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CASE combines a multitude of data sources on academic achievement using modern econometric methods. This foundation is used to analyze the specific grade point average of individual graduates. We differentiate between the different publicly recognized universities and colleges, different degree types, and different fields of study: Over 30,000 combinations in 2015 alone. At this point CASE separates between 57 different study fields in Germany.
This data is used to generate the CASE Score in a two-step process: first, we compare the GPA of a degree with the distribution of GPAs in the graduate's program. In a second step, we combine this information with CASE-exclusive data about the performance profiles of students in the specific program. The optimization of the relative weighting of these factors is based, among other sources, on research exclusively run by CASE, using a total of more than 300,000 collected questionnaires.
The data that builds the basis of the CASE Algorithm is updated twice a year. This, as well as updates in the methods, may change the assessment of a candidate by CASE. The distributions are smoothed using a weighted moving average that includes a lag of up to three years. This smoothes out short-term fluctuations and aids analysis of future degrees. Degrees in different countries are evaluated using slightly different methods, but since results are generally presented in the format of "Top X%", these differences are not relevant for the interpretation of the results.
The individual GPA is shown in a figure that compares it to the GPAs that were earned by others in the candidate's program. The vertical axis indicates the probability of a specific grade. The horizontal axis shows the GPA, where 1.0 is the best and 4.0 is the lowest passing grade. Typically, GPAs between 2.0 and 3.0 are most common, therefore the highest point on the figure is often found in that range. The figure represents a probability density function that is based on the actual local grade distribution. To make the data continuous, a piece-wise cubic polynomial is used to interpolate between grade steps.
The position in this grade distribution ranks the degrees according to their relative performance in the respective study program. A degree obtained in a program with a strict grading standard would therefore typically score better than the absolute grade suggests. The relative grade is given as a top percentile. A GPA within the top 4% of the local grade distribution is therefore better than a GPA within the top 68%.
The CASE Subject Score allows for a comparison of degrees obtained in the same study field, but at different institutions. In addition to the grade distribution, it also considers information about the abilities and personality of students at the specific university into account. CASE uses its own data about intelligence and personality profiles of students at these universities. We enrich this data with additional information like the numerus clausus or the average high school GPA of students in the program.
The curve compares a degree to all other degree types earned at different universities in the same study field. The further to the right a degree is positioned, the better the assessment of that degree relative to others within that subject area. Results are shown as percentiles. A degree could for example be among the top 10% of all degrees earned in mechanical engineering in Germany.
The CASE Score enables the comparison of all applicants across different institutions, study fields, degree types and graduation years. The CASE algorithm is designed to factor all this information in and to produce a score that is as predictive as possible of a candidate's academic ability. For this the methods used for the CASE Subject Score is extended to all German higher education graduates. The resulting ranking allows the direct comparison of all your applicants.
The figure presents the degree's CASE Score relative to all German graduates, irrespective of their subject area. The curve is identical for all degrees that are being analyzed, only the relative position changes depending on the individual score. The interpretation of the figure is identical to the previous figures: Points to the left of the degree represent worse scores, points to the right represent better scores. The curve itself is based on roughly four million data points, which are graphically represented using a kernel density function.
CASE Scores and CASE Subject Scores for degrees from institutions located in the United Kingdom, in Italy, Portugal or in Spain are to be interpreted just like scores for German degrees. Because of differences in the education systems and the availabilty of research data the methods to generate the scores has been partly adapted. Nonetheless, the core of the methods is identical across countries. Just like in Germany, scores are based on the combination of program-specific grade distributions and an analysis of the competitiveness of the students in these programs. The defintion of subject areas, however, can differ. There are also differences in the availability of data in different countries. Particular years or degree types might be available for one country, but not for another.
A notable difference is that we are sometimes for legal reasons not able to present explicit distributions of the GPAs of students. This information is, however, always part of the calculation of CASE Sores and CASE Subject Scores.
In the case of British post-graduate degrees we have adapted our numbers for the fact that British universities often do not report explicit GPAs. In order to reflect the lower precision stemming from this, we show a range of scores rather than a single CASE Score or CASE Subject Score.
For India we only offer the analysis of degrees from engineering colleges. While we cannot offer an analysis of a students position within the local grade distribution, we do take the grade into account when calculating CASE Subject Scores and CASE Scores. For this purpose we use a standardized grade distribution. Generally speaking, our comparisons for India are primarily based on the admission requirements for different study programs.