An empirical examination of the phenomenon of grade inflation in higher education: a focus of grade divergence between business and other fields of study.

Lowe, S. Keith ; Borstorff, Patricia C. ; Landry, Robert J., III 等

ABSTRACT

This study examined the level of grade inflation experienced by college graduate cohorts between two time periods: 1993 and 2000. Research emphasis was centered upon grade inflation of graduates in business and compared to eleven other academic fields of study. The data for this study originated from the Baccalaureate and Beyond Longitudinal Study (B&B) series conducted by the National Center for Educational Statistics. Through independent sample t-tests, the results showed significant grade inflation in the GPA of college graduates had occurred in the interim between these two time periods. Specifically, it was found that cumulative and within major GPAs had increased across all twelve fields of study at means of 0.23 and 0.21 grade points, respectively. One-way analysis of variance (ANOVA) procedures also indicated that while grade inflation did occur within each of the twelve academic fields of study chosen for this study, some fields experienced a disproportionate rate of grade inflation in relation to the other fields. Post-hoc tests revealed that graduates from the business field experienced grade inflation that was significantly different than several other fields of study. Notably, the grade inflation level within major GPA from business graduates was higher than graduates in engineering, life sciences, mathematics, and physical sciences but less than education and professional fields. The level of grade inflation within cumulative GPA of business graduates was found to be less than graduates in health, life sciences, mathematics, and physical sciences but greater than graduates in professional fields of study.

INTRODUCTION

Academic achievement as a research topic is prevalent within the existing literature on higher education in the United States. The most common measurement of academic achievement is provided through the assignment of some form of grading or marking system (Basinger, 1997; Betts, 1995). Colleges and universities almost universally assess student academic achievement through an administrative policy whereby faculty members assign a letter or numerical grade for individual courses to students (Grove & Wasserman, 2004; Iyasere, 1984). Administrators in turn utilize the grades assigned by faculty members and convert them to a scale commonly referred to as a quality point or grade point average (GPA) to create a measure of academic success (Murray & Wren, 2003; Riley, Checca, Singer, & Worthington, 1994).

According to Agnew (1995) and Caulkins, Larkey, and Wei (1996), GPA is the dominant measure of student quality in all levels of education within the United States, specifically institutions of higher education. The most common scale of GPA is administered upon the four-point scale, with a "perfect" GPA being defined by a 4.0. Final GPAs are a key component in shaping college graduates' educational and career paths through several methods, including acceptance into graduate and professional institutions, academic scholarships, financial aid, and desirable employment in the corporate world (Caulkins, Larkey, & Wei, 1996; Freeman, 1999; Pope & Ma, 2004; Wright & Palmer, 1994). Because excellent grades are an outcome sought by most students in higher education, the pressure to both earn these grades by students and to provide them by faculty has become immense (Birk, 2000; Goldman, Schmidt, Hewitt, & Fisher, 1974). While the importance of GPA has been exacerbated in recent years, Mannello (1964) exemplifed the importance college students place upon grades over four decades ago by noting that "students have a neurotic fixation on grades" (p. 328). The trend whereby the overall grades of college graduates has continued to increase at a swift rate is often referred to as grade inflation.

One of the aspects of grade inflation that has received less attention and dedicated research is that grade inflation has not occurred unilaterally across various academic disciplines and individual colleges within postsecondary institutions (Becker, 1997; Shea, 1994). This difference in overall student GPAs has shown grades to increase at an uneven rate across various academic disciplines, an occurrence that has been referred to by Freeman (1999) as grade divergence. Specifically, grades in business and natural sciences tend to be lower and less affected by grade inflation than grades in other fields such as education, humanities, and the pre-professional fields such as law or medicine (Becker, 1997; Shea, 1994). It is from the divergence point-of-view proposed by Freeman (1999) concerning the differences between fields of study in grade inflation this study is focused. Specifically, the area of business is highlighted and its interrelationship to the eleven other fields chosen for this study.

LITERATURE REVIEW

Data on college student grading suggest that undergraduate GPAs have been inflating over the past three decades across all types of postsecondary institutions (Geisinger, 1980; Wilson, 1999). This increase is illustrated by Levine and Cureton's (1998) research of GPAs reported by undergraduate institutions in three different years: 1969, 1976, and 1993. The percentages of the grade of A and C have effectively reversed themselves. In 1969, seven percent of all undergraduate students received grades of A-minus or higher. By 1993, this proportion had risen to 26 percent. In contrast, grades of C or lower decreased from 25 percent in 1969 to nine percent on 1993.

Grade inflation is the focus of a considerable body of literature analyzing several hypothesized contributing factors to its existence (Dickson, 1984; Feldman, 1976; Kolevzon, 1981; McKenzie & Staaf, 1974; Moore & Trahan, 1998; Share, 1997). While not an inclusive list, the most cited factors leading to grade inflation include: student retention (which leads to increased funding dollars in most states), changing student demographics, student evaluations, and the evolving role of faculty priority toward research activities. Also prevalent within the literature are suggested outcomes that arise from the presence of grade inflation (Sabot & Wakeman-Linn, 1991; Shea, 1994) and suggested solutions and remedies to curtail its occurrence (Felton & Koper, 2005; Johnson, 1997; Martinson, 2004; Nagle, 1998; O'Connor, 1979; Scott, 1988; White, 1997; Zangenehzadeh, 1988).

The introduction of the term "grade inflation" owes its roots to the era of the early 1960s when college grades began to rise at a time when monetary pricing for consumer goods and services were also rising at a swift rate (Kamber & Biggs, 2004). Select researchers suggest that the term of inflation was assigned to the grading of students out of convenience due to the perceived association with the deteriorating buying power of the United States dollar and that terms such as "grade devaluation", "grade leniency," or "grade compression" would have been more fitting terms (Kamber & Biggs, 2004; Kuh & Hu, 1999; Landrum, 1999). Yale University actually refers to the phenomenon of grade inflation within many of its publications under a synonymous term: "upward grade homogenization" (Wilson, 1999).

A thorough review of the relevant literature revealed that there are several definitions that have been offered for grade inflation (McSpirit, Kopacz, Jones, & Chapman, 2000). McKenzie and Staaf (1974) defined grade inflation as a continual increase in the awarding of the grades of A and B by the faculty with a corresponding decrease in the awarding of the grades of D and F, as indicated above. Burwen (1971) defined grade inflation as the increase in student grade point averages (GPAs) and Juola (1974) described it as the rise in grade points awarded. In a candid approach, Mullen (1995) defined grade inflation as "when a grade is viewed as being less rigorous than it ought to be" (p. 5).

Although these aforementioned definitions offered for grade inflation are certainly relevant, more robust definitions include the components of student aptitude and achievement (Scanlan & Care, 2004; Wissler, 1975). Carney, Isakson, and Ellsworth (1978) suggested that grade inflation exists when there is an increase in overall student GPAs without a noted increase in standardized college entrance exams such as the American College Test (ACT), Scholastic Aptitude Test (SAT), or other student aptitude scores. Goldman (1985) stated that grade inflation is defined as an upward shift in the GPA of students without a corresponding increase in student achievement. Zirkel (1999) defined grade inflation as "a rise in academic grades not accompanied by a commensurate increase in academic achievement" (p. 247). Grove and Wasserman (2004), along with Hadley and Vitale (1985), added a time component to the definition, stating that grade inflation is an upward shift in the GPA of college students over a period of time without a corresponding increase in student or academic ability.

METHODOLOGY

The data utilized for this study was obtained from the Baccalaureate and Beyond Longitudinal Study (B&B) series conducted by the National Center for Educational Statistics (NCES), a department of the U.S. Department of Education. The B&B series was a nationally representative sample consisting of more than 10,000 college graduates from approximately 648 institutions of higher education. Specifically, two time periods (1993 and 2000/01) were selected to serve as the populations for this study, representing two unique cohorts of college graduates. This data originated from two restricted data sets that contained the individual survey data. In order to acquire access to these restricted data sets for B&B:93 and B&B:2000/01, the authors successfully completed the application process for a license from the U.S. Department of Education that regulates the data's usage and ensures confidentiality. While the summary data and related reports of all B&B studies are available to the general public through print and an internet-based data analysis system (DAS), this public use data does not contain individual survey data that was essential to the analyses that were conducted within this study.

Research Population and Sample

The respondent population for the B&B:93 study consisted of all students who attended postsecondary institutions in the United States and Puerto Rico between July 1, 1992 and June 30, 1993 and received a baccalaureate degree during this time period. The number of undergraduate students enrolled during this study period and successfully receiving a baccalaureate degree was approximately 1.2 million. Within this population, 10,028 were selected by NCES for the sample group (Wine et al, 2005). Similarly, the respondent population for this B&B:2000/01 study consisted of all students who attended postsecondary institutions in the United States and Puerto Rico between July 1, 1999, and June 30, 2000 and also received or were expected to receive a baccalaureate degree during this time period. The number of undergraduate students enrolled during this study period and successfully receiving a baccalaureate degree was approximately 1.3 million. Within this population, 10,030 were selected by NCES for the sample group (Charleston et al, 2003).

Data Collection

Variable selection from the B&B data sets was performed using software and a related tool provided by the NCES. This software, an electronic codebook (ECB), allowed the researchers to choose the necessary variables and related data and use Statistical Package for Social Sciences (SPSS) coding to conduct the appropriate statistical analyses. Variables chosen from each B&B data set included cumulative GPA and within major GPA for each college graduate participating in the survey. Also, two new variables were created by this study's authors to measure the level of grade inflation for cumulative and within major GPA using these existing variables from B&B.

RESEARCH FINDINGS AND ANALYSES

The results of this study are presented in three parts. First, a set of chi-square analyses were conducted to control for any significant differences in the demographic characteristics and distribution of the twelve major fields of study between the two B&B time periods. Second, two separate independent samples t-tests were conducted for cumulative and major GPA scores to confirm the existence of grade inflation between the two B&B time periods. Finally, one way analysis of variance (ANOVA) procedures were conducted among the twelve fields of study to display any significant differences in grade inflation that occurred from 1993 to 2000.

Differences in Samples

Changing demographic characteristics of college graduates have been cited as a contributing factor for an increase in GPA over time. For this reason, the following four variables were tested for significant variations across the two time periods chosen for this study: gender, age, race, and the highest educational level of the graduate's parents. A chi square analysis revealed none of the four student characteristic variables experienced significant changes between the B&B:93 and B&B:2000/01 studies. Therefore, a change in graduate's demographic characteristics between time periods can be excluded as an explanatory variable for the level of grade inflation. Results of this analysis are displayed in Table 1.

Following the definition of grade inflation offered by Hadley and Vitale (1985), along with Grove and Wasserman (2004), it was necessary to test for increasing academic achievement between 1993 and 2000. A significant increase would suggest that an increase in college graduate's academic ability could be used to explain the increase in student GPA while a nonsignificant test would rule out increased academic ability as an explanatory variable for grade inflation. A variable from B&B for standardized college entrance examination scores was used as a proxy for academic ability. This variable was a combined variable generated from the college entrance scores from American College Testing (ACT) and the Scholastic Aptitude Test (SAT). Testing with chi square revealed that no significant changes occurred in academic achievement that might explain grade inflation between periods. Results of this analysis are displayed in Table 2.

Finally, a chi-square analysis was used to determine if the proportion of fields of study of graduates from the B&B:2000/01 cohort differed from B&B:93 graduates. No significant difference was found which would indicate that the twelve fields of study are evenly distributed by year of graduation. This even distribution effectively eliminated the changing of the percentage of majors in any specific field as a valid explanatory variable for grade inflation. Results of this analysis are displayed in Table 3.

Testing of Grade Inflation Between Time Periods

To assess the grade inflation that occurred between study periods, two separate independent samples t-test procedures were conducted, one that tested cumulative GPA and one that tested the major GPA earned by college graduates participating in the study. Conducting separate tests for cumulative and major GPA was necessary to display any trends within GPA that might occur between a graduate's overall coursework and only coursework within his or her academic field of study.

Testing of Grade Inflation--Cumulative GPA

An independent-samples t-test was conducted to compare the mean cumulative GPAs earned from college graduates sampled by the 1993 B&B study and college graduates sampled by the 2000/01 B&B study. The t-test was found to be significant, t (20,042) = 37.36, p < .01. College graduates from the 2000/01 B&B study (M = 3.20, SD = 0.47) on the average achieved a higher cumulative GPA than those college graduates surveyed for the 1993 B&B study (M = 2.97, SD = 0.40). The 95% confidence intervals were 3.19 and 3.21 for the 2000 college graduates; intervals for 1993 college graduates were 2.97 and 2.99. A summary of the results are presented in Table 4.

Due to the significance of the t value, effect size was computed. The eta square ([[eta].sup.2]) index was computed to illustrate the proportion of the variance of the test variable (cumulative GPA) that is a function of the grouping variable (year of B&B Study). An [[eta].sup.2] value of .065 indicated that 6.5% of the variance of major GPA was explained by whether the student received his or her college degree in 1993 or 2000. While the measurement of [[eta].sup.2] is dependent upon the area of investigation, Green and Salkind (2000) indicated that this size index is interpreted as a medium effect size. Figure 1 displays the graphical distributions of means and standard deviations represented by error bars for cumulative GPA for the two B&B time periods.

The level of grade inflation that occurred in the approximately seven-year elapsed time period between the administration of the B&B:93 and the B&B:2000/01 was measured as the difference between cumulative GPA scores earned by college graduates of each respective time period. The difference of 0.23 grade points within cumulative GPA was found to represent significant grade inflation.

[FIGURE 1 OMITTED]

Testing of Grade Inflation--Major GPA

An independent-samples t-test was conducted to compare the mean, major GPAs earned from college graduates sampled by the 1993 and 2000/01 B&B Studies. The test was significant, t (20,042) = 32.68, p < .01. College graduates from the 2000/01 B&B study (M = 3.33, SD = 0.47) on the average achieved a higher within-major GPA than those college graduates surveyed for the 1993 B&B study (M = 3.12, SD = 0.42). The 95% confidence intervals were 3.32 and 3.34 for the 2000 college graduates; the intervals for 1993 graduates were 3.11 and 3.13. A summary of the results are presented in Table 5.

Because the t value in this case was significant, it was appropriate to discuss effect size (Dewberry, 2004). For a significant difference in means, the appropriate measure of effect size is represented as d. To obtain d, the difference in the two means was divided by the pooled standard deviation. In this case, d = 0.47, representing a medium effect size (Cohen, 1988).

The eta square ([[eta].sup.2]) index was computed to illustrate the proportion of the variance of the test variable (major GPA) that is a function of the grouping variable (year of B&B Study). An [[eta].sup.2] value of .051 indicated that 5.1% of the variance of major GPA was explained by whether the student received his or her college degree in 1993 or 2000. While the measurement of [[eta].sup.2] is dependent upon the area of investigation, Green and Salkind (2000) indicate that this size index is interpreted as a medium effect size. Figure 2 displays the graphical distributions of means and standard deviations by error bars for major GPA for the two B&B time periods.

The level of grade inflation that occurred in the approximately seven-year elapsed time period between the administration of the B&B:93 and the B&B:2000/01 was measured as the difference between major GPA scores earned by college graduates of each respective time period. The difference of 0.21 grade points within major GPA was found to represent significant grade inflation.

[FIGURE 2 OMITTED]

Testing of Grade Divergence Among Fields of Study

To adequately assess the level grade inflation that occurred among fields of study, two separate ANOVA procedures were conducted, one that tested cumulative GPA and one that tested the major GPA earned by college graduates participating in the study. As indicated earlier, conducting separate tests for cumulative and major GPA was necessary to display any trends within GPA that might occur between a graduate's overall coursework and only coursework within his or her academic field of study.

Analysis of Grade Divergence--Cumulative GPA

A one-way analysis of variance (ANOVA) was conducted to compare the mean levels of grade inflation within the cumulative GPA among the twelve academic major fields collected for this study. The ANOVA showed that there is a significant difference of grade inflation within cumulative GPA across twelve academic majors F(11, 10010) = 25.263, p < .01.

Within the twelve fields of study selected for this analysis, mathematics (M = 0.31) and physical sciences (M = 0.30) experienced the greatest level of grade inflation within the cumulative GPA of college graduates. Following, in order of descending order of grade inflation experienced, were health (M = 0.26), engineering (M = 0.25), humanities (M = 0.23), business (M = 0.22), computer/information systems (M = 0.22), education (M = 0.22), and social sciences (M = 0.21). The lowest level of grade inflation was experienced by graduates in professional (M = 0.20) and technological (M = 0.19) fields of study. Descriptive statistics (means and standard deviations) for each field of study are presented in Table 6. Additionally, a graphical plot of the means by academic field of study is presented in Figure 3.

[FIGURE 3 OMITTED]

Because the samples from the 1993 and the 2000/01 B&B Studies are drawn from populations with heterogeneous variances, Dunnett's T3 follow-up tests were used to examine the differences among cumulative GPAs in specific pairs of academic fields of study (Dewberry, 2004). Thirty-four statistically significant pairwise differences were found between major fields of study. Because the focus of this study's analysis was primarily on the comparison of the business fields of study to the other eleven fields, only the five significant combinations of cumulative GPA from business are presented in Table 7.

Analysis of Grade Divergence--Major GPA

A one-way analysis of variance (ANOVA) was conducted to compare the mean levels of grade inflation among the twelve academic major fields of study collected for this study. The ANOVA showed that there is a significant difference among the level of grade inflation within major GPA across twelve academic fields of study F(11,10010) = 20.929, p < .01.

Within the twelve fields of study selected for this analysis, technology (M = 0.25), education (M = 0.23), and professional (M = 0.23) experienced the greatest level of grade inflation within the major GPA of college graduates. Following, in order of descending order of grade inflation experienced, were social sciences (M = 0.22), computer/information systems (M = 0.21), humanities (M = 0.21), business (M = 0.20), health (M = 0.19), and life sciences (M = 0.15). The lowest level of grade inflation was experienced by graduates in physical sciences (M = 0.14) and mathematics (M = 0.13) fields of study. Descriptive statistics (mean and standard deviation) for each field of study are presented in Table 8. Also, a graphical plot of the grade inflation means by academic field of study is presented in Figure 4.

[FIGURE 4 OMITTED]

Because the samples from the 1993 and the 2000/01 B&B Studies were drawn from populations with heterogeneous variances, Dunnett's T3 follow-up tests were used to examine the differences among major GPAs in specific pairs of academic fields of study (Dewberry, 2004). Thirty-six statistically significant pairwise differences were found between major fields of study. Because the focus of this study's analysis was primarily on the comparison of the business fields of study to the other eleven fields, only the six pairwise differences in major GPA from business are presented in Table 10.

FUTURE RESEARCH

Future statistical analyses should be conducted on data collected for individual majors of recent college graduates. For this study, grade point averages were presented for twelve academic fields of study and not individual majors. Data collection for the 2000/01 Baccalaureate and Beyond Longitudinal study was classified for 99 individual majors but research scope limitations did not allow each to be presented in this study. A future researcher could use individual major data to obtain a more detailed analysis within the twelve general fields of study. For example, a researcher interested specifically in business disciplines could conduct analyses for individual majors such as management, marketing, finance, and economics for a more detailed analysis of grade inflation within major fields.

While not included within the limitations of this research study, NCES collected a variable for the B&B Studies that provides the Carnegie classification of the institution conferring an undergraduate degree. A future study using this Carnegie variable would provide a more detailed analysis of how grade inflation varies by classification and institution type. For example, there is interest in how higher education institutions classified as research intensive would compare with regional, comprehensive institutions.

CONCLUSION

While certainly not a new topic in higher education, grade inflation continues to pervade the editorial and scholarly literature. Many authors have relegated their opinions toward this topic to the simple acknowledgement that it indeed exists and no further analysis is necessary. However, authors like Freeman (1999) point out that the study of grade divergence across various academic disciplines is a recent research perspective of grade inflation. Generally speaking, how do specific fields of study such as business rank in comparison to other fields?

Based on our study, we concluded that the GPA of college graduates increased significantly from the college graduate cohort participating in the B&B:93 Longitudinal Study to the B&B:2000/01 cohort. More specifically, cumulative and major GPA increased 0.23 and 0.21 grade points, respectively, over the interim between these two data collection periods. Controlling for changing demographic characteristics of these graduates and the distribution of field of study, these increases can be viewed as grade inflation.

The results of cumulative grade inflation experienced between the 1993 and 2000/01 B&B Longitudinal Studies were similar to those reported by Kolevzon (1981), Mullen (1995), and somewhat less than Juola (1977). Kolevzon's study analyzed 20 academic departments within a single institution of higher education over a period of seven years between 1969 and 1976. The amount of grade inflation during the period of this study was 0.30, or somewhat less than one-third of a full grade point. Mullen's six-year study yielded a grade inflation of 0.19 grade points from 1987 to 1992. Additionally, Juola (1977) discovered a somewhat higher level of grade inflation in a study of 134 colleges. This level of grade inflation was found to be 0.40 grade points.

The results of grade inflation of major GPA experienced between the 1993 and 2000/01 B&B Studies were similar to those reported by Kuh and Hu (1999). This nationwide study of college graduates was conducted over a ten-year period from 1985 to 1995 and resulted in grade inflation in the major GPA of 0.27 grade points, or somewhat more than one-fourth of a full grade point over the study period.

The findings of this study lend validity to the theory of grade compression offered by Kamber and Biggs (2004). Under the grade compression assumption, grades can only rise to a certain level and cannot inflate perpetually because the highest GPA remains a 4.0. This is in contrast to currency inflation, which theoretically contains no ceiling and can rise infinitely. Summerville, Ridley, and Maris (1990) state that fields of study such as business, mathematics, and physical sciences are considered "low grading" departments and experience little or no grade inflation while fields of study such as education or humanities are considered "high grading" fields of study. While the time period of this current research study (1993-2000) are different from the one by Summerville, Ridley, and Maris (1990), the field of business and mathematics experienced higher levels of grade inflation than other traditional "high grading" fields. It is quite possible that grade inflation in fields such as education are leveling off while fields such as business are playing "catch-up."

While this examination of grade inflation and its subset of grade divergence does not offer a panacea, the trends that emerged were intriguing. This study will hopefully serve as a guide to stimulate future interest and further research in the increase of college graduate's educational achievement, specifically within the business disciplines.

REFERENCES

Agnew, E. (1995). Rigorous grading standards does not raise standards: It only lowers grades. Assessing Writing, 2(1), 91-103.

Basinger, D. (1997). Fighting grade inflation: A misguided effort? College Teaching, 45(3), 88-91.

Becker, W. E. (1997, September). Teaching economics to undergraduates. Journal of Economic Literature, 35, 1347-73.

Betts, J. R. (1995). Does school quality matter? Evidence from the National Longitudinal Survey of Youth. Review of Economics and Statistics, 77(2), 231-50.

Birk, L. (2000). Grade inflation: What's really behind all those A's? Harvard Education Letter, 16(1), 3-5.

Burwen, L. S. (1971). National grading survey. San Francisco: San Francisco State University, Office of Institutional Research.

Carney, P., Isakson, R. L., & Ellsworth, R. (1978). An exploration of grade inflation and some related factors in higher education. College and University, 53(2), 217-230.

Caulkins, J. P., Larkey, P. D., & Wei, J. (1996). Adjusting GPA to reflect course difficulty (1996-4). Pittsburgh, PA:

Carnegie Mellon University, The Heinz School of Public Policy and Management.

Charleston, S., Riccobono, J., Mosquin, P., & Link, M. (2003). Baccalaureate and beyond longitudinal study: 2000/2001 methodology report, NCES 2003-156. U.S. Department of Education, National Center for Education Statistics: Washington, DC.

Cohen, J. (1988). Statistical power analysis for the behavioral sciences. New Jersey: Lawrence Erlbaum Associates.

Cross, L. H. & Frary, R. B. (1993). College grading. College Teaching, 41(4), 143-49.

Dewberry, C. (2004). Statistical methods for organizational research: Theory and practice. New York: Routledge.

Dickson, V. A. (1984). An economic model of faculty grading practices. Journal of Economic Education, 6, 197-203.

Elbow, P. H. (1969). More accurate evaluation of student performance. The Journal of Higher Education, 40(3), 219-30.

Feldman, K. A. (1976). Grades and college students, evaluations of their courses and teachers. Research in Higher Education, 4, 69-111.

Felton, J. & Koper, P. T. (2005). Real GPA and nominal GPA: A simple adjustment that compensates for grade inflation. Assessment and Evaluation in Higher Education, 30(6), 561-69.

Freeman, D. G. (1999). Grade divergence as a market outcome. Journal of Economic Education, 30(4), 344-51.

Geisinger, K. (1980). Who are giving all those A's? Journal of Teacher Education, 31(2), 11-15.

Goldman, R. D. & Hewitt, B. N. (1975). Adaptation level as an explanation for differential standards in college grading. Journal of Educational Measurement, 12(3), 149-61.

Goldman, R. D., Schmidt, D. E., Hewitt, B. N., & Fisher, R. (1974). Grading practices in different major fields. American Educational Research Journal, 11(4), 343-57.

Green, S. B. & Salkind, N. J. (2000). Using SPSS for windows and macintosh: Analyzing and understanding data. New Jersey: Pearson Education.

Grove, W. A. & Wasserman, T. (2004). The life-cycle pattern of collegiate GPA: Longitudinal cohort analysis and grade inflation. Journal of Economic Education, 35(2), 162-74.

Haagen, C. H. (1964). The origins of a grade. The Journal of Higher Education, 35(2), 89-91.

Hadley, M. & Vitale, P. (1985). Evaluating student achievement. (ERIC Document Reproduction Service No. ED 285 878)

Haskell, R. E. (1997). Academic freedom, promotion, reappointment, tenure and the administrative use of student evaluation of faculty (SEF): Analysis and implications of views from the court in relation to academic freedom, standards, and quality instruction. Education Policy Analysis Archives, 5(21).

Iyasere, M. (1984). Setting standards in multiple-section courses. Improving College and University Teaching, 32, 173-79.

Johnson, V. E. (1997). An alternative to traditional GPA for evaluating student performance. Statistical Science, 12(4), 251-69.

Juola, A. E. (1974). Grade inflation (1960-1973), a preliminary report. East Lansing: Michigan State University, Office of Education Services.

Kamber, R. & Biggs, M. (2004). Grade inflation: Metaphor and reality. Journal of Education, 184(1), 31-38.

Kolevzon, M. S. (1981). Grade inflation in higher education: A comparative study. Research in Higher Education, 15(3), 195-212.

Kuh, G. & Hu, S. (1999). Unraveling the complexity of the increase in college grades from the mid-1980s to the mid-1990s, Educational Evaluation and Policy Analysis, 21(3), 297-320.

Landrum, R. E. (1999). Student expectations of grade inflation. Journal of Research and Development in Education, 32(2), 124-128.

Levine, A. & Cureton, J. S. (1998). When hope and fear collide: A portrait of today's college student. San Francisco: Jossey-Bass.

Mannello, G. (1964). College teaching without grades: Are conventional marking practices a deterrent to learning? The Journal of Higher Education, 35(6), 328-34.

McKenzie, R. B. & Staaf, R. J. (1974). An economic theory of learning: Student sovereignty and academic freedom. Blacksburg, VA: University Publications.

McSpirit, S., Kopacz, P., Jones, K., & Chapman, A. (2000, Winter). Faculty opinion grade inflation: Contradictions about its cause. College & University Journal, 19-25.

Moore, M. & Trahan, R. (1998). Tenure status and grading practices. Sociological Perspectives, 41(4), 775-82.

Mortenson, T. G. (1997, February). Georgia's HOPE scholarship program: Good intentions, strong funding, bad design. Postsecondary Education Opportunity Newsletter, 56.

Mullen, R. (1995). AIR 1995 Annual Forum Paper. (ERIC Document Reproduction Service No. ED 386 970)

Murray, C. & Wren, C. T. (2003). Cognitive, academic, and attitudinal predictors of the grade point averages of college students with learning disabilities. Journal of Learning Disabilities, 36(5), 407-15.

Nagle, B. (1998). A proposal for dealing with grade inflation: The relative performance index. Journal of Education for Business, 74(1), 40-43.

O'Connor, D. (1979). A solution to grade inflation. Educational Record, 60(2), 295-300.

Pope, N. & Ma, Y. (2004). Grade-risk: An insurable event in the classroom. Risk Management and Insurance Review, 7(2), 189-95.

Riley, H. J., Checca, R. C., Singer, T. S., & Worthington, D. F. (1994). Grades and grading practices: Results of the 1992 AACRAO study. American Association of Collegiate Registrars and Admission Officers, Annapolis Junction, MD: AACRAO Distribution Center.

Sabot, R. & Wakemann-Linn, J. (1991). Grade inflation and course choice. Journal of Economic Perspectives, 5(1), 159-70.

Scanlan, J. M. & Care, W. D. (2004). Grade inflation: Should we be concerned? Journal of Nursing Education, 43(10), 475-78.

Scott, R. C. (1988). A comment on "Grade Inflation: A Way Out." Journal of Economic Education, 19(3), 227-29.

Share, C. E. (1997). Implications of considering students as consumers. College Teaching, 45(4), 122-23.

Shea, C. (1994). Grade inflation's consequences. Chronicle of Higher Education, 40(18), A45-6.

White, R. A. (1997). An alternative to traditional GPA for evaluating student performance: Achievement index. Statistical Science, 12(4), 273-74.

Wilson, B. P. (1999). The phenomenon of grade inflation in higher education. National Forum, 79(4), 38-41.

Wine, J. S., Cominole, M.B., Wheeless, S., Dudley, K., & Franklin, J. (2005). 1993/03 baccalaureate and beyond longitudinal study methodology report (NCES 2006-166). U.S. Department of Education, Washington, DC: National Center for Education Statistics.

Wissler, E. J. (1975). An A is an A is an F, or is it? Engineering Education, 66(3), 232-37.

Wright, R. E. & Palmer, J. C. (1994). GMAT scores and undergraduate GPAs as predictors of performance in graduate business programs. Journal of Education for Business, 69(6), 344-49.

Zangenehzadeh, H. (1988). Grade inflation: A way out. Journal of Economic Education, 19(3), 217-26.

Zirkel, P.A. (1999). Grade inflation: A leadership opportunity for schools of education? Teachers College Record, 101(2), 247-60.

S. Keith Lowe, Jacksonville State University

Patricia C. Borstorff, Jacksonville State University

Robert J. Landry III, Jacksonville State University

Table 1: Frequency, Percentage Distribution, and Statistical
Significance of Student Characteristic Data From Respondents to the
1993 and 200/01 B&B Studies

 1993

 Category N %
Gender
 Male 4,340 43.3
 Female 5,682 56.7
Age
 21 years or less 2,601 26.0
 22 years 2,635 26.3
 23 to 25 years 2,419 24.1
 Over 25 years 2,367 23.6
Race
 Caucasian 9,221 92.0
 Non-Caucasian 801 8.0
Highest Educational Level of Parents
 High school diploma or less 3,632 36.2
 Associate degree 1,532 15.3
 Baccalaureate degree 2,481 24.8
 Master's degree 1,492 14.9
 Doctorate degree 885 8.8

 2000/01

 Category N % Significance
Gender
 Male 3,844 38.4 p = 0.67
 Female 6,178 61.6
Age
 21 years or less 2,654 26.5 p = 0.61
 22 years 2,507 25.0
 23 to 25 years 2,425 24.2
 Over 25 years 2,436 24.3
Race
 Caucasian 9,227 92.1 p = 0.74
 Non-Caucasian 795 7.9
Highest Educational Level of Parents
 High school diploma or less 3,142 31.4 p = 0.22
 Associate degree 2,044 20.4
 Baccalaureate degree 2,315 23.1
 Master's degree 1,611 16.1
 Doctorate degree 910 9.0

Table 2: Frequency, Percentage Distribution, and Statistical
Significance of Academic Achievement Data From Respondents to the 1993
and 200/01 B&B Studies

 1993 2000/01

 Category N % N % Significance

Combined
ACT/SAT Scores
 No exam taken 2,716 27.1 2,742 27.4 p = 0.14
 Below 1,000 2,541 25.4 2,536 25.3
 1,000-1,200 2,945 29.3 2,940 29.3
 Above 1,200 1,820 18.2 1,804 18.0

Table 3: Frequency and Percentage Distribution of Academic Field of
Study Data from Respondents to the 1993 & 2000/01 B&B Studies

 1993 2000

Field of Study N % N % Significance

Business 1,451 14.5 1,185 11.8 p = 0.81
Computer Science 251 2.5 347 3.5
Education 1,579 15.8 1,369 13.7
Engineering 676 6.8 508 5.1
Health 759 7.6 1,103 11.0
Humanities 1,288 12.9 1,398 13.9
Life Sciences 814 8.1 832 8.3
Mathematics 183 1.8 115 1.1
Physical Sciences 182 1.8 172 1.7
Professional 941 9.4 911 9.1
Social Sciences 1,638 16.3 1,854 18.5
Technology 260 2.6 228 2.3

Table 4: Means and Standard Deviations for t-test of Cumulative GPA of
College Graduates Participating in B&B:93 and B&B:2000/01 Studies

Year of B&B Study M SD

 1993 2.97 0.40
 2000/01 3.20 0.47

Table 5: Means and Standard Deviations for t-test of Major GPA of
College Graduates Participating in B&B:93 and B&B:2000/01Studies

Year of B&B Study M SD

 1993 3.12 0.42
 2000/01 3.33 0.47

Table 6: Frequencies, Means, and Standard Deviations of Grade
Inflation Within Cumulative Grade Point Average of Respondents to the
B&B:2000/01 Study

Major Field of Study N M SD

Business 1,185 0.22 0.19
Computer/Information Systems 347 0.22 0.19
Education 1,369 0.22 0.17
Engineering 508 0.25 0.18
Health 1,103 0.26 0.17
Humanities 1,398 0.23 0.20
Life Sciences 832 0.28 0.18
Mathematics 115 0.31 0.16
Physical Sciences 172 0.30 0.20
Professional 911 0.20 0.18
Social Sciences 1,854 0.21 0.19
Technology 228 0.19 0.20

Table 7: Statistically Significant Combinations Between Business
and Other Fields of Study--Grade Inflation of Cumulative GPA

Significant Combinations Significance Level

Business & Health p < .01
Business & Life Sciences p < .01
Business & Mathematics p < .01
Business & Physical Sciences p < .01
Business & Professional p < .05

Table 8: Frequencies, Means, and Standard Deviations of Grade
Inflation Within Major Grade Point Average of Respondents to the
B&B:2000/01 Study

Major Field of Study N M SD

Business 1,185 0.20 0.19
Computer/Information Systems 347 0.21 0.18
Education 1,369 0.23 0.17
Engineering 508 0.17 0.17
Health 1,103 0.19 0.17
Humanities 1,398 0.21 0.19
Life Sciences 832 0.15 0.19
Mathematics 115 0.13 0.17
Physical Sciences 172 0.14 0.21
Professional 911 0.23 0.18
Social Sciences 1,854 0.22 0.19
Technology 228 0.25 0.20

Table 10: Statistically Significant Combinations Between Business
and Other Fields of Study--Grade Inflation of Major GPA

Significant Combinations Significance Level

Business & Education p < .01
Business & Engineering p < .01
Business & Life Sciences p < .01
Business & Mathematics p < .01
Business & Physical Science p < .01
Business & Professional p < .05