While the total volume of people taking the GMAT over the last year fell marginally from the year before, and again from it’s all-time high in 2009, the percentage of those test-takers who were women or from racial minorities grew significantly in the 2010-2011 GMAT season.
Below are some of the most significant shifts in the test taking population from 2011:
The percentage of female test takers increased for the sixth consecutive year to 41%, which is up from 39% just two years earlier. The fastest growing group to mention in the GMAT pipeline is the under 24 year old population, which has exploded since 2007 – reflecting the push for those seeking post-graduate degrees to do so more quickly than in the past, mainly due to the abysmal job market.
These changes reflect the larger trend in higher education for an increasing amount of minority and international students to apply and be accepted to post-graduate programs across the globe.
Repeat Test Taking
Much of the conference hosted by the GMAC that we discussed earlier also focused on the extensive research that the GMAC has conducted on test takers, and how they score on the GMAT. The GMAC included 27,763 candidates in its comprehensive study. The retake rate is 18%.
Who retakes the GMAT?
- Candidates with lower than average Total scores
- Higher percent of non-native speakers of English
- About the same number of men as women
- Test takers that did not finished Quantitative section
- Test takers with a high discrepancy between Verbal and Quantitative scores
27.4% of retake candidates took their second exam between 31 and 60 days after their first test date while 20.4% of candidates retook within the first 30 days. Only 15% of students retake after 180 days from their first exam date.
The highest gains in score for retake candidates usually occur in the GMAT Quant percentile.
Who gains the most from retaking?
- High discrepancy score
- Below-average first scores
- Did not finish Quantitative section
- Young test takers who are 24 years and younger
- Native English speakers
In the fall of 2007, Manhattan Review was invited to attend an insightful and interactive conference hosted by the Graduate Management Admission Council (GMAC). After a busy season launching a spectrum of new products and services, we have taken some serious looks at the conference notes and materials along with various, in-depth reports published by the GMAC.
Mr. David Wilson, President and CEO of the GMAC, was the keynote speaker. Major issues that he addressed in his humorous, yet informative introduction included:
- GMAC works together with MBA programs in maintaining quality of business school education by upholding high testing standards
- The demographics of MBA applicants (and GMAT test-takers) are constantly changing. Some MBA programs are demanding more work experience from candidates. Some MBA programs are more active in recruiting college graduates with little experience
- Undergraduate students should think about taking the GMAT before they graduate. Test scores are valid for 5 years
Mr. Wilson also described recent expansion and plans at GMAC for further growth in Europe and Asia.
Before we continue on with detailed analysis of GMAT trends, we would like to share a few findings of ours based on what is published about Mr. Wilson’s impressive track record: A professor and a former partner at Ernest & Young, Mr. Wilson graduated from Queen’s University in Canada, received his MBA from the University of California (Berkeley), and Ph.D. from the University of Illinois. It is not surprising that the GMAC has grown by leaps and bounds (from 6 staff members in 1994 to 100+ staff members currently) under Mr. Wilson’s leadership, while making the MBA an internationally recognized high-value degree.
Study Time and GMAT Score
At the conference, GMAC senior managers shared some interesting data about the number of hours test takers study and their scores. The numbers provided by GMAC prove that as the number of hours a student prepares for the exam increases, the student’s self-reported GMAT score increases correspondingly. For example, students who reported that they spent 84 hours (equivalent to 8-9 weeks assuming an average weekly study time of about 10 hours) preparing for the GMAT on average scored in the 500-540 range. Students that studied 20 hours more (equivalent to 10-11 weeks with the same assumption earlier) scored 100 points more, scoring in the range between 600 and 640.
Similarly, results from GMAC show that the number of weeks of advanced preparation directly correlate to test takers’ scores. Test takers that study 10 weeks are 13 percent more likely to score over a 600 than students who study 1 to 3 weeks.
At the conference, the GMAC also released information collected from surveys of test takers. 29 percent of GMAT test takers spent 20 or less hours preparing for the exam. 24 percent of test takers prepared for 21 to 50 hours. In the next bracket, 24 percent of test takers spent 51 to 100 hours preparing. Another 24 percent studied 101 or more hours.
When asked how far in advance test takers began to study, 5 percent answered that they spent no time preparing. 9 percent started preparing less than one week before taking the test. 23 percent prepared 1 to 3 weeks in advance. 26 percent prepared 4 to 6 weeks in advance while 17 percent prepared 7 to 9 weeks. Finally, 21 percent prepared ten weeks or more.
Make the extra effort and go the extra mile – the rewards will definitely come your way! Hard work and determination are certainly good friends with luck.
We are here to provide cost-effective and time-effective preparation courses for all of you so that you can get a leg up over your peers, but nothing replaces your own self-study.
Computer-Adaptive Testing Algorithm
As mentioned in yesterday’s post, there are three main types of statistics required of all items in an item bank –
Computer adaptive testing (“CAT”) can begin when such an item bank exists. However, two more steps are required. First, the test-maker needs to select a procedure for determining test-takers’ ability estimates based upon their performance on the tested items. Second, the test-maker needs to choose an algorithm for sequencing the set of test items to be administered to test-takers.
An ideal item pool for a computer adaptive test would be one with a large number of highly discriminating items well distributed at each ability level. The information functions for these items would appear as a series of peaked distributions across all levels of ability estimate.
The CAT algorithm is usually an iterative process with the following steps:
We will continue with our analysis on the GMAT CAT scoring system tomorrow.
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