Appendix 11: Collection of the Transcript Data

To complement data on respondents' educational experiences collected during the yearly interviews, NLSY97 staff collected transcripts directly from respondents' high schools once the youths graduated or left school. Once the transcripts were received from the schools, survey staff coded the transcript record into a standard format. The resulting created variables comprise a history of the respondent's terms in school, courses taken, and other academic indicators. This appendix describes the survey materials used during data collection and explains the procedures and criteria for data entry and coding. It also lists specific details about individual Transcript Survey variables.

• Transcript Survey Data Collection

• Creation of the Transcript Data File

• Notes on Transcript Survey Variables

• Coding Information for Course Code Variables

• NLSY97 Transcript Survey Carnegie Unit Equivalent Credits

Return to Table of Contents

Transcript Survey Data Collection

Conducted in 1999-2000, Wave 1of the NLSY97 Transcript Survey sought hard copy transcripts from 1,622 NLSY97 respondents who had provided signed authorization for transcript collection, and who were no longer enrolled in high school in spring 2000. Non-enrollment occurred when the youth either graduated from high school or dropped out of school and was at least 18 years old. From Wave I, coded transcript data are available for 1,417 respondents.

To complete the Transcript Survey effort, a second and final wave of the NLSY97 Transcript Survey requested hard copy transcripts from 5,701 eligible NLSY97 respondents. Youth respondents eligible for the Wave 2 Transcript Survey had a signed Permission to Contact School form on file, a known high school reported during a previous interview, and did not have a transcript collected during Wave I. The vast majority of NLSY97 respondents finished their high school careers by the end of the 2004 academic year, resulting in complete transcript records submitted from the schools. Transcript data was collected and coded for 4,815 respondents during Wave 2. Transcript data combined from both waves are available for 6,232 respondents.

NORC mailed a transcript request packet to each school from which an NLSY97 youth received his or her high school diploma, or to the last school the youth reported attending in the Youth interview. The packet contained informational materials about the NLSY97 and a pamphlet describing the NLSY97 Transcript Survey. In addition, packets included the following items:

1. a cover letter addressed to the school principal

2. a one-page cover sheet questionnaire collecting school-specific grading and transcript policies

3. a Student Request list identifying the sampled students in the school

4. the signed permission forms for these students

These documents are available in PDF form at the link below:

Collection of the Transcript Data, Wave 1 - example documents
Collection of the Transcript Data, Wave 2 - example documents

(To download Acrobat Reader for free, see the Adobe website: http://www.adobe.com/. For a hard copy version of this document, users should contact NLS User Services: phone: (614) 442-7366 or e-mail: usersvc@postoffice.chrr.ohio-state.edu )

Return to top

Creation of the Transcript Data File

Organization of the data. There are several different types of variables in the transcript data file. First, at the school level the variable TRANS_SCH_CAT reports whether a course catalog was received from the school to aid in coding. The highest number of schools reported for any respondent is 12, so this variable is repeated 12 times. This course catalog variable also functions as the identification number of the school. During the data entry process described below, each school attended by a respondent was assigned a unique sequence ID number between 1 and 12, with the school that provided the transcript always listed as school #01. These numbers were used in variables that report which school the respondent attended in each term-for example, if a respondent has a value of 4 for term 1, then he or she attended school #04 in the course catalog variables. This school ID number does not link to any variables in the main data file.

Second, the transcript file includes information about the respondents that is not associated with a specific term or course. For example, these variables present test scores on a variety of achievement tests (ACT, PSAT, SAT, SAT II, AP), information on absences and tardies, the student's school completion status, and dates of enrollment. Variables also indicate whether the respondent participated in programs such as gifted, bilingual, or special education.

A number of variables refer to the respondent's terms of enrollment. For up to 28 terms, these items report the beginning and ending dates of the term, the way in which the school year is divided (such as a season, entire year, or another term based system), the academic year of the term, the respondent's grade level that term, and the number of credits earned. A variable listing the school the respondent attended during that term can be linked to the course catalog variable as described above.

Finally, the transcript file provides details about each course appearing on a student's high school transcript. Course-specific variables include the course code from the Revised Secondary School Taxonomy (SST-R), the grade earned in the course, and the credit value of the course. Because schools use many different grading systems, the course grades were converted into a standard scale that can be compared across respondents. A series of variables called "Recoding Status of Grade" indicates how the grade earned variable for each course was created. This process is described in more detail below.

Data entry and processing procedures. The transcript data capture process involved several distinct data entry steps, tailored to the structure of the data, the cleaning and reconciliation needs for the relevant variables, and scheduling requirements of the data collection process. The basic data entry and processing steps utilized during Wave 1 were:

1. Entry of course-level data into an Access data capture system from high school transcripts
2. Coding of entered course-level data using Access coding system
3. Entry of student-level data from Student Request List and high school transcripts into NORC's SurveyCraft Computer-Assisted Data Entry (CADE) system
4. Entry and coding of transfer school information from Student Request List, high school transcripts, and NLSY97 youth interview data using Access and SAS programs
5. Entry of school-level data from one-page Transcript Cover Sheet into SurveyCraft CADE system
6. Assigning course grades to a uniform grade scale using SAS transformations.

Each data entry and processing step is described in greater detail below. Enhancements to transcript processing developed specifically for the Wave 2 effort are noted following each section.

Wave 2 data entry and processing enhancements. Building on the Wave 1 model, the transcript data entry and processing steps were revised, improving the efficiency of the process and enhancing the quality of the data. The revised process included adding an edit and retrieval task at the beginning, streamlining the data entry instruments for a one-time, comprehensive entry task, utilizing an improved coding system separate from the data entry instrument, and building an auto-coding program.

Wave 2 transcript editing process. Due to the wide variation in the layout of high school transcript records, an editing and review task was implemented prior to data entry. Editing provided the first level of standardization of each transcript in preparation for data entry and also allowed clerks to identify problematic transcripts requiring a retrieval contact with the school. Editor staff identified key student level data elements, counted the number of transfer schools reported and sequenced term and course data as it appeared on the transcript. Editors highlighted terms and dates on the transcript, which created a series of reference points to maintain the sequence of courses and terms during data entry. Editor staff also reviewed the transcript for problematic or missing course and term data. If a potential data entry or coding problem existed, a retrieval form was completed and reviewed by a supervisor to determine whether a call to the school was necessary for further clarification.

Wave 1 course-level data entry. Course-level data include the course title, course number (assigned by school), grade earned, credits earned, and honors designation. For matching purposes, the school ID was assigned and term dates were captured during this phase of data entry. Entry was performed using an MSAccess data-capture system. All courses were independently entered twice. Where entry and re-entry matched perfectly, no further quality control was performed. If one or more discrepancies were found electronically between the entry and re-entry, a supervisor adjudicated the two data-entered versions with the original hard copy transcript to determine the accurate values. Courses were entered in the order that they appeared on the transcript. This order varied from school to school, with systems including chronologically, alphabetically by course title, numerically by course number, etc.

Wave 1 data entry of student-specific data down to the term level. All other student-specific data were captured in a SurveyCraft instrument for computer-assisted data entry. These variables include the student's enrollment in gifted, special education, or bilingual programs, standardized test scores, dates of enrollment at the school, class rank and cumulative grade-point average, term-level information on beginning and ending dates of terms, absences and tardies, and credits earned by term. The SurveyCraft program generated a single record for each youth, containing up to 18 terms of study. Term date information was used to match term-level data with the school attended during that term. All transcripts from a school were data entered at the same time to exploit clerk familiarity with transcript formats and school-specific abbreviations. All transcripts were independently entered twice. Where entry and re-entry matched perfectly, no further quality control was performed. If one or more discrepancies were found electronically between the entry and re-entry, a supervisor adjudicated the two data-entered versions with the original hard copy transcript to determine the accurate values. Terms were entered in chronological order when such sequence could be determined.

Wave 2 data entry system. A more comprehensive SurveyCraft computer-assisted data entry system was constructed for the Wave 2 data processing effort. The updated instrument allowed clerks to key all contents of the transcript at one time, capturing student, school, term and course level data in a series of loops. The editing process allowed a standard transcript sequence to be followed during data entry. Course and term data were reported in a chronological sequence whenever possible. The consolidated CADE system eliminated the need to match course level and term level data from two different systems, allowed data entry to sequence terms in chronological order by school for each youth record, and added another level of quality control through double entry and adjudication of both the data entry and coded items. The same rules for adjudication used during Wave 1 data entry were also applied.

Wave 1 course coding. Course-level data were used for coding courses into the Revised Secondary School Taxonomy (SST-R), a hierarchical framework for high school course offerings. After all course-level data from a transcript had been entered, re-entered, and adjudicated, the transcript was available for course coding. To maximize coder familiarity with school naming and catalog conventions, all transcripts from a school were usually coded together. Coding of all courses was done independently by two coders. If the two codes were not equal, a supervisor adjudicated the discrepancy and assigned a final code. Because many schools did not submit course catalogs or had indecipherable course titles (e.g., Course 1), clerks called some schools directly for assistance in coding, speaking to administrative or instructional staff who were able to clarify course content. The coding process used a menu-driven MSAccess system, which exploited the hierarchical structure of the code frame and prevented coders from inadvertently entering invalid codes. All 'uncodable' courses were reviewed by the coding supervisor and project director where necessary.

Wave 2 course coding. The course coding process in Wave 2 utilized a similar menu driven MSAccess system. After transcript records were entered, re-entered and adjudicated, a flag was set in the data entry system. Flagged transcript records were extracted from the SurveyCraft data on a regular schedule and loaded by batches into the coding system. Within each batch, transcript records were grouped by school to allow clerks to maximize familiarity with school naming and catalog conventions. Along with course level data presented on the coding screen, key term level information, including dates, term season, and grade level were also presented, allowing the clerks to easily reference course titles in the transcript record and course catalog. Mirroring Wave I, each course was coded independently by two different coders, and any discrepancies between the two codes assigned were reviewed by a supervisor responsible for assigning the final code.

Wave 2 auto-coding program. Using course description and coding matches from the Wave 1 coding effort, a list of course descriptions with codes assigned was developed for an auto-coding program. This matching program was run before courses were loaded into the MSAccess coding system. Approximately 25% of all courses coded were completed by the auto-coding program. Project staff reviewed all auto-coded course descriptions and codes assigned for consistency and flagged any discrepancies for manual coding.

Transfer data. Transcripts often included information about courses attended at other institutions. These data could appear either as an original hard copy attachment to the sampled school's transcript or as additional lines on the sampled school's transcript. These terms and courses were data entered during the appropriate stage of data entry, with a designation that the term or course pertained to a transfer school. Course and term-specific information about transferred work was generally complete, but information about the school from which work was transferred was often inadequate for coding purposes. As described above, all terms attended at the same school are associated with the same school ID.

Wave 2 transfer data and sequence of schools and terms. Building on lessons learned during the Wave 1 transcript processing, special effort was made to preserve a chronological sequence within the transcript for course, term and school data reported. The sequence established during the edit and data entry processes was used to order the terms chronologically. When preparing the term level data, the term year and season were used to confirm the sequence. For a small group of cases, the term sequence was difficult to assign when the transcript record indicated attendance at one or more institutions during similar term years. In these instances, attempts to sequence terms were based on the time period reported on the hard copy transcript whenever possible.

School 01 is always associated with the primary school or the school submitting the transcript. For the Wave 2 data, transfer schools are numbered in reverse chronological order as they appear on the transcript, often beginning with the most recent transfer school event moving in reverse order to the earliest transfer school event. In most instances, the school first attended by the student on the transcript will have the highest school number in the SCH_CAT.xx series.

Missing course catalogs and the Internet. For Wave 2 processing, if a series of transfer schools was present for a student, the SCH_CAT.xx variable was set to "no" indicating the catalog was not received. While a catalog for that school may have been received during the data collection period, it may not have been accessible to coding staff during the course of the transcript data collection. When available, online course catalogs were useful in clarifying particular types of coursework reported at a given school and were utilized by supervisors during the adjudication process.

Coursework reported below grade 9. Most transcripts entered and coded span a typical high school career from grades 9 or 10 through 12. For some districts and states, the transcript record includes middle school or junior high coursework, usually taken during grades 7 and 8. Other high school transcripts also record equivalency or classroom coursework eligible for high school credit that was earned while the student was in grade 8 or below. While no effort was made to collect middle school or junior high level coursework for the NLSY97 Transcript Survey, courses taken at these grade levels were coded and have been made available when provided as part of the hard copy transcript record.

School data. The one-page Transcript Cover Sheet provided information for assigning course grades to a uniform grade scale. During Wave 1 transcript processing, these data were entered into a SurveyCraft data capture instrument, once for each school submitting valid transcripts. Ten percent of schools were re-entered, and a supervisor referred to the original hard-copy to adjudicate discrepancies.

Wave 2 Transcript Cover Sheet procedures: Since a small percentage of schools during the Wave 1 effort reported unique grading scales, a data entry system was not built for Wave 2. Rather, the grade scale data were captured by a data processing clerk inside a spreadsheet containing high and low equivalents for each letter grade. An entry was made for each school submitting valid transcripts and a completed Transcript Cover Sheet. A supervisor reviewed the contents of the spreadsheet to ensure accuracy. When discrepancies reported on the Transcript Cover Sheet were discovered, the school was contacted as part of the retrieval process for clarification. The final grade scale spreadsheet was used in the standardized course grade procedures noted below.

Course grades. High school transcripts included a variety of systems for course grades, including letter grades or numbers. For ease of comparison, these were standardized into a uniform grading system. The standardized grading scale for the resulting CRS_GRADE variable ranges from 01 to 20. Table 1 lists the corresponding letter grades for each of the CRS_GRADE values.

Table 1. Grading system for coded transcript variables

In addition to the standardized grade variable, survey staff created a variable for each course called CRS_GRADE_RECODE_STATUS. This variable provides information on how the CRS_GRADE variable was created from the information provided by the school. The values of the recoding status variable are listed in Table 2.

Table 2. Values for CRS_GRADE_RECODE_STATUS

Each standardized grade was assigned using one of the following four methods:

1. The transcript reported letter grades using the system in Table 1 above. All letter grades were directly assigned to the corresponding standardized grade in Table 1. Letters that could not be classified into one of the categories 1-19 were considered to be unrecodable and included in category 20. In the cases where the CRS_GRADE variable was recoded directly from the grade on the transcript, CRS_GRADE_RECODE_STATUS was assigned a value of 0.
2. The school used numeric grades and provided grading specifications on the one-page Transcript Cover Sheet. For these respondents, numeric grades were converted to standardized grades using the grading specifications provided by the school. For example, if the numeric grade fell within the range for an 'A' as specified by that particular school, it was assigned to category 02. Fewer than 5% of schools provided multiple grading specifications; in all cases, the primary specifications were used. Due to the possibility of transcription errors, numeric grades below 15 were considered to be unrecodable when the minimum passing grade was higher than 15. For all cases where the CRS_GRADE variable was recoded from the transcript using the school's own grading specifications, CRS_GRADE_RECODE_STATUS was assigned a value of 1.
3. The school used letter grades of a type different than those shown in Table 1. During Wave I, grades of 'G' were classified as 05, 'O' and 'E' as 02, and 'O+' and 'E+' as 01. CRS_GRADE_RECODE_STATUS was assigned a value of 2. During Wave 2 grade construction, a variation in the interpretation of the 'E' grade across schools was discovered. In these cases, school specific grade scales were consulted to properly classify "E' grades as 02, 13, 14, or 15. If the grades could not be recoded, then CRS_GRADE was assigned a value of 20 and CRS_GRADE_RECODE_STATUS was assigned to 3.
4. The school used numeric grades and did not provide grading specifications. The means of the upper and lower limits of the grading systems across all schools were used to construct the standard grading system shown in Table 3. If the school did not specify its grading specifications, numeric grades (and numeric grades with a qualifier attached) were recoded based on this standard system. For Wave 2, the means of the upper and lower limits of the grading schools were recalculated using the grading systems received from all Wave 2 schools, as a check in the possibility of fluctuation in school grading systems. A different set of limits was developed and can be found in Table 3 below.

Once again, to take into account the possibility of transcription errors, numeric grades below 15 were considered to be unrecodable. CRS_GRADE_RECODE_STATUS was assigned a value of 2 when recoding was done using the standard grade specifications. If the grades could not be recoded, then CRS_GRADE was given a value of 20 and CRS_GRADE_RECODE_STATUS was coded as 3.

Table 3. Standard numeric grading system

Return to top

Notes on Transcript Survey Variables

Transcript Survey variables can be found in the NLSY97 data set by browsing through the "transcript survey" area of interest or by searching for question names with the prefix TRANS_. This section provides supplemental notes not included in the codebook about individual transcript variables.

Table 4. Additional information about Transcript Survey variables

Return to top

Coding Information for Course Code Variables

As part of the NLSY97 Transcript Survey, project staff coded respondents' courses using the revised Secondary School Taxonomy of courses (SST-R). The SST-R codes use a combination of numbers and letters to create a unique identifier for each type and level of high school course content. Because the NLSY97 data base system requires that all data be in numeric form, it was necessary to convert the SST-R codes into numbers for use with the Transcript Survey data. The following table indicates the NLSY97 number assigned for each original SST-R code and course description. These codes were used in variables R97128.-R97251. (TRANS_CRS_CODE.01-.175) in the NLSY97 data set.

Table 5. Numeric Course Code, R-SST Codes and Code Descriptions

Return to top

NLSY97 Transcript Survey Carnegie Unit Equivalent Credits (CRS_CARNEGIE_CREDIT.xxx)

The NLSY97 High School Transcript variables include credits earned for completed coursework as reported by the school submitting the transcript. Because credit systems vary considerably across schools, researchers may find it useful to use a transformation into Carnegie credit units, which are comparable across schools. One Carnegie credit is defined as the credits earned for a class that meets every day for one period for an entire school year. An NLSY97 Transcript Survey respondent's primary school is the school submitting the transcript record for processing; for the majority of transcript records processed, this is the last high school attended reporting coursework for the student. The effort to standardize course credits is based on the number of school course credits equal to one Carnegie credit as reported at the primary school. A multiplier was identified at the school level and applied to all school-based credits, creating a standardized credit system.

Carnegie Credit Conversion Method

The conversion of school-based course credits into a standardized Carnegie unit was established through three distinct approaches at the primary school level:

1. Identify Carnegie unit equivalent credits directly reported by the school
2. Establish a Carnegie credit equivalent measure through credits earned for an entire year of English coursework, directly reported by the school.
3. If a school did not directly report the relationship between English coursework and credits earned for one school year, observe patterns of English Survey and other English credits earned over an entire school year within the transcript record.

A standardized Carnegie credit measure was created through observation of school credits earned for coursework routinely taken over a full school year. Review of the transcript survey data indicates that English coursework is most often repeated over a year for the student's entire high school career, allowing a close approximation of the number of school-based credits earned over one full school year. If a school could not provide a Carnegie credit equivalent measure for school credits, the school was asked to provide the number of school credits a student earns for completion of English coursework across an entire school year.

Standardized Carnegie Credits based on School Reports. Initial transcript requests at schools did not include a series of questions regarding Carnegie equivalent credits. While recontacting schools during the 2004 wave, specific effort was made to define school credits earned in terms of Carnegie credits. Data processing clerks also reviewed course catalog materials submitted and identified schools with Carnegie Unit conversions reported or English credits earned by school year. In total, approximately 90% (n = 5,583) of the student transcripts submitted by primary schools either reported Carnegie equivalent credits or provided the number of English credits earned over one school year. The school-based reports were used to create a multiplier directly applied to course credits noted below.

School Reported Carnegie Credit Equivalencies. When a school provided the number of school course credits equal to one Carnegie credit unit, a credit multiplier was built based on the ratio: X school-based credits = 1 Carnegie credit unit. This multiplier was associated with the primary school. For student records associated with the primary school, the multiplier was applied to each course credit and captured in the CRS_CARNEGIE_CREDIT.xxx variable. The recode flag was set to 1 in each instance (see Table 1).

Standardized Carnegie Credits Based on School Reported English Credits. If a school provided the number of school-based credits earned for one full school year's English coursework, a credit multiplier was built based on the ratio: X English Credits Earned for One School Year = 1 Carnegie credit unit. This comparison was built on the underlying assumption that the number of school-based credits earned for English coursework completed over one school year was equivalent to one Carnegie credit unit. The multiplier was associated with the primary school. For student records associated with the primary school, the multiplier was applied to each course credit and captured in the CRS_CARNEGIE_CREDIT.xxx variable. The recode flag was set to 2 in each instance (see Table 1).

Standardized Carnegie Credits Based on Transcript Observations. For the remaining 10% of student records, a standard Carnegie credit equivalent was constructed by observing credit patterns across schools within transcript records. Again, English coursework was targeted as such coursework was more likely to be repeated across school years and have similar curriculum. Course credit patterns were first observed in English Survey coursework (1_31E*). If a credit pattern could not be detected, the program was expanded to observe a pattern across all English coursework (1_3*).

Standardized Carnegie Credits Based on English Survey Credits within Transcripts. Programs were built to observe English Survey course credit patterns across school years (where course codes = 1_31E*). Course credits were summed across school years to create a multiplier based on the ratio (X English Survey credits for 1 school year = 1 Carnegie credit unit). The multiplier was associated with the primary school. For student records associated with the primary school, the multiplier was applied to each course credit and captured in the CRS_CARNEGIE_CREDIT.xxx variable. The recode flag was set to 3 in each instance (see Table 1).

Standardized Carnegie Credits Based on Other English Credits within Transcripts. Programs were built to observe English course credit patterns across school years (where course codes = 1_3*). Course credits were summed across school years to create a multiplier based on the ratio (X English credits for one school year = 1 Carnegie credit unit). The multiplier was associated with the primary school. For student records associated with the primary school, the multiplier was applied to each course credit and captured in the CRS_CARNEGIE_CREDIT.xxx variable. The recode flag was set to 4 in each instance (see Table 1).

Unclassifiable Credits. In few instances, a credit system across schools could not be observed from reviewing English coursework credits earned. Reasons for not classifying school-based credits into a Carnegie credit equivalency include: credits were not reported (i.e., "missing") at the course level, zero credits were earned for all courses reported, not enough credits were reported to establish a Carnegie multiplier, and credits reported varied enough to prevent a standardized multiplier across student records. In such instances, CRS_CARNEGIE_CREDIT.xxx was set to a missing value (-3) and the recode flag was set to 5 (see Table 1).

Table 1: Values for CRS_CARNEGIE_RECODE.xxx

Additional Notes regarding the Carnegie Credit Assignment

Quality control checks were developed to evaluate the procedures using school-based credits earned for one year of English coursework in calculating a standard Carnegie multiplier. The three standardized calculations using English course credits were tested on the schools with direct Carnegie credit conversions reported. In addition, staff reviewed the total number of Carnegie credits earned by student to determine if the Carnegie credits reported seem reasonable. A range of 16 - 24 Carnegie credits earned for academic coursework was benchmarked. While a large majority fall within this range of credits, there are still outliers. Some reasons for these outliers are noted below.

Primary Schools and Credits Earned at Other/"Transfer" Schools. One key assumption is that the primary school calculated credits earned for coursework taken at other ("transfer") schools based on the primary school's credit system required for graduation. This assumption proved true in most cases, as the primary school would adjust the transferable credits from other schools into meaningful credits necessary to graduate. In some instances, however, it is clear that the conversion of credits earned at prior schools into equivalent credits at the primary school did not occur. When possible, a conversion based on English coursework observed across the transfer schools was used to standardize the credits across both schools. In the remaining instances, it was determined that a standardized set of Carnegie credits could not be established based on the information presented, and Carnegie credits for these transcripts were coded as unclassifiable. The CRS_CARNEGIE_RECODE.xxx variables indicate what steps were taken for each individual course.

Course Credit Reporting and Data Entry Errors. If a clear entry or reporting error was identified for a particular course credit (often a missing decimal point) and a correction could be identified from reviewing other course credits earned or total credits reported by term, the Carnegie credit reported in the data file was constructed to reflect the adjusted credit earned, rather than using the apparently erroneous course credit value. Approximately 100 courses were affected by these types of corrections. The original credit information remains in the CRS_CREDIT.xx variable series.

Grades 7 and 8. Student transcripts with high numbers of Carnegie credits often include grade levels outside of the typical grades 9-12 high school career. A number of district level transcripts report middle school and high school coursework. Coursework taken in grades 7 and 8 was assigned a Carnegie credit equivalent. Researchers can use the grade level variables in order to exclude these courses (and credits) from specific analyses as appropriate.

Vocational and Enrichment Coursework Credits. It is apparent from review of the transcript records that many schools apply a different credit weighting system to certain types of vocational coursework (where R-SST = 2_*) and enrichment coursework (where R-SST = 3_*) than to academic level coursework (where SST = 1_*). While Carnegie credits have been calculated for these vocational and enrichment courses, users should note the credits earned for vocational and enrichment courses inflate the total number of Carnegie credits earned for some transcripts.

Return to top Return to Table of Contents