforced their decision to become an engineer and enabled them to persist. Most students taking ECE 100 during the spring semester do not have any course in engineering until that time. The predictions of graduating from the CEAS were highly significantly different for those who were still in CEAS in Fall 96 and those who had left by that time. The predictions of women students who were still in the CEAS after one year were very highly significantly different from the women who had left. There was a similar significant difference between minority students and men who were still in the CEAS after one year and
those that were not. The men were more confident than women were of graduating from the CEAS. As a group, the minority students were the most confident about their chances to graduate from the CEAS. Women were the least confident group. The graduation predictions of women students who were still in the CEAS after one year were very highly significantly different from the women who had left. These results confirm the need for retention programs to be designed to increase the selfefficacy of women in engineering. Of the id students still in the CEAS after one year, the minority students had an 81.8% retention rate, women 80.6%, non-minority students 76.6%, and men 76.4%. The students were very good predictors on the chance of failing at least one class. The predictions of failing a class were very highly significantly different between those students who had no E’s and those that had at least one. These two groups also gave significantly different predictions on graduating from the CEAS. Of the students who received no E’s during their first year, the differences of the predictions on graduation were very highly significant. The math scores analysis highlights the importance of doing well in the first math class taken by an engineering student. Most of the students did not recover from doing poorly in a math class their first year. In light of this, the CEAS has urged the mathematics department to reinstate mathematics placement tests. The tests were made available Fall 96. Data is currently being analyzed to determine if the placement test can be used to predict the grade that a student will receive in the course. Studies have shown that many women who leave engineering may be doing well academically compared with men. This survey bore out this statement. Of the 6 women who were no longer in the CEAS after one year, only one had a GPA of less than a 2.0. Three of the women had a GPA greater than or equal to 3.0. Among the 27 men who left during or after the first year, 14 of them had a GPA of less or equal to 2.0. Five of them had a GPA of 3.0 or greater.
Conclusions All of the women who were still in the CEAS had predicted either a very good or some chance of their graduation from the CEAS. This was not true for the men. The id women who were no longer in the CEAS after one year were better graduation predictors than the id men who were no longer in the CEAS. The graduation predictions were significantly different for those that had left the CEAS and those who were still in the CEAS after one year for men, women, and minority
students. These results would suggest that an intervention program, especially with women and minorities in their first semester of engineering work, is needed to change a course that is already being set. If an engineering student thinks that it is unlikely that she/or he will graduate from the CEAS, it is likely that this will be the case. The students were rather good at predicting whether they would fail at least one course. The predictions of the retained students who did and who did not receive an E during their first year were very significantly different regarding failure of a class, as was their prediction of graduation from the CEAS. For the students receiving no E’s, the prediction of class failure was the same for those who had left the CEAS and those who had not, but their prediction of graduation from the CEAS was very statistically different. These results would suggest that the availability of tutors or other classroom help should be emphasized during orientation and in an intervention program of counseling around midterm in the first semester, especially for those students who believe that their chances are not good for graduating from the CEAS. The results of this study should be shared with the students. There was no significant difference in the ECE 100 grades of the students who were or were not still in the CEAS after a year. However, there was a definite correlation between poor math grades and attrition from the CEAS. The use of math placement tests will be continued and studies will be done on their ability to help direct a student to the correct first math class. Mandatory math placement based on the test should be considered. Based on these results, students are being encouraged very strongly to not attempt a math class for which they are not fully prepared. Records showed that the women who left the CEAS were doing better academically than the men who left. In fact, only one of the six women who left had a GPA of less than a 2.0. Additional research needs to be done on why women are leaving the CEAS. The retention rate of the id students in this survey is higher than that of CEAS freshmen in general. Further study will be done to see if there is a correlation between retention rates and the taking of ECE 100 in the first semester of the school year.
Acknowledgments Special thanks go to Dana Hastings for entering data from the survey and running many analyses on request. Dana also created numerous charts and the overheads to be used for the presentation of this paper. I appreciate her cheerfulness, patience, and complete competency
with the computer. A special thanks also goes to Gloria Rogers, a Foundation Coalition colleague at RoseHulman, for her critique of the survey and her suggestion of the addition of the question on academic future and success predictions.
References 1.
Felder, Richerd M., Felder, Gary N., Mauney, Meredith, Hamrin, Charles E. Jr., and Dietz, E. Jacquelin, “A Longitudinal Study of Engineering Student Performance and Retention. III. Gender Differences in Student Performance and Attitudes,” Journal of Engineering Education, April 1995, pp. 151-163. 2. Noel, Lee and Levitz, Randy, “Recruiting GraduatesTo-Be,” Recuitment & Retention in Higher Education, Vol. 9, No. 8, August 1995, pp. 4-6. 3. Sax, L. J., Astin, A. W., Korn, W. S., Mahoney, K. M., The American Freshman: National Norms for Fall 1995. Los Angeles: Higher Education Research Institute, UCLA., 1995, pp. 6-7. 4. Anderson-Rowland, Mary R., “Understanding Freshman Engineering Student Retention through a Survey,” Annual Conference Proceedings, American Society for Engineering Education, Milwaukee, Wisconsin, June 1997, Paper 3553.2, (CD-ROM), 7 pages. 5. Office of Institutional Analysis, Arizona State University, Tempe, Arizona. 6. “Why Undergraduates Withdraw from ASU During a Semester,” Student Affairs Research and Evaluations, Arizona State University, Tempe, Arizona, 1990, 16 pages. 7. Seymour, Elaine, and Hewitt, Nancy M., “Talking about Leaving: Factors Contributing to High Attrition Rates Among Science, Mathematics, and Engineering Undergraduate Majors,” Boulder: University of Colorado, Bureau of Sociological Research, 1994. 8. Johnson, David W., Johnson, Roger T., and Smith, Karl A., “Active Learning: Cooperation in the College Classroom,” Interaction Book Company, Edina, Minnesota, 1991. 9. Felder, Richard M., “A Longitudinal Study of Engineering Student Performance and Retention. IV. Instructional Methods," Journal of Engineering Education, October 1995, pp. 361-367. 10. Morrison, Catherine, Griffin, Kenneth, and Marcotullio, Peter, “Retention of Minority Students in Engineering,” NACME Research Letter, Volume 5, Number 2, December 1995, pp. 1-20.
11. Blaisdell, Stephanie L., “A Theoretical Basis for Recruitment and Retention Interventions for Women in Engineering,” Annual Conference Proceedings, American Society for Engineering Education, Washington, D. C., June 1996, Paper 1692.1, (CD Rom). 12. Bandura, A., “Self-efficacy: Toward a Unifying Theory of Behavioral Change,” Journal of Social and Clinical Psychological Review, 84(2), 1997, pp. 191215. 13. Anderson-Rowland, Mary R., “A First Year Engineering Student Survey to Assist Recruitment and Retention,” Proceedings, Frontiers in Education Conference, Salt Lake City, Utah, November 1996, pp. 372-376.
