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Improving financial literacy of college students: a cross-sectional analysis.

Financial literacy has become more important than ever as an increasing number of college students are relying on credit cards to finance their education. We examine whether college students are knowledgeable about finance, whether they improve upon that knowledge, and whether their demographic profile, financial backgrounds, and engagement/motivation level affect their financial knowledge and learning. Recruiting students who voluntarily participated in the pre- and post-tests of personal finance and managerial finance, and using multiple regression and the results of student course evaluations, we find that using finance courses positively affect the students' financial literacy. Moreover, we find that gender difference is found only in the pre-test of managerial finance, that female students significantly improved learning, and that students in the upper level of finance courses overall outperformed those in the lower level in both tests of personal finance and managerial finance. We also find that students' job experiences, financial background, attitude and behavior, and class participation and motivation determine the amount of their learning.

Keywords: Financial literacy, student learning, demographic profile, financial background, engagement/motivation

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Financial literacy has become more important than ever as an increasing number of college students are relying on credit cards to finance their education. In contrast to the growth of credit card usage, students may have limited knowledge on the specifics of credit cards, i.e., the cash advance fee, the interest rate on their credit card, their credit card limit, and their current credit card balance (Jones, 2005; Joo, Grable, & Bagwell, 2001; Warwick & Mansfield, 2000). On the basis of a survey result in which participants correctly answered 53% of questions on personal finance, Chen and Volpe (1998) claim that college students are not knowledgeable about personal finance and they may not make sound financial decisions.

Lyons (2004) and Jones (2005) argue that college students overall seem to use credit cards responsibly and to manage their balances. However, there are financially at-risk college students who have excessive amounts of debt in today's consumer culture (Roberts & Jones, 2001). Recent statistics show that more than 50 percent of the students may carry four or more credit cards when they reach their senior year and the number of 18 to 24-year-olds declaring bankruptcy has increased 96% in 10 years (Young Americans: Center for Financial Education, 2009).

Hayhoe, Leach, and Turner (1999), Hayhoe et al. (2005), and Jones (2005) show that students with four or more credit cards are more likely to be older and female, to feel good with the use of credit cards, to apply for the cards at every opportunity, and are less likely to understand that interest is the cost of using credit. Studies identify demographic profile and characteristics of financially at-risk college students (Lyons, 2004; Lyons & Hunt, 2003). The at-risk students are more likely to be female, black, and/or Hispanic, older, to be financially independent, to receive need-based financial assistance, to hold $1,000 or more in other types of debt, and to have acquired their credit cards by mail, at a retail store, and/or at a campus table.

Student learning is highly associated with education quality, student engagement, motivational effects, self-beliefs, and achievement expectations (Clayson, Haley, & Smith, 2008; Cottrell & Jones, 2002; House, 2006; Kuh, 2005; Hamilton & Saunders, 2009). They find that the quality of the student experience has been improved through course assessments and changes in course designs, and through students being more deeply involved in their own learning, i.e., academic challenge, active and collaborative learning, student-faculty interaction, enriching educational experiences, and supportive campus environment. A recent study shows that teaching styles and teaching techniques affect student performance differently for higher GPA versus lower GPA students and for quantitative majors and qualitative majors (Fendler, Ruff, & Shrikhande, 2009). Lower GPA students primarily benefit from the use of the Personal teaching style. High GPA, qualitative majors primarily benefit from the use of the Authority and Delegator teaching styles while high GPA, quantitative majors primarily benefit from the use of the Authority teaching styles.

The purpose of this study is threefold. First, we examine the status of financial literacy by recruiting subjects for the study. They are students who took managerial finance or portfolio management courses at the State University of New York, Fredonia in Spring 2009 semester. Sixty-four and forty-nine students from two sections of managerial finance and one section of portfolio management voluntarily participated in pre- and post-tests on the second day and the second to last day of the semester. The students answered 38 multiple choice questions (30 personal finance and 8 managerial finance questions) and 18 questions about their demographic profile and financial characteristics. The questions on personal finance were developed by the Jump$tart Coalition for Personal Financial Literacy while seven questions of managerial finance were adopted from the test bank developed by Ross, Westerfield, and Jordan (2008) and one question was from the National Council on Economic Education (2005).

New York State has personal finance standards in high school, although the standards are not required to be implemented. So, we predict that the students have decent knowledge of personal finance. However, the students who have not taken managerial finance have limited knowledge of the subject at the beginning of the semester. We find that students from the three classes correctly answered 19.5 (65%) to 22.7 (76%) of 30 questions on personal finance, and 3.1 (38%) to 4.7% (59%) of 8 questions on managerial finance in the pre-test. These results indicate that the students, on average, received passing grades in personal finance in contrast to the results of the previous studies (Chen & Volpe, 1998; 2006 Jump$tart Questionnaire). Students in the managerial finance classes received failing grades in the pretest of managerial finance, which is not surprising because most of them had not taken the course yet. Students in the portfolio management class who previously took managerial finance barely passed the pre-test of managerial finance with a grade D, which implies that they need reinforcement.

Secondly, we investigate student learning over the semester, using the pre- and post-tests. We find that students in one section of the managerial finance class significantly improved the average score on the test of managerial finance from 3.1 (39%) to 4.4 (55%) of 8 questions while students in the other section and portfolio management improved marginally. We also find that the significant improvement results in part from an increase in the average score of female students from 2.4 (30%) to 4.5 (56%). On the other hand, we find that students in all classes marginally improved or did not improve the average score on personal finance portion of the tests. These findings may support Chen and Volpe's (1998) claim that female students have lower levels of knowledge in the pre-test. However, they did not examine whether students improve learning. In addition, students in the portfolio management class overall performed significantly better in both tests of personal finance and managerial finance than those in the managerial finance classes.

Finally, we examine additional factors that will influence student learning. To test a progress of student learning, we employ student demographic profile and financial characteristics, and student self-evaluations. The profile and characteristics are mainly based on a survey questionnaire developed by the Jump$tart coalition. Data of the self-evaluations are available as part of the course evaluations by students at the end of the spring semester. We find that students who work full time in the summer and part time during the college year, and students who expect to earn more, performed better in the pre-test of managerial finance. We also find that the student ownership of a checking account positively affects performance in the pre-test of managerial finance while the student ownership of a credit card negatively affects performance in its post-test, and that students who are spending-oriented outperformed those who are thrifty or neither thrifty nor spending-oriented in the pre-test of personal finance. Furthermore, we find that a significant improvement of student learning in one section of the managerial finance class results in part from higher student participation, more effort, and high achievement expectations.

Hypotheses

Examining student learning over the semester, we set up the following hypotheses.

Hypothesis 1. Students who have not taken managerial finance will significantly improve knowledge in managerial finance at the end of the semester. This prediction is based on a continuous assessment of student performance at Fredonia.

Hypothesis 2. Students may not significantly improve knowledge in personal finance because they take managerial finance, not personal finance. This prediction is based on the importance of reinforcements. Although managerial finance is closely related to personal finance, student performance may not be significantly improved unless students take personal finance.

Hypothesis 3. Student demographic profile and financial background, and student self-evaluations affect student performance. This prediction highlights that gender, race, summer internship, use of debit and credit cards, attitudes towards spending, and class participation and motivation may play an important role in student performance and learning.

Data and Methods

The State University of New York at Fredonia offered three sections of BUAD 320 (Managerial Finance) and one section of BUAD 416 (Portfolio Management) in Spring 2009. One of the authors taught two sections of the managerial finance course (named BUAD 320(A) and BUAD 320(B)) and the portfolio management course (named BUAD 416). Nineteen, thirty-four, and twenty students enrolled in BUAD 320(A), BUAD 320(B), and BUAD 416, respectively. Before giving the students pre- and post-tests, the author received training through Collaborative Institutional Training Initiative Program and got an approval of the application for the use of human subjects. Sixty-four students participated in the pre-test. Nineteen and twenty-seven students are from BUAD 320(A) and BUAD 320(B), and eighteen are from BUAD 416. Forty-nine students participated in the post-test. Four and five fewer students of BUAD 320 (A) and BUAD 416 participated in the post-test, respectively. In contrast, four more students of BUAD 320(B) participated in the post-test.

Around two-thirds of the subjects (63%) are male students in both tests (see Table 1). More than eighty percent are Caucasians, about six percent are African American, and about two to three percent are Hispanic, Asian, or Native American. Most students are juniors or seniors, except for 3 and 4 sophomores in pre- and posttests. Forty of forty-six students in the managerial finance classes have not taken any finance-related classes while students in the portfolio management class have taken at least managerial finance. More than 90 percent of students are using debit cards while sixty-four percent and seventy-five percent have at least one credit card at the beginning and end of the semester, respectively.

T-statistic is used to compare student performance between classes, gender, or college level in the pre- and post-tests. The statistic includes differences in mean and standard deviation, and sample size. We use a multiple regression model to relate student demographic profile and financial characteristics to student performance.

Results

Student Performance in the Pre-test

Average scores in the pre-test of personal finance are 19.53 and 20.44 of 30 students in BUAD 320(A) and 320(B), respectively (see Table 2). They are not significantly different from zero at the 5 % level. Similar results are found in managerial finance. Average scores in the pre-test of managerial finance are 3.05 and 3.07 in each section, which are not significantly different from zero between the sections. Average scores in the pre-test of personal finance and managerial finance in BUAD 416 are 22.50 and 4.67, respectively. The score in the pre-test of managerial finance in BUAD 416 is significantly better than that in either BUAD 320(A) or BUAD 320(B) while the score in the pre-test of personal finance is significantly better than that only in BUAD 320(A). Results of the pre-test of personal finance indicate that the students overall passed the course with C, which is contrary to Chen and Volpe's (1998) study that students may have limited knowledge on making sound financial decisions. In addition, results of the pre-test of managerial finance are not surprising, considering that students in portfolio management already took managerial finance.

Table 2 shows that there is no significant difference in average scores in the pre-test of personal finance between males and females and between juniors and seniors in each class, and in average scores in the pre-test of managerial finance between juniors and seniors in each class, and between males and females in portfolio management. On the other hand, the average scores of male students in the pretest of managerial finance in BUAD 320(A) and BUAD 320 (B) are 3.70 and 3.56, which are significantly greater than those of female students, 2.33 and 2.36. These findings are overall consistent with the previous studies.

Student Performance in the Post-test

Similar results are found in student performance of personal finance in the post-test between both sections of managerial finance as in the pre-test (see Table 3). However, the average score in the posttest of managerial finance in BUAD 320(B) is 4.35, which is significantly better than that of BUAD 320(A), 3.29. In addition, students in BUAD 416 outperformed those in both BUAD 320(A) and BUAD 320(B) in personal finance while they outperformed students only in BUAD 320(A) in managerial finance at the 5% level of significance. Table 3 also shows that there is no significant difference of student performance in personal finance and managerial finance between males and females and between juniors and seniors in each class.

Table 4 shows that students in BUAD 320(B) significantly improved the average score on managerial finance, although students in BUAD 320(A) and BUAD 416 improved marginally. The table also shows that female students in BUAD 320(B) have significantly improved the average score of managerial finance over the semester. For example, their average score is 4.50 in the post-test while it is 2.36 in the pre-test. In addition, students in all classes, on average, marginally improved or did not improve performance in personal finance. These findings are in contrast to those of the pre-test where male students performed better than female students in both sections of managerial finance, which highlights student learning and reinforcements.

Other factors that may affect student performance

Demographic profile and financial background. The Jump$tart Coalition has developed a survey questionnaire of demographic profile and financial background, attitude, and behavior. Some of the survey questions are slightly modified to fit our sample. Demographic profile covers ethnicity, education plans after college, employment history, salary expectation, parents' total income, and parents' highest level of schooling. Financial characteristics, attitude, and behavior include ownership of a credit card, use of debit card, bank account, checking account balance and bounced checks, ownership of stocks and mutual funds, thrifty vs. spending-oriented, greatest cause of serious financial difficulty, feelings for families that cannot pay their bills, and older people without much money saved and a good pension.

Using dummy variables, we ran multiple regressions to find factors that influence average scores in the pre- and post-tests of personal finance and managerial finance in the combined sample of all classes as follows:

Score Personal Finance, or Managerial Finance = Intercept + [beta]1Xi, Eqs. (1) and (2) where Xi = Ethnicity, Education plans after College, Employment history, Salary expectation, Parents' total income, or Parent's highest level of schooling.

Score Personal Finance, or Managerial Finance = Intercept + [beta]1Xi, Eqs. (3) and (4) where Xi = Ownership of a credit card, Use of a debit (or ATM) card, Bank account, Checking account balance and bounced checks, Ownership of stocks and mutual Funds.

ScorePersonal Finance, or Managerial Finance = Intercept + [beta]1Xi, Eqs. (5) and (6) where Xi = Thrifty vs. spending-oriented, Greatest cause of serious financial difficulty, Feelings for families that cannot pay their bills, Older people w/o much money saved and a good pension.

Tables 5(a) and 5(b) show that non-Caucasian students outperformed Caucasian students by 0.45 point in the pre-test of managerial finance at 5% level of significance. Note that the proportion of non-Caucasian students is about 17% in the sample (11 of 64 students in the pretest). However, there is no significant difference between the groups in the posttest. The pre-test of managerial finance shows that students who plan to attend a master program performed worse than others. We find that students who work full time in the summer and part time during the college year performed better than others in the pre-test of managerial finance at the 5% level. Moreover, we find that students who expect to make $60,000 or more, or $40,000 to $49,999 per year performed better than those who expect to make less than $40,000, $50,000 to $59,999, or don't know in the pre-test of managerial finance. On the other hand, we have mixed results on parent's education. Students whose parents are college graduates or more performed worse in the pre-test and performed better in the post-test of managerial finance at the 5% level.

Results of the regressions of student financial background on average scores of personal finance and managerial finance are documented in Tables 6 (a) and (b). Students using their own credit cards and student using their own and their parents' credit cards performed worse in the posttest of managerial finance at the significance level of 5%. The ownership of at least a savings account positively affected performance in the pre-test of managerial finance. Students who subtract every check and ATM withdrawal from the balance in their checkbook, but have "bounced" at least one check for insufficient funds, performed better than others in the pre-test of managerial finance at the 5% level. Tables 7(a) and 7(b) indicate that students who are very spending-oriented, spending-oriented, or somewhat thrifty significantly outperformed those who are very thrifty and neither thrifty nor spending-oriented in the pre-test of personal finance. Lastly, the students who think that older people find it tough to live on Social Security performed significantly better than students who think that older people get by on Social Security by keeping their expenses down when they retire if they have not saved money and do not have a good pension from their former jobs in the post-test of personal finance.

Course evaluations by students. Students evaluate a course at the end of a semester at Fredonia. As part of a course evaluation, the students evaluate their attendance, participation, effort, and expected grades. Seventy-nine to ninety-five percent of students in BUAD 320(A), BUAD 320(B), and BUAD 416 responded to the evaluations. Table 8 shows that there is almost no difference in class attendance and preparation between the classes. Ninety-three to ninety-five percent of the students always or almost always attended class and seventy-three to seventy-eight percent devoted at least 6 six hours outside of class to the course per week.

However, with regard to the level of participation and effort, students in BUAD 320(B) more actively participated in and commit more effort to the course than those in BUAD 320(A) and BUAD 416. Seventy-four percent of students in BUAD 320(B) very actively or actively participated in the course in contrast to sixty and sixty-one percent in BUAD 320(A) and BUAD 416. Ninety-five percent of students in BUAD 320(B) rated their efforts excellent or good compared to seventy-nine percent and seventy-four percent in BUAD 320(A) and BUAD 416. Furthermore, there are significantly different grade expectations between the classes. Eighty-five and eighty-six percent of students in BUAD 416 and BUAD 320(B) expected their grade to be close to A or B. On the other hand, no student in BUAD 320(A) expected his or her grade to be A, and only forty-seven percent of students in the class expected their grade to be close to B.

These results may be consistent with the differences of student performance in the post-test of managerial finance between BUAD 320(A) and 320(B). The significantly improved student performance in BUAD 320(B) may be in part due to the students' higher participation and more effort. In addition, they would clearly expect what grades they would receive through feedback over the semester. These findings support the importance of student engagement and learning found in the previous studies, and are consistent with Hamilton and Saunders' (2009) claim that finance educators need to develop student-centered teaching methods where the educators design curricula fulfilling the learning needs of the new generation of learners, and engage them in the learning of finance concepts and methods and of financial decision making skills.

Conclusion

We examine whether college students are knowledgeable about finance, whether they improve learning on finance, and whether student demographic profile and financial background, and student engagement and motivation affect financial knowledge and learning. We recruited students for the study, following the guidelines of the use of human subjects. The students were taking managerial finance or portfolio management courses at the State University of New York, Fredonia, Spring 2009. Sixty-four and forty-nine students from two sections of managerial finance and one section of portfolio management voluntarily participated in the pre- and post-tests of personal finance and managerial finance.

We find that male students outperformed female students in the managerial finance classes on the pre-test of managerial finance, that students in section B of managerial finance outperformed those in section A in the post-test of managerial finance, and that female students in section B significantly improved performance in managerial finance. Moreover, we find students in portfolio management overall performed better than students in both sections of managerial finance in the pre- and post-tests of personal finance and managerial finance. It may not be surprising because managerial finance is a required course for all business students and portfolio management is a required course for finance majors only. In addition, students overall passed managerial finance with D in its post-test. These findings indicate the importance of student learning and reinforcement. Students have improved performance but have not achieved faculty expectations. We also find that summer job experiences, salary expectations, the ownership of a checking account or a credit card, and spending-oriented versus thrifty, influence student performance in the pre- or post-test of personal finance and managerial finance. Furthermore, we find that students significantly improved learning by actively participating in and committing more effort to the class.

References

Chen, H., & Volpe, R. P. (1998). An Analysis of Personal Financial Literacy Among College Students. Financial Services Review, 7, 107-128.

Clayson, D. E., Haley, D. A., & Smith, F. S. (2008). Improving the Quality of Finance Majors by Developing a Complementary and Synergistic Partnership: Faculty, Employers and Finance Majors. Advances in Financial Education, 6, 28-42.

Cottrell, S. A., & Jones, E. A. (2002). A Snapshot of Scholarship of Teaching and Learning Initiatives: Using Assessment Results to Improve Student Learning and Development. Assessment Update, 14, 6-7.

Fendler, R. J., Ruff, C., & Shrikhande M. (2009). Teaching Styles, Learning Levels, and Student Performance in the Finance Core. Advances in Financial Education, 7, 56-85.

Hamilton, J., & Saunders, K. T. (2009). An Update of Teaching Methods and Evaluation in the Introductory Finance Classroom. Advances in Financial Education, 7, 86-100.

Hayhoe, C. R., Leach, L. J., Allen, M. W., & Edwards, R. (2005). Credit Cards Held by College Students. Proceedings of the Association for Financial Counseling and Planning Education, 16(1), 1-10.

Hayhoe, C. R., Leach, L. J, & Turner, P. R. (1999). Discriminating the Number of Credit Cards Held by College Students Using Credit and Money Attitudes. Journal of Economic Psychology, 20, 643-656.

House, J. D. (2006). Using the College Student Survey to Assess Student Perceptions and Achievement. Assessment Update, 18, 7-9.

Jones, J. E. (2005). Credit Cards Held by College Students. Proceedings of the Association for Financial Counseling and Planning Education, 16(2), 9-16.

Joo, S., Grable, J. E., & Bagwell, D. C. (2001). College Students and Credit Cards. Proceedings of the Association for Financial Counseling and Planning Education, 12, 8-15.

Kuh, G. D. (2005). Putting Student Engagement Results to Use: Lessons from the Field. Assessment Update, 17, 12-13.

Lyons, A. C. (2004). Differences in Spending Habits and Credit Use of College Students. Journal of Consumer Affairs, 38, 56-80.

Lyons, A. C., & Hunt, J. L. (2003). The Credit Practices and Financial Education Needs of Community College Students. Proceedings of the Association for Financial Counseling and Planning Education, 14(1), 63-74.

National Council on Economic Education (2005). What American Teens and Adults Know About Economics.

Roberts, J. A., & Jones, E. (2001). Money Attitudes, Credit Card Use, and Compulsive Buying Among American College Students. Journal of Consumer Affairs, 35, 213-240.

Ross, S. A., Westerfield, R. W., & Jordan, B. D. (2008) Essentials of Corporate Finance, McGraw-Hill/Irwin.

Warwick, J., & Mansfield, P. (2000) Credit Card Consumers: College Student's knowledge and Attitude. Journal of Consumer Marketing, 17, 617-626.

Young Americans: Center for Financial Education, 2009.

Author Note

Mojtaba Seyedian and Taihyeup David Yi, Department of Business Administration, SUNY Fredonia. Correspondence concerning this article should be addressed to Mojtaba Seyedian, Department of Business Administration, SUNY Fredonia, Thompson Hall, Room E336E, 280 Central Ave. Fredonia, NY 14063. E-mail: Mojtaba.Seyedian@fredonia.edu

MOJTABA SEYEDIAN

TAIHYEUP DAVID YI

SUNY Fredonia
Table 1 Demographic Profile and Financial Background of Students

                                                           P.-Test

                                                           N      %
Gender
  Male                                                    40    62.5
  Female                                                  24    37.5
College Level
  Senior                                                  31    48.4
  Junior                                                  30    46.9
  Sophomore                                                3     4.7
Ethnicity
  White                                                   53    82.8
  Black                                                    4     6.3
  Hispanic                                                 2     3.1
  Asian                                                    2     3.1
  Native American                                          2     3.1
  Other                                                    1     1.6
Finance Classes Taken in College
  None                                                    40    59.7
  Personal finance only                                    3     4.5
  Managerial finance only                                  8    11.9
  Managerial finance and corporate finance                11    16.4
  Managerial finance and Investments                       5     7.5
  Managerial finance, corporate finance and Investments
  All
Ownership of a Credit Card
  My own                                                  29    45.3
  My parents'                                              3     4.7
  Both my own and my parents'                              9    14.1
  None, I don't use a credit card                         23    35.9
Use of a Debit (or ATM) card
  For getting cash from an ATM and for buying things      53    82.8
    directly
  For getting cash from an ATM only                        6     9.4
  Don't have a debit card                                  5     7.8

                                                          Post-Test

                                                           N     %
Gender
  Male                                                    37    62.7
  Female                                                  22    37.3
College Level
  Senior                                                  29    49.2
  Junior                                                  26    44.1
  Sophomore                                                4     6.8
Ethnicity
  White                                                   49    83.1
  Black                                                    4     6.8
  Hispanic                                                 2     3.4
  Asian                                                    1     1.7
  Native American                                          1     1.7
  Other                                                    2     3.4
Finance Classes Taken in College
  None
  Personal finance only                                   39    66.1
  Managerial finance only                                  2     3.4
  Managerial finance and corporate finance                 3     5.1
  Managerial finance and Investments                       1     1.7
  Managerial finance, corporate finance and Investments    9    15.3
  All                                                      5     8.5
Ownership of a Credit Card
  My own                                                  37    62.7
  My parents'                                              3     5.1
  Both my own and my parents'                              4     6.8
  None, I don't use a credit card                         15    25.4
Use of a Debit (or ATM) card
  For getting cash from an ATM and for buying things      52    88.1
    directly
  For getting cash from an ATM only                        3     5.1
  Don't have a debit card                                  4     6.8

Table 2 Student Performance (Pre-Test)

1. BUAD 320(A), BUAD 320(B), and BUAD 416

                      Personal   Finance

                 N      Mean     Std Dev         T-statistic

BUAD 320(A)      19    19.53      3.37
BUAD 320(B)      27    20.44      4.16            0.818 (a)
BUAD 416         18    22.50      4.20     2.365 (b) **, 1.618 (c)

2. BUAD 320(A)

                      Personal   Finance

                 N      Mean     Std Dev         T-statistic

Gender
  Male           10    20.60      3.89
  Fema1e         9     18.33      2.35              1.557
College Level
  Senior         12    19.17      3.43
  Junior         6     20.50      3.62           -0.748 (d)
  Sophomore      1     18.00       --

3. BUAD 320(B)

                      Personal   Finance

                 N      Mean     Std Dev         T-statistic
Gender
  Male           16    20.00      4.58
  Female         11    21.09      3.59             -0.692
College Level
  Senior         10    20.80      4.02
  Junior         15    20.53      4.16            0.162 (d)
  Sophomore      2     18.00      7.07

4. BUAD 416

                      Personal   Finance

                 N      Mean     Std Dev         T-statistic

Gender
  Male           14    22.43      4.42
  Female         4     22.75      3.95             -0.139
College Level
  Senior         9     22.67      3.50
  Junior         9     22.33      5.02              0.167

1. BUAD 320(A), BUAD 320(B), and BUAD 416

                 Managerial   Finance

                    Mean      Std Dev          T-statistic

BUAD 320(A)         3.05       1.27
BUAD 320(B)         3.07       1.54             0.043 (a)
BUAD 416            4.67       1.33     3.430 (b) **, 3.709 (c) **

2. BUAD 320(A)

                 Managerial   Finance

                    Mean      Std Dev          T-statistic

Gender
  Male              3.70       1.25
  Fema1e            2.33       0.87              2.794 **
College Level
  Senior            3.25       1.36
  Junior            3.00       0.89             0.467 (d)
  Sophomore         1.00        --

3. BUAD 320(B)

                 Managerial   Finance

                    Mean      Std Dev          T-statistic
Gender
  Male              3.56       1.50
  Female            2.36       1.36              2.160 **
College Level
  Senior            3.00       0.94
  Junior            3.33       1.84             -0.589 (d)
  Sophomore         1.50       0.71

4. BUAD 416

                 Managerial   Finance

                    Mean      Std Dev          T-statistic

Gender
  Male              4.50       1.34
  Female            5.25       1.26               -1.035
College Level
  Senior            4.67       1.66
  Junior            4.67       1.00                 0

Notes:

(a): T-statistic between BUAD 320(8) and BUAD 320(A): (b):
T-statistic between BUAD 416 and BUAD 320(A); (c): T-statistic between
416 and BUAD 320(B); (d): T-statistic between seniors and juniors.

*: Significant at the 10% level; **: Significant at the 5% level.

Table 3 Student Performance (Post-Test)

1. BUAD 320(A), BUAD 320(B), and BUAD 416

                         Personal   Finance

                   N       Mean     Std Dev    T-statistic

BUAD 320(A)       13      19.92      2.87
BUAD 320(B)       31      20.06      4.02       0.130 (a)
BUAD 416          14      22.86      4.20     2.841 (b) **,
                                              2.824 (c) **

2. BUAD 320(A)

                         Personal   Finance

                   N       Mean     Std Dev    T-statistic

Gender             6      21.33      2.88
  Male           8 (+)    18.71      2.43         1.756
  Fema1e
College Level      8      18.88      3.09
  Senior           5      21.75      1.71     -2.152 (d) *
  Junior           1      21.00       --
  Sophomore

3. BUAD 320(B)

                         Personal   Finance

                   N       Mean     Std Dev    T-statistic

Gender
  Male            21      19.52      4.65
  Female          10      21.20      1.87        -1.430
College Level
  Senior          14      21.36      3.91
  Junior          14      20.43      3.59       0.656 (d)
  Sophomore               17.00      6.56

4. BUAD 416

                         Personal   Finance

                   N       Mean     Std Dev    T-statistic

Gender
  Male            10      22.60      2.88
  Female           4      23.50      1.29        -0.806
College Level
  Senior           7      22.71      2.06
  Junior           7      23.00      3.06        -0.208

1. BUAD 320(A), BUAD 320(B), and BUAD 416

                 Managerial   Finance

                    Mean      Std Dev    T-statistic

BUAD 320(A)         3.29       1.33
BUAD 320(B)         4.35       1.28     2.504 (a) **
BUAD 416            5.14       1.35     3.653 (b) **,
                                         1.847 (c) *

2. BUAD 320(A)

                 Managerial   Finance

                    Mean      Std Dev    T-statistic

Gender              3.67       1.37
  Male              3.00       1.31         0.923
  Fema1e
College Level       3.38       1.69
  Senior            3.20       0.84       0.255 (d)
  Junior            3.00        --
  Sophomore

3. BUAD 320(B)

                 Managerial   Finance

                    Mean      Std Dev    T-statistic

Gender
  Male              4.29       1.45
  Female            4.50       0.85        -0.506
College Level
  Senior            4.43       1.16
  Junior            4.50       1.22      -0.156 (d)
  Sophomore         3.33       2.08

4. BUAD 416

                 Managerial   Finance

                    Mean      Std Dev    T-statistic

Gender
  Male              5.30       1.49
  Female            4.75       0.96         0.818
College Level
  Senior            4.86       1.68
  Junior            5.43       0.98        -0.775

Notes:

(a): T-statistic between BUAD 320(B) and BUAD 320(A): (b): T-statistic
between BUAD 416 and BUAD 320(A); (c): T-statistic between 416 and
BUAD 320(B); (d): T-statistic between seniors and juniors.

* Significant at the 10% level: **: Significant at the 5% level.

(+): One junior female student did not take personal finance
questions.

Table 4 Student Learning

1. BUAD 320(A), BUAD 320(B), and BUAD 416

                         Personal   Finance

                   N       Mean     Std Dev   T-statistic

BUAD 320(A)
  Pre-Test        19      19.53      3.37
  Post-Test       13      19.92      2.87      0.351 (a)
BUAD 320(B)
  Pre-Test        27      20.44      4.16
  Post-Test       31      20.06      4.02     -0.352
BUAD 416
  Pre-Test        18      22.50      4.20
  Post-Test       14      22.86      4.20      0.310

2. BUAD 320(A)

                         Personal   Finance

                   N       Mean     Std Dev   T-statistic
Male
  Pre-Test        10      20.60      3.89
  Post-Test        6      21.33      2.88      0.429
Female
  Pre-Test         9      18.33      2.35
  Post-Test      8 (+)    18.71      2.43      0.315

3. BUAD 320(B)

                         Personal   Finance

                   N       Mean     Std Dev   T-statistic

Male
  Pre-Test        16      20.00      4.58
  Post-Test       21      19.52      4.65     -0.314
Female
  Pre-Test        11      21.09      3.59
  Post-Test       10      21.20      1.87      0.089

4. BUAD 416

                         Personal   Finance

                   N       Mean     Std Dev   T-statistic

Male
  Pre-Test        14      22.43      4.42
  Post-Test       10      22.60      2.88      0.114
Female
  Pre-Test         4      22.75      3.95
  Post-Test        4      23.50      1.29      0.361

                 Managerial   Finance

                    Mean      Std Dev   T-statistic

BUAD 320(A)
  Pre-Test          3.05       1.27
  Post-Test         3.29       1.33      0.522
BUAD 320(B)
  Pre-Test          3.07       1.54
  Post-Test         4.35       1.28      3.413 **
BUAD 416
  Pre-Test          4.67       1.33
  Post-Test         5.14       1.35      0.983

2. BUAD 320(A)

                 Managerial   Finance

                    Mean      Std Dev   T-statistic
Male
  Pre-Test          3.70       1.25
  Post-Test         3.67       1.37     -0.044
Female
  Pre-Test          2.33       0.87
  Post-Test         3.00       1.31      0.045

3. BUAD 320(B)

                 Managerial   Finance

                    Mean      Std Dev   T-statistic

Male
  Pre-Test          3.56       1.50
  Post-Test         4.29       1.45      1.488
Female
  Pre-Test          2.36       1.36
  Post-Test         4.50       0.85      4.365

4. BUAD 416

                 Managerial   Finance

                    Mean      Std Dev   T-statistic

Male
  Pre-Test          4.50       1.34
  Post-Test         5.30       1.49      1.352
Female
  Pre-Test          5.25       1.26
  Post-Test         4.75       0.96     -0.631

Notes:

(a): T-statistic between post-test and pre-test

*: Significant at the 5% level

(+): One junior female student did not take persona1 finance
questions.

Table 5(a) Multiple Regression with Demographic Profile of Students
(Pre-Test)

(1) [Score.sub.Personal Finance] or (2) [Score.sub.Managerial
Finance] = Intercept + [[Beta].sub.1][X.sub.i], where [X.sub.i]; =
Ethnicity, Education plans after College, Employment history,
Salary expectation, Parents' total income, or Parent's highest
level of schooling

                                 (1)      Personal    Finance

Variable                         Dl          D2          D3        D4

Intercept         21.46
                  (3.32) **
Ethnicity                      -1.19
                               (0.64) *
Education Plans                -1.06      -0.77
  after College                (1.43)     (1.46)
Employment                      2.43       1.99        4.35
  History                      (1.67)     (1.71)      (2.51) *
Salary                          0.46       2.56        1.98       1.56
  Expectation                  (2.06)     (1.87)      (2.82)     (2.69)
Parents' Total                 -1.32      -1.88       -2.74
  Income                       (2.45)     (2.22)      (2.10)
Parent's                       -0.25      -0.01
  Highest                      (1.61)     (1.43)
  Level of
  Schooling
[R.sup.2]          0.24
                                           Manage-
                                 (2)        rial      Finance

Variable                         Dl          D2          D3

Intercept          2.87
                  (1.03) **
Ethnicity                      -0.45
                               (0.20) **
Education Plans                -0.72      -1.26
  after College                (0.44)     (0.45) **
Employment                      1.19      -0.03        0.43
  History                      (0.52) **  (0.53)      (0.78)
Salary                          2.55       2.96        2.03
  Expectation                  (0.64) **  (0.58) **   (0.88) **
Parents' Total                 -0.77      -0.75       -0.13
  Income                       (0.76)     (0.69)      (0.65)
Parent's Highest               -0.57      -1.07
  Level of                     (0.50)     (0.45) **
  Schooling
[R.sup.2]          0.50

Variable             D4

Intercept

Ethnicity

Education Plans
  after College
Employment
  History
Salary              3.94
  Expectation      (0.84) **
Parents' Total
  Income
Parent's Highest
  Level of
  Schooling
[R.sup.2]

Table 5(b) Multiple Regression with Demographic Profile of Students
(Post-Test)

                                 (1)      Personal    Finance

Variable                          Dl      D2             D3        D4

Intercept         17.26
                  (2.76) **
Ethnicity                      -0.29
                               (0.50)
Education Plans                 2.00       0.71
  after College                (1.51)     (1.67)
Employment                      2.11       1.80        1.51
  History                      (1.43)     (1.54)      (1.87)
Salary                          1.15       1.95        1.93       2.32
  Expectation                  (1.90)     (2.03)      (2.70)     (2.47)
Parents' Total                  1.59       0.56       -2.46
  Income                       (2.55)     (2.39)      (2.31)
Parent's                        1.34       2.24
  Highest Level                (1.42)     (1.38)
  of Schooling
[R.sup.2]          0.25

                                           Manage-
                                 (2)        rial      Finance

Variable                          Dl              D2       D3      D4

Intercept          2.45
                  (1.07) **
Ethnicity                      -0.00
                               (0.20)
Education Plans                 0.50       0.62
  after College                (0.59)     (0.65)
Employment                      0.81       0.96        1.30
  History                      (0.56)     (0.60)      (0.72) *
Salary                          0.64       1.16        1.23       0.83
  Expectation                  (0.74)     (0.79)      (1.05)     (0.96)
Parents' Total                  0.09      -0.22       -1.09
  Income                       (0.99)     (0.92)      (0.89)
Parent's                       -0.05       1.06
  Highest Level                (0.55)     (0.53) **
  of Schooling
[R.sup.2]          0.26

Note: Standard deviation in parenthesis. *: Significant at 10%.
**: Significant at 5%.

Gender: Ethnicity: D1 = 1 if White, 0 Otherwise; Education plans after
college: D1=1 if No further education is planned, D2=1 if Attend a
master program, 0 if Don't know; Employment history: D1 =1 if Work
full time in summer and part time in college year, D2=1 if Work full
time in summer and don't work in college year. D3=1 if Work part time
in summer and part time in college year, 0 if Work part time in summer
and don't work in college year; Salary expectation: D1=1 if Under
$30,000 or $30,000 to $39,999, D2=1 if $40,000 to $49,999, D3=1 if
$50,000 to $59,999, D4=7 if $60,000 or more, 0 if Don't know; Parents'
total income: D1=1 if Less than $20,000 or $20,000 to $39,999. D2=1 if
$40,0110 to $79,999, D3=1 if $80,000 or more, 0 if Don't know; Parent's
highest level of schooling: D1=1 if Some college, D2=1 if College
graduate or more than college, 0 if Completed high school.

Table 6(a) Multiple Regression with Financial Background of Students
(Pre-Test)

(3) [Score.sub.Personal Finance] or (4) [Score.sub.Managerial
Finance] = Intercept + [[beta].sub.1][X.sub.i], where [X.sub.i] =
Ownership of a credit card, Use of a debit (or ATM) card, Bank
account. Checking account balance and bounced checks, Ownership of
stocks and mutual Funds

                                               (3)        Personal

Variable                                       D1            D2

Intercept                       21.76
                              (3.21) **
Ownership of a Credit                         1.63          -0.15
  Card                                       (1.31)        (2.78)
Use of a Debit (or ATM)                       3.43          4.44
  card                                       (2.64)        (3.18)
Bank Account                                  -2.90         -0.46
                                             (4.30)        (4.04)
Checking Acct Balance                         1.05          0.29
  and Bounced Checks                         (2.18)        (1.28)
Ownership of Stocks and                       -1.76
  Mutual Funds                               (1.45)
[R.sup.2]                       0.16

                               Finance

Variable                         D3            D4

Intercept

Ownership of a Credit           -0.36
  Card                         (1.69)
Use of a Debit (or ATM)
  card
Bank Account                    -2.39
                               (4.05)
Checking Acct Balance           0.63
  and Bounced Checks           (2.03)
Ownership of Stocks and
  Mutual Funds
[R.sup.2]

                                               (4)       Managerial

Variable                                       D1            D2

Intercept                       1.42
                               (1.11)
Ownership of a Credit                         0.32          -1.71
  Card                                       (0.45)       (0.96) *
Use of a Debit (or ATM)                       -1.60         -1.91
  card                                      (0.91) *      (1.10) *
Bank Account                                  2.97          1.64
                                            (1.49) **      (1.40)
Checking Acct Balance                         1.11          0.89
  and Bounced Checks                         (0.76)       (0.44) **
Ownership of Stocks and                       0.58
  Mutual Funds                               (1.17)
[R.sup.2]                       0.33

                               Finance

Variable                         D3            D4

Intercept

Ownership of a Credit          -0.77
  Card                         (0.59)
Use of a Debit (or ATM)
  card
Bank Account                    2.89
                              (1.40) **
Checking Acct Balance           0.88
  and Bounced Checks           (1.25)
Ownership of Stocks and
  Mutual Funds
[R.sup.2]

Table 6(b) Regression with Financial Background of Students Post-Test

                                               (3)        Personal

Variable                                       D1            D2

Intercept                       23.57
                              (3.54) **
Ownership of a Credit                         -0.63         -3.19
  Card                                       (1.11)        (2.27)
Use of a Debit (or ATM)                       -1.74         -0.98
  card                                       (2.74)        (3.31)
Bank Account                                                1.14
                                                           (4.74)
Checking Acct Balance                         -5.13         -1.97
  and Bounced Checks                        (1.74) **     (1.15) *
Ownership of Stocks and                       -0.57
  Mutual Funds                               (1.16)
[R.sup.2]                       0.29

                               Finance

Variable                         D3            D4

Intercept

Ownership of a Credit          -3.97
  Card                        (2.21) *
Use of a Debit (or ATM)
  card
Bank Account                    2.16
                               (4.65)
Checking Acct Balance           -0.80
  and Bounced Checks           (1.49)
Ownership of Stocks and
  Mutual Funds
[R.sup.2]

                                               (4)       Managerial

Variable                                       D1            D2

Intercept                       3.54
                              (1.31) **
Ownership of a Credit                         -0.89         -0.05
  Card                                      (0.41) **      (0.84)
Use of a Debit (or ATM)                       -1.49         -0.89
  card                                       (1.01)        (1.22)
Bank Account                                                2.61
                                                           (1.75)
Checking Acct Balance                         -0.95         -0.27
  and Bounced Checks                         (0.64)        (0.43)
Ownership of Stocks and                       0.46
  Mutual Funds                               (0.43)
[R.sup.2]                       0.27

                               Finance

Variable                         D3            D4

Intercept

Ownership of a Credit           -2.01
  Card                        (0.82) **
Use of a Debit (or ATM)
  card
Bank Account                    2.70
                               (1.71)
Checking Acct Balance           -0.36
  and Bounced Checks           (0.55)
Ownership of Stocks and
  Mutual Funds
[R.sup.2]

Note: Standard deviation in parenthesis, *: Significant at 10%, **:
Significant at 5%

Ownership of a Credit Card: D1=1 if My own, D2=1 if My parents', D3=1
Both my own and my parents', 0 It Nona, I don't use a credit card; Use
of a Debit (or ATM) card: D1=1 if For getting cash from an ATM and
for buying things directly, D2=1 For getting cash from an ATM only, 0
if Don t have a debit card; Bank Account:  D1=1 if Have a savings
account but no checking account, D2=1 if Have a checking account but
no savings account, D3=1 if Have both a savings and a checking
account, 0 if Don't have a bank account; Checking Account Balance and
Bounced Checks: D1=1 ff Subtract every check and ATM withdrawal from
the balance in  my checkbook but have "bounced" at least one check for
insufficient funds, D2=1 if Don't subtract every check and ATM
withdrawal from my checkbook but have  never "bounced" a check, D3=1 if
Don't subtract every check ATM and withdrawal from my checkbook and
have "bounced" at least one check for insufficient funds, 0 if
Subtract every check and ATM withdrawal from the balance in my
checkbook and have never "bounced" a check for insufficient funds;
Ownership of Stocks and Mutual Funds: D1=0 if Own no stocks or mutual
funds, 1 Otherwise.

Table 7(a) Multiple Regression with Financial Altitude and Behavior
of Students (Pre-Test) (5) [Score.sub.Personal Finance] or (6)
[Score.sub.Managerial Finance] = Intercept + [[beta].sub.1][X.sub.i],
where [X.sub.i] = Thrifty vs. spending-oriented, Greatest cause of
serious financial difficulty, Feelings for families that cannot pay
their bills, Older people w/o much money saved and a good pension

                                               (5)        Personal

Variable                                       D1            D2

Intercept                       12.96
                              (3.75) **
Thrifty vs. Spending-                         -0.11         4.33
  Oriented                                   (1.97)       (1.42) **
Greatest Cause of Serious                     1.90          1.21
  Financial Difficulty                       (2.05)        (2.05)
Feelings for Families That                    -0.20
  Cannot Pay Their Bills                     (0.91)
Older People w/o Much                         1.28
  Money Saved and a                          (1.04)
Good Pension
[R.sup.2]                       0.28

                               Finance

Variable                         D3            D4

Intercept

Thrifty vs. Spending-           4.80          5.37
  Oriented                    (1.61) **     (2.27) **
Greatest Cause of Serious       2.74
  Financial Difficulty         (2.38)
Feelings for Families That
  Cannot Pay Their Bills
Older People w/o Much
  Money Saved and a
Good Pension
[R.sup.2]

                                               (6)       Managerial

Variable                                       Dl            D2

Intercept                       2.66
                               (1.65)
Thrifty vs. Spending-                         0.13          0.91
  Oriented                                   (0.86)        (0.62)
Greatest Cause of Serious                     0.03          0.40
  Financial Difficulty                       (0.90)        (0.90)
Feelings for Families That                    0.07
  Cannot Pay Their Bills                     (0.40)
Older People w/o Much                         -0.02
  Money Saved and a                          (0.45)
Good Pension
[R.sup.2]                       0.08

                               Finance

Variable                         D3            D4

Intercept

Thrifty vs. Spending-           0.16          0.67
  Oriented                     (0.71)        (1.00)
Greatest Cause of Serious       0.41
  Financial Difficulty         (1.05)
Feelings for Families That
  Cannot Pay Their Bills
Older People w/o Much
  Money Saved and a
Good Pension
[R.sup.2]

Table 7(b) Regression with Financial Attitude and Behavior of
Students (Post-Test)

                                               (5)        Personal

Variable                                       D1            D2

Intercept                       16.32
                              (3.26) **
Thrifty vs. Spending-                         1.61          0.64
  Oriented                                   (1.80)        (1.39)
Greatest Cause of Serious                     -1.11         -1.27
  Financial Difficulty                       (1.71)        (1.69)
Feelings for Families That                    -0.91
  Cannot Pay Their Bills                     (0.81)
Older People w/o Much                         2.42
  Money Saved and a                         (0.94) **
  Good Pension
[R.sup.2]                       0.26

                               Finance

Variable                         D3            D4

Intercept

Thrifty vs. Spending-           2.69          2.41
  Oriented                    (1.53) *       (2.17)
Greatest Cause of Serious       -3.31
  Financial Difficulty         (2.21)
Feelings for Families That
  Cannot Pay Their Bills
Older People w/o Much
  Money Saved and a
  Good Pension
[R.sup.2]

                                               (6)       Managerial

Variable                                       D1            D2

Intercept                       4.19
                              (1.43) **
Thrifty vs. Spending-                         0.25          -0.32
  Oriented                                   (0.79)        (0.61)
Greatest Cause of Serious                     -0.39         -0.43
  Financial Difficulty                       (0.75)        (0.74)
Feelings for Families That                    -0.22
  Cannot Pay Their Bills                     (0.35)
Older People w/o Much                         0.40
  Money Saved and a                          (0.41)
  Good Pension
[R.sup.2]                       0.07

                               Finance

Variable                         D3            D4

Intercept

Thrifty vs. Spending-           0.27          0.39
  Oriented                     (0.67)        (0.95)
Greatest Cause of Serious       -0.86
  Financial Difficulty         (0.97)
Feelings for Families That
  Cannot Pay Their Bills
Older People w/o Much
  Money Saved and a
  Good Pension
[R.sup.2]

Note: Standard deviation in parenthesis, * : Significant at 10%,
** : Significant at 5%

Thrifty vs. Spending-Oriented: D1=1 if Very thrifty, saving money
whenever I can, D2=1 if Somewhat thrifty, often saving money, D3=1 if
Somewhat spending oriented, seldom saving money, D4=1 if Very spending-
oriented, hardly ever saving money, 0 if Neither thrifty nor spending-
oriented, Greatest Cause of Serious; Financial Difficulty: D1=1 if
Buying too much on credit. D2=1 if Not following a financial plan,
D3=1 if Not being able to earn enough money, 0 if Not enough savings;
Feelings for Families That Cannot Pay Their Bills: D1=0 if Not so bad,
a lot of families go through this, or Pretty bad, it is painful to
experience, D1=1 if Very bad, it is one of the worst things that can
happen to a family; Older People w/o Much Money Saved and a Good
Pension: D1=0 if Get by on Social Security by keeping their expenses
down, D1=1 if Find it tough to live on Social Security.

Table 8 Student Course Evaluations

Q1 How often did you attend class?

                                        Almost          Most of the
                      Always            always             time

BUAD 320(A)           6 (40%)           8 (53%)           1 (7%)
BUAD 320(B)          14 (52%)          11 (41%)           2 (7%)
BUAD 416              7 (37%)          11 (58%)           1 (5%)

Q2 On average, how man hours outside of class did you devote to this
course per week?

                        9+                6-8               4-5

BUAD 320(A)           3 (20%)           8 (53%)           3 (20%)
BUAD 320(B)           8 (30%)          13 (48%)           6 (22%)
BUAD 416              4 (21%)          10 (53%)           4 (21%)

Q3 What was your level of participation in this course?

                                                        Moderately
                    Very active         Active            active

BUAD320(A)            1 (7%)            8 (53%)           6 (40%)
BUAD 320(B)           2 (7%)           18 (67%)           3 (11%)
BUAD 416              5 (28%)           6 (33%)           6 (33%)

Q4 Which is the closest to your expected grade in the course?

                         A                 B                 C

BUAD 320(A)           0 (0%)            7 (47%)           7 (47%)
BUAD 320(B)           8 (30%)          15 (56%)           4 (15%)
BUAD 416              6 (32%)          10 (53%)           3 (16%)

Q5 How would you rate your effort in the course?

                     Excellent           Good            Adequate

BUAD 320(A)           5 (36%)           6 (43%)           2 (14%)
BUAD 320(B)           6 (23%)          19 (73%)           1 (4%)
BUAD 416              8 (42%)           6 (32%)           5 (26%)

                                     Less than 1/
                   About 1/2 of        2 of the
                     the time            time

BUAD 320(A)           0 (0%)            0 (0%)
BUAD 320(B)           0 (0%)            0 (0%)
BUAD 416              0 (0%)            0 (0%)

Q2 On average, how man hours outside of class did you devote to this
course per week?

                        2-3               0-1

BUAD 320(A)           1 (7%)            0 (0%)
BUAD 320(B)           0 (0%)            0 (0%)
BUAD 416              1 (5%)            0 (0%)

Q3 What was your level of participation in this course?

                   Occasionally       Not active
                      active

BUAD320(A)            0 (0%)            0 (0%)
BUAD 320(B)           3 (11%)           1 (4%)
BUAD 416              0 (0%)            1 (6%)

Q4 Which is the closest to your expected grade in the course?

                         D                 F

BUAD 320(A)           1 (7%)            0 (0%)
BUAD 320(B)           0 (0%)            0 (0%)
BUAD 416              0 (0%)            0 (0%)

Q5 How would you rate your effort in the course?

                       Poor            Very poor

BUAD 320(A)           1 (7%)            0 (0%)
BUAD 320(B)           0 (0%)            0 (0%)
BUAD 416              0 (0%)            0 (0%)

Notes:

(1.) Course enrollment: 19 in BUAD 320(A), 34 in BUAD 320(8), and 20
in BUAD 416.

(2.) Number of survey respondents: 15 (79%) in BUAD 320(A), 27 (79%)
in BUAD 320(B), and 19 (95%) in BUAD 416.
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Publication:College Student Journal
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Geographic Code:1USA
Date:Mar 1, 2011
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