Structural change in the CPCU curriculum and its effect on the completion time.

Choudhury, Askar ; Jones, James R. ; Gamage, Jinadasa 等

ABSTRACT

This study investigates the impact of structural change of CPCU program's curriculum on candidates (students) completion time. The CPCU professional certification is the most recognized system in the area of property/casualty insurance, which provides a comprehensive, integrated, skill and knowledge set in all areas of property/casualty insurance. American Institute for CPCU has changed their curriculum program in 2003; first, they have deleted two redundant courses from the program, second, provided students with two different options to choose from on elective courses. Data collected for this study include 1782 candidates who completed their program beginning 1999 to 2006. After controlling for age, gender, and education level, we find that structural change in 2003 is instrumental in shortening the length of program completion time. Results indicate that the predictive power of structural change in the curriculum to be contingent on the level of education and gender. Candidates with higher level of education, as measured by their highest degree earned, achieved significantly better performance. Findings of this study have important implications on curriculum change for any certification or degree program. Despite the differences among candidates education level, academic performance is impacted by structural change in the program curriculum. The relationship between gender-based increases in candidate's academic performance appears significant in this study. These findings are consistent with the hypothesis that efficient curriculum structure combined with education level enhances the shortening process of program completion time.

INTRODUCTION

The system of CPCU (Chartered Property and Casualty Underwriter) professional examinations and certification is the most recognized system in the area of property/casualty insurance, which provides comprehensive integrated, skill and knowledge set in all areas of property/casualty insurance. As with professional designations in other fields, such as the CPA in accounting, the CPCU is awarded to individuals willing to go beyond the normal requirements of their profession. The American Institute for Chartered Property and Casualty Underwriters (AICPCU) confers the CPCU designation. Traditionally, the CPCU designation was earned through the successful completion of ten college-level courses with national essay examinations, an experience requirement, and an agreement to be bound by ethical standards. Curriculum includes risk management, insurance products, insurance operations, financial analysis, and legal and regulatory environment of insurance. Each course is accredited by the American Council on Education (ACE) for at least 3 college undergraduate credits and some for 3 graduate credits. The certification helps practitioners to make sound, ethical decisions in the complex environment of property and casualty insurance.

During 2003, the CPCU curriculum was changed to enable students to complete the program by successfully completing 8 of 11 possible courses in the program. Thus an 8-part program is tantamount to completing about 24 hours of college credits (per ACE). The CPCU designation is conferred solely by the American Institute for CPCU of Malvern, Pa. In this research, we look at the changes in their program and how these changes affect CPCU program, as well as the length of completion time for certification.

The CPCU designation has been historically offered mostly in the United States, with the audience for it being the professionals within the property/casualty industry. The property/casualty industry in the United States operates in a regulated environment, and within the evolving American culture, consumer markets, and labor force. Thus factors such as, overall educational trends, demographic, litigation, and consumerism influence the insurance industry. Therefore, the need for educated professionals, and ultimately the desire and ability of insurance industry people to seek and attain CPCU certifications for diverse knowledge to keep up with the dynamic change in the environment. Thus, the objective of this paper is to analyze the effect of recent structural change in the CPCU program curriculum. We hypothesize, by changing the structure of the CPCU program curriculum; the modified system potentially mitigates the impact of the externalities in the completion time, in what may be characterized as "swift structural shift".

Our sample consists of observations of the CPCU designee candidates who completed the program. This sample covers the period of 1999 through 2006. The sample observations are divided into pre- and post-event structural change in 2003. We examine the intervention effect of the curriculum change on completion time (length of program completion) in number of months. We control for the age, gender and level of education. Pre-event period providing a benchmark, we find the structural change is instrumental in shortening the length of completion time. This suggests that the curriculum change have impacted candidate's performance to accelerate the course completion process. Our results contribute to the literature by documenting the constructive externalities of CPCU program and associating systematic curriculum change with the completion time momentum.

Following section summarizes the background information. In the third section we discuss our data selection and research methodology. Results of our analyses are discussed in section four and we summarize our findings in section five.

BACKGROUND

The number of industry designations has continued to grow. Although these other designations may not compete directly against CPCU in terms of curriculum offered, they may compete in terms of time. According to the 2007 Society of Insurance Trainers and Educators Designation Handbook, there are over 200 designations and certifications. U.S. Department of Education reported that over 125,000 people earned MBAs in 2005. Even though the number of business schools has increased by 10 percent according to the Department of Education, the growth rate of part-time students has been the most dramatic with 62 percent of schools reporting increases in enrollment and 20 percent reporting significant increases in part-time MBAs. The average age for part-time MBA enrollees is 31 years, which competes squarely with the market of prospective students enrolling in CPCU, which also had an average age of 31 for enrollment in CPCU over the period studied. Because the CPCU curriculum is a broad-based curriculum, focusing on all aspects of the industry including financial acumen, some courses are significantly quantitative. This may pose a problem to many students. The second half of the 20th century witnessed a trend of declining standards and quality in quantitative education in the U.S. Employers compete for a shrinking pool of talent of quantitative professionals, who can combine mathematical knowledge with practical applications. The effect of this trend is that a growing number of students may find the quantitative-oriented CPCU courses more challenging and therefore increase their completion time. This could also potentially affect the desire to enroll in or the ability to complete the CPCU program.

Exhibit 1: CPCU--Old Program Structure.

Foundations of Risk Management and Insurance
Personal Lines Insurance Coverage
Commercial Property Risk and Insurance
Commercial Liability Risk and Insurance
Insurance Company Operations
The Legal Environment of Insurance
Management
Accounting and Finance in Insurance
Economics
Insurance Ethics and Professionalism

The American Institute for CPCU cited several reasons for changing the curriculum. First, many of the students specialized and/or worked for companies that specialized in personal lines or commercial lines insurance. Enabling students to choose concentrations in their preferred area and then taking a survey course on the other lines was seen as more practical and relevant. This should generate interests among candidates to complete the program on an accelerated manner. In addition, courses from the old curriculum such as Management and Economics were deleted. The primary reason is that nearly 85 percent of CPCU matriculates had already taken similar course in their undergraduate or graduate degree program. This also enables the program to dovetail better with part-time MBA programs in which a growing number of professionals are enrolled. The growth in part-time MBA programs is probably the most significant competition for the time and resources of existing and prospective CPCU students.

Allowing students to take courses on additional topics was viewed as more relevant and supportive to the students. A new course on Financial Institutions was added to reflect the convergence of the financial services industry and the need for students to better understand other financial service products and operations in order to advance in their careers. Finally, the Institute believed that reducing the number of courses required from 10 to 8 would reduce "completion time" by several months. According to an internal survey conducted by AICPCU in 2001, "Time to Complete" was cited as the number one obstacle by students as reasons not to be able to complete CPCU certification program. The pressure on students to enroll in the CPCU program is always a challenge both with respect to money and time. Therefore, a structural transformation in the CPCU program can assist to alleviate these impediments.

Exhibit 2: CPCU--New Program Structure.

Five foundation courses:

Foundations of Risk Management, Insurance, and Professionalism
Insurance Operations, Regulation, and Statutory Accounting
The Legal Environment of Insurance
Finance for Risk Management and Insurance Professionals
Financial Services Institutions
Students can choose between (A or B) personal or commercial
concentration.

A. Commercial Concentration (with personal survey)
Commercial Property Risk Management and Insurance
Commercial Liability Risk Management and Insurance
Survey of Personal Risk Management, Insurance, and Financial
Planning

B. Personal Concentration (with commercial survey)
Personal Risk Management and Property-Liability Insurance
Personal Financial Planning
Survey of Commercial Risk Management and Insurance

DATA AND METHODOLOGY

The sample period is an eight year window with 1782 completed (i.e., number of candidates who completed the program) candidates' complete record of data. The event date, 2003, is the date when the structural change in the CPCU program went into effect. During this year they changed their regular ten course program into a more condensed 8 course program, which includes insurance related subject matters that are both at the undergraduate and graduate level. Revised program is equivalent to completing about 24 hours of college course credits and also has options between personal lines or commercial lines insurance. This has provided prospective candidates an incentive to enroll into the program and accelerate the completion time. Such major change in the curriculum procedure could impact the CPCU program and its affiliated CPCU Society greatly. To test the effect of this event on candidates' completion time (length of program completion), we divided our sample into two periods: the pre-event period--January 1999 through December 2002 and the post-event period includes January 2003 through December 2006. Researchers in other studies explored and tested this very important characteristic of intervention on both cross-section and longitudinal data; see Choudhury (2007) for an intervention analysis of a tax reform act on a longitudinal data.

Table-1A and Table-1B presents summary statistics for the pre- and post-event periods. A multiple regression analysis was applied to assess the significance of structural change in the CPCU program. Structural change variable is created as a dummy variable to asses the impact of the program change in 2003. In addition to the primary independent variable, program change, the analysis also included three other independent variables: gender, age, and level of education. Gender is a binary variable and coded 1 for male and 0 for female. A number of prior studies have investigated the impact of gender as a predictor of academic performance. Two earlier studies found that female students performed better than males in accounting area (Mutchler, Turner, & Williams, 1987; Lipe, 1989), while others found males outperforming females in finance (Borde, Byrd, & Modani, 1996) and Economics (Dale & Crawford, 2000; Heath, 1989). Several studies in computer arena found that, compared to male, females tend to display lower computer aptitude (Rozell & Gardner, 1999; Smith & Necessary, 1996; Williams, Ogletree, Woodburn, & Raffeld, 1993) and higher level of apprehension (Anderson, 1996; Bozionelos 1996; Igbaria & Chakrabarti 1990). Other studies, such as Zeegers (2001), however, could not find any differences between male and female learning behavior. Because the present study focuses on candidates' performance in terms of completion time, we include gender in the research model so its effect can also be explored and controlled to observe other factors effect.

To test the relationship between completion time and change in the program we perform two separate analyses. First, we use correlation analysis (Table 3A) to examine the direction of the association between variables and also to observe whether the program change exhibits any structural change. Second, we regress the completion time (number of months) on the age (AGE), gender (GENDER), education level (EDUCATION), and structural change in the program (PRGM_CHANGE). Completion time is calculated as number of months taken to complete the certification program. Therefore, the difference between the first examination date and the date of completion of the program is termed as completion time. Age is a continuous independent variable. In general, it is assumed that there is a difference between younger and older people in their learning process. These differences may relate to candidates' job position, the larger amount of life experience with motivation that they bring with them to a learning environment.

Numerous studies have found GPA to be significantly correlated with student performance in accounting (Doran, Bouillon, & Smith, 1991; Eskew & Faley, 1988; Jenkins, 1998), marketing (Borde, 1998), and economics (Bellico, 1974; Cohn, 1972; Dale & Crawford, 2000). However, because the level of education (highest degree earned) differs greatly among candidates in this study and their performance on completion time may be influenced due to the level of education, we therefore include education level as an independent variable instead of GPA. Vermunt (2005) observed that, education and learning patterns influence student's academic performance. In our study, education is an ordinal (hierarchical) categorical variable and therefore, kept in its original format (similar to Likert-Scale) ranging from high school diploma to doctorate, rather than coding into a set of indicator variables (note that, statistical significance remains comparable irrespective of type of coding of this factor). This factor will control for the level of background knowledge to isolate and test for candidates' performance in completion time due to structural change. The nature of academic discipline and education level is supposed to influence peoples thinking strategies to which academic performance may depend on.

Thus, a multiple regression model was run using SAS software (see, SAS/STAT User's Guide, 1993) on four different independent variables; age, gender, education, and program change. Program change is to measure the recent structural change in the CPCU program. This measure is designed to test the hypothesis of structural change (pre and post) in view of candidates' performance. Therefore, the specification of the regression model is of the following form:

Where:

Completion_Time: Length of time needed to complete. Age: Age of a candidate. Gender: Male=1, Female=0. Education (Level of Education): High School=1, Associate=2, Bachelor=3, Masters=4, Law=5, Doctorate=6. Prgm_Change: On or after 2003 = 1, before 2003 = 0.

Multiple regression is often appropriate for continuous and/or categorical predictive variable (X) with a continuous response (Y). It uses method of least squares or a method of maximum likelihood for normal populations. Further discussions on different estimation methods; see Choudhury, Hubata & St. Louis (1999), and Choudhury (1994).

EMPIRICAL RESULTS

Descriptive statistics for the various measures of independent and dependent variables are presented in Table 1A for pre-event period and in Table 1B for post-event period. Relatively large standard deviation value for completion time in pre-event period suggests that there was a great degree of variations among students' performance and as a result average completion time is quiet larger during the pre-event period compared to post event period. Gender differences are not quite visible in Table 2A and Table 2B between pre and post-event. Shown in Table 3A are simple pair-wise correlation coefficients among the independent variables. We found that gender and completion time were negatively correlated at the 0.05 significance level (note that, even though simple-correlation is statistically meaningless for gender, this correlation is only an indication of the relationship direction in a simple linear regression setting). This result is not surprising. As discussed earlier, studies suggest that males tend to demonstrate a higher level of proficiency in different environments than females. It is possible that gender-bound differences exert influence the way in which male and female are inclined to learn (Gallos, 1995; Gilligan, 1982; Richardson, 2000).

We also found education and completion time to be negatively correlated; this is consistent with the expectation that high-achieving students make greater efforts in acquiring the necessary knowledge and skills; as a result they may be more competitive. The correlations found in Table 3A do not pose a serious multicollinearity threat. Most of the correlation coefficients among independent variables are relatively small in magnitude.

In Table 3B, we report the results of the regression analysis. The proposed model appeared to fit well in estimating performance as a result of completion time. Reported coefficients of determination (R2) is 0.35, while F value is 236.33, at a significance level <0.0001. Results indicate that structural change is a significant (p-value <0.0001) predictor of student's performance as measured by completion time. Therefore, the program curriculum change in 2003 resulted in shortening candidates' completion time by 1.83 years (21.97 months) on average after controlling for demographic factors. Age is not statistically significant. Therefore, there was no evidence to support that age influences candidate's performance. Although, level of education is statistically significant but the magnitude of the coefficient does not contribute much to the curbing of completion time. Finally, we found gender to be a significant factor on completion time. This result provides support for the hypothesis that candidates' gender may contribute to a four month curbing of completion time for males. A number of possible explanations exist for this difference.

One explanation relates to differences in learning styles. Severiens and Ten Dam (1997) observe that males scored higher than female on undirected learning. The CPCU is primarily a self-study program. Nearly two-thirds of the students reported that they self-study. Although self-study could potentially be directed, it may be less directed than other educational alternatives. Contrast the CPCU program to MBA programs that provide instructor-led learning and directed group learning. The perceived self-efficacy may be higher for women in these more directed learning environments as one study indicates that in group work females perceive that they contribute more than their male counterparts (Kaenzig, Anderson and Lynn, 2006).

Competing educational alternatives may also explain the difference. In 2001, the number of females surpassed the number of males earning a bachelor's degree in business (see, U.S. Dept. of Ed., National Center for Education Statistics, Earned Degrees Conferred). Women earning a bachelor's in business may find the MBA education as a superior educational alternative for attaining professional credentials than a CPCU designation. In fact, 51 percent of schools offering MBA stated that they had special outreach efforts for females and in 2006 public universities saw a 55 percent increase in female applicants for MBA programs (GMAC 2006). Thus women who may have started their CPCU program may ultimately find that an MBA offers greater utility and better suitability to their learning style. Concurrent enrollment in MBA or other educational alternatives with greater perceived utility may contribute to augmenting the time for females to complete the CPCU designation.

Finally, a more traditional explanation of competing time demands for women compared to men, could also account for the difference. Considering that the average age of a CPCU enrollee is 31, competing time for family care could be a factor and gender differences in time spent on family care is well-documented. On weekdays, among adults living in households with children under 18, women spent 115 minutes each day performing childcare activities; by contrast, men spent 49 minutes. On weekends, women spent 78 minutes each day on childcare while men provided about 52 minutes. This amounts to annual difference of nearly 80 hours a year, the approximate amount of time to study for one CPCU exam. Furthermore the differences are even greater when considering secondary childcare activities such as housekeeping and purchasing goods and services for children (BLS 2006).

Each of the above possible explanations suggests strategies for the American Institute for CPCU for addressing gender differences including facilitating more directed and group learning, special marketing efforts to females, especially those with bachelor degrees in business, developing flexible exam and online learning formats. Also, facilitating improved expectation settings for family members of women enrolled in CPCU education.

CONCLUSIONS

In this study, we examine the performance impact of CPCU candidates' due to the structural change in the program. Results of multiple regression analysis found the predictive power of structural change in the program curriculum to be dependent on the level of education and gender. As expected, candidates with a higher level of education, as measured by their highest degree earned, achieved significantly better performance.

Findings from this study have important implications on curriculum change for any certification program. Despite the differences among candidates education level, their academic performance is impacted by the curriculum change. The relationship between gender-based increases in candidate's academic performance appears significant in this study. This predictive power of gender on performance may not depend on whether and how much level of education is attained by the candidate. Rather, it probably depends on which professional and personal lives environment they exist. These findings are consistent with the hypothesis that efficient curriculum structure combined with education level generates a motivational environment for shortening the completion time. Therefore, the results of this study indicate that the structural modification in the program have impacted and motivated candidates to accelerate their completion process.

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Askar Choudhury, Illinois State University

James R. Jones, Illinois State University

Jinadasa Gamage, Illinois State University

Krzysztof Ostaszewski, Illinois State University

TABLE-1A: Summary Statistics of Completion Time (1999-2002)

 Median Mean
 COMPLETION_TIME COMPLETION_TIME

EDUCATION GENDER
1 F 51.83 55.83
 M 40.42 38.88
 All 50.52 52.84

2 GENDER
 F 42.21 51.37
 M 40.5 40.21
 All 41.13 47.13

3 GENDER
 F 48.03 51.63
 M 45.24 48.57
 All 46.57 49.88

4 GENDER
 F 50.04 50.88
 M 43.58 43.94
 All 43.76 46.34

5 GENDER 42.44 45.93
 F 42.44 45.93
 M 42.18 44.79
 All 42.2 45.24

6 GENDER
 F -- --
 M 54.16 54.16
 All 54.16 54.16

All 45.27 49.09

 Std N
 COMPLETION_TIME COMPLETION_TIME

EDUCATION GENDER
1 F 14.94 28
 M 10.11 6
 All 15.53 34

2 GENDER
 F 19.74 31
 M 14.95 19
 All 18.72 50

3 GENDER
 F 19.04 309
 M 18.83 413
 All 18.97 722

4 GENDER
 F 18.43 53
 M 18.52 100
 All 18.72 153

5 GENDER 15.21 19
 F 15.21 19
 M 18.80 29
 All 17.31 48

6 GENDER
 F -- --
 M 12.62 2
 All 12.62 2

All 18.77 1009

TABLE-1B: Summary Statistics of Completion Time (2003-2006)

 Median Mean
 COMPLETION_TIME COMPLETION_TIME

EDUCATION GENDER
1 F 24.79 27.19
 M 32.02 28.14
 All 27.8 27.67

2 GENDER
 F 36.31 34.6
 M 22.45 22.3
 All 28.11 28.86

3 GENDER
 F 28.7 29.01
 M 27.62 26.85
 All 28.01 27.67

4 GENDER
 F 25.15 24.35
 M 21.6 22.46
 All 22.54 23.07

5 GENDER
 F 21.73 23.46
 M 18.58 20.99
 All 20.84 21.91

6 GENDER
 F 7.23 7.23
 M 32.22 28.13
 All 30.81 25.14

All 26.56 26.35

 Std N
 COMPLETION_TIME COMPLETION_TIME

EDUCATION GENDER
1 F 9.62 6
 M 7.49 6
 All 8.24 12

2 GENDER
 F 5.78 8
 M 6.39 7
 All 8.63 15

3 GENDER
 F 8.70 144
 M 8.95 233
 All 8.90 377

4 GENDER
 F 8.53 43
 M 9.86 91
 All 9.47 134

5 GENDER
 F 8.53 9
 M 9.75 15
 All 9.21 24

6 GENDER
 F -- 1
 M 12.74 6
 All 14.05 7

All 9.32 569

TABLE-2A: Summary Statistics of Completion Time by Gender (1999-2002)

 Median Mean
 COMPLETION_TIME COMPLETION_TIME

GENDER
F 48.03 51.540
M 44.02 47.200
All 45.27 49.090

 Std N
 COMPLETION_TIME COMPLETION_TIME

GENDER
F 18.63 440
M 18.67 569
All 18.77 1009

TABLE-2B: Summary Statistics of Completion Time by Gender (2003-2006)

 Median Mean
 COMPLETION_TIME COMPLETION_TIME

GENDER
F 27.58 27.88
M 25.12 25.44
All 26.56 26.35

 Std N
 COMPLETION_TIME COMPLETION_TIME

GENDER
F 8.95 211
M 9.43 358
All 9.32 569

TABLE-3A: Correlation Analysis (1999-2006)

Pearson Correlation Coefficients
Prob > |r| under H0: Rho=0

 COMPLETION_TIME PRGM_CHANGE AGE

COMPLETION_TIME 1.00000 -0.57858 -0.02876
 <.0001 0.2258

PRGM_CHANGE -0.57858 1.00000 -0.00450
 <.0001 0.8497

AGE -0.02876 -0.0045 1.00000
 0.2258 0.8497

GENDER -0.14852 0.07055 0.01469
 <.0001 0.0030 0.5377

EDUCATION -0.19816 0.24103 0.07824
 <.0001 <.0001 0.0010

 GENDER EDUCATION

COMPLETION_TIME -0.14852 -0.19816
 <.0001 <.0001

PRGM_CHANGE 0.07055 0.24103
 0.0030 <.0001

AGE 0.01469 0.07824
 0.5377 0.0010

GENDER 1.00000 0.08709
 0.0002

EDUCATION 0.08709 1.00000
 0.0002

Note: PRGM_CHANGE--represents the structural change in the
curriculum of CPCU program

TABLE-3B: Regression Results on Completion Time (1999-2006)

Analysis of Variance

 Sum of Mean
Source DF Squares Square F Value Pr > F

Model 4 228245 57061 236.33 <.0001
Error 1758 424470 241.45046
Corrected Total 1762 652715
R-Square 0.3497 Adj R-Sq 0.3482