Appendix 11: Collection of the Transcript Data (High School)

Conducted in 1999-2000, Wave 1 of 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 links below:

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

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.

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.

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_STATUSwas 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_STATUSwas 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.

Transcript Record Status and Transcript Wave

The Transcript Record Status variable is provided for all 8,984 respondents in the NLSY97 sample. For each respondent, the variable indicates whether or not a transcript was requested for the youth, and as appropriate, why a transcript was not requested, or why a transcript was not received. The second variable, available for all respondents with transcript data, reports whether the respondent's data was collected in wave 1 or wave 2 of the transcript survey.

Characteristics of Youth's primary school

These variables pertain to the school from which the youth's transcript was primarily collected. In most cases, this is the last school that the youth attended. Three variables were extracted from Quality Education Data (QED) data files:

Four additional variables were coded from a variety of sources. In priority order, we captured information from hard-copy school catalogs, on-line school catalogs, other on-line school information, or telephone calls to school staff. Information is valid for the 2004-2005 school year.

Data quality flag

This flag, called TRANS_PROBFLAG, was constructed to alert users to the existence of cases whose data we believed was incomplete or flawed in some way that would make the case less likely to provide useful information. The flag is a composite of five separate tests flagging different types of problems; a positive result for any one (or more) of those tests resulted in the case being coded 1 (Yes) for TRANS_PROBFLAG. The variable does not indicate how many flaws are present in a given case. The five component tests are:

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. Table 4 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.

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 5).

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 5).

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 5).

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 5).

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 5).

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.

These variables categorize as academic or vocational a student's full coursetaking behavior in high school. The variables follow recommendations set forth in U.S. Department of Education. National Center for Education Statistics. "Procedures Guide for Transcript Studies" Working Paper 1999-05, by Martha Naomi Alt and Denise Bradby. Project Officer, Denise Nelson. Washington, D.C.:1999. (For an explanation of the course codes [e.g., 1_31*], see Coding Information for Course Code Variables section above.)

Academic specialist (question name: TRANS_ACAD_SPEC)

• Student earned at least 4 credits in English (1_31* 1_32 1_33 1_34);
• at least 3 credits in mathematics at the Algebra 1 level or higher (1_14 1_15 1_16 1_17*);
• at least 2 credits in biology, chemistry, or physics (1_22* 1_23* 1_24*);
• at least 2 credits in social studies (1_41* 1_42* 1_43* 1_44* 1_45* 1_46* 1_47*) with at least 1 credit in US or world history (1_41* 1_42*);
• at least 2 credits in a single foreign language (1_61* 1_62* 1_63* 1_64* 1_65* 1_66*).

Academic concentrator (question name: TRANS_ACAD_CONC)

• Student earned at least 4 credits in English (1_31* 1_32 1_33 1_34);
• at least 3 credits in mathematics (1_11* 1_12* 1_13 1_14 1_15 1_16 1_17* 1_18 1_19*);
• at least 3 credits in science (1_21* 1_22 1_23 1_24* 1_25* 1_26*);
• at least 3 credits in social studies 1_41* 1_42* 1_43* 1_44* 1_45* 1_46* 1_47*).

Vocational specialist (question name: TRANS_VOC_SPEC)

• Student earned at least 4 credits in a single Specific Labor Market Preparation (SMLP) vocational area (2_C*), with at least 2 of these credits in that SLMP's 2nd-level or higher courses or co-op/work experience coursework (2_C*B 2_C*C 2_C*D 2_C11 2_C071BA).

Vocational concentrator (question name: TRANS_VOC_CONC)

• Student earned at least 3 credits total in a single Specific Labor Market Preparation (SLMP) vocational area (2_C*).

School program (question name: TRANS_SCH_PGM)

• The "School Program" variable combines the information from the four variables above. This variable is coded as follows:
  1. Academic specialist (and not vocational concentrator)
  2. Vocational concentrator (and not academic specialist)
  3. Both academic specialist and vocational concentrator
  4. Neither academic specialist nor vocational concentrator

Subject-area pipeline variables were modelled closely on the standards established in NCES Working Paper No. 2003-01 for categorization of mathematics, foreigh language, and science course-taking. Some changes in procedure were necessary because of our use of the R-SST course-coding scheme; these are noted in the appropriate sections below. (For an explanation of the course codes [e.g., 1_31*], see Coding Information for Course Code Variables section above.)

Mathematics Pipeline (question name: TRANS_MATHPIPE)

The division between students with one or fewer credits in course-code 1_16 and those with more than one credit was made in order to adapt the R-SST course-coding scheme to the 8-category math pipeline standard established in NCES 2003-01.

Sciences

Life Sciences Pipeline (question name: TRANS_BIOPIPE)

Chemistry Pipeline (question name: TRANS_CHEMPIPE)

Physics Pipeline (question name: TRANS_PHYSICS_PIPE)

(For 1_24D, see Physical Sciences Pipeline.)

Physical Sciences Pipeline (question name: PHYS_SCI_PIPE)

Overall Physical Sciences Pipeline (question name: TRANS_OPS_PIPE)

Life Sciences and Physical Sciences Pipeline (question name: TRANS_SCI_PIPE)

Foreign languages

The foreign language variables are as follows:

All foreign language pipline variables are coded using the following coding scheme:

The 0 category includes students with pre-high-school foreign-language coursework but none in high school.

Number of Languages Attempted (question name: TRANS_FRN_LANG_ATMPT)

All recorded high-school coursework in any foreign language (1_61* through 1_66*) was included in this measure, with any number of credits or none, and counting all courses coded 1_66* (Foreign Language, Other) collectively as 1 language attempted . The range in our data is from 0 to 4 languages.

Credits by Academic Year, academic/vocational

Summary credits variables sum Carnegie credits (TRANS_CRS_CARNEGIE_CREDIT.xxx) over the relevant course codes or time period. Total credits variables are assigned to reserved codes for three classes of students: those with only pre-high school coursework; those with no relevant courses; and those who had relevant courses, but no valid Carnegie credits associated with those courses. Question names for these variables are as follows:

Course codes for these variables are classified as follows (for an explanation of the course codes [e.g., 1_31*], see Coding Information for Course Code Variables section above):

Cumulative Credits by Academic Year (question name: TRANS_CUM_CRDS_EARNED_XXYY)

These variables sum the Carnegie credits earned by each student over the course of his/her high school career as of the end of each academic year. The variable has valid values for every academic year from when the student first reported high school coursework, to when the student last reported high school coursework, including interim years (if any) in which no coursework was reported.

Terms were assigned to an academic year primarily by a series of rules using information contained in the variables TERMSEAS, TERMYEAR, TRMSTRMO, TRMSTRYR, TRMENDMO, and TRMENDYR. For example, a Fall term beginning in September of 1999 would be assigned to the 1999-2000 academic year. However, start and end dates are often either missing or inaccurate, so there was extensive re-coding of academic year based on the entire sequence of terms included in the transcript, with reference to the GRLEVEL and CRSCODE variables as necessary. Summer terms were included with the previous academic year; thus, courses taken in Summer 1999 were coded as belonging to the 1998-1999 academic year.

Cumulative Percentage of New Basics requirements fulfilled by Academic Year (question name: TRANS_PCT_NB_EARNED_XXYY)

The New Basics curriculum is a minimum curriculum recommended by the National Commission of Excellence in Education (NCEE) in 1983 to be completed by high school graduates. These variables represent the cumulative percentage of New Basics Core requirements completed by each student.

New Basics Core Requirements

• English- 4 credits (1_3*)
• Math- 3 credits (1_1*)
• Science- 3 credits (1_2*)
• Social Science- 3 credits (1_4*)
• Computer Science- 0.5 credits (2_C071*)

The Carnegie credits earned for courses fulfilling New Basics requirements were summed by subject area over each academic year, and the cumulative percentage of Core New Basics requirements completed was calculated. Percentages were capped at 100, so that students exceeding requirements would show 100% fulfillment. Users may refer to National Center for Education Statistics publications for additional information on the New Basics curriculum.

Grade Level by Academic Year (question name: TRANS_GRD_LV_XXYY)

These variables report the student's grade level for each academic year we have course work reported for them. In some cases, there were two or more grade levels reported for a single academic year. In these cases, the academic year grade level is set to the grade level associated with the highest number of credits. In most cases, this is also the highest grade level reported during that academic year. Summer terms (and their associated grade levels) were excluded from this construction.

Coursework Reported by Academic Year (question name: TRANS_CRSWRK_IN_XXYY)

After the assignment of terms to academic years (see the section Cumulative Credits by Academic Year for an explanation of this process) we recorded for each student the academic years in which any coursework was reported for that student. Academic years in which only pre-high-school coursework was reported are assigned a reserved code; an academic year which contained a mixture of high-school and pre-high-school coursework (often because of high school work pursued during the summer after 8th grade) was coded as having valid coursework reported.

Credit-Weighted Grade Point Averages (question names: TRANS_CRD_GPA_OVERALL and TRANS_CRD_GPA_YR_XXYY)

These variables indicate grade point averages on a 4 point grading scale. For each course, the quality grade (TRANS_CRS_GRADE.xxx) is weighted by Carnegie credits (TRANS_CRS_CARNEGIE_CREDIT.xxx). Quality grades were recoded as follows: 1 = 4.3, 2=4.0, 3=3.7, 4=3.3, 5=3.0, 6=2.7, 7=2.3, 8=2.0, 9=1.7, 10=1.3, 11=1.0, 12=0.7, 13=0.0, all other values recoded to missing. Overall and Academic Year variables include all courses.

Subject variables are defined as follows:

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.

Available in the restricted-use geocode data only, these variables record information concerning high-school graduation requirements applicable to each case. GRADREQ_TYPE describes whether the requirements were in terms of credits, terms, or term/years. The five credit-requirement variables, GRADREQ_TOTAL through GRADREQ_SOC, give the total number of credits required for graduation and the numbers required from courses in the four specific subject areas of English, Math, Science, and Social Studies. The final variable, GRADREQ_SOURCE, shows where the requirements information was obtained. We preferred to show requirements information that came from or applied to the student's particular school, either through the individual school's catalog or website or from the school district. However, in some cases school-specific information was not available, and in these cases, we show graduation requirements set by the state in which the primary school was located, where these requirements could be determined. The values of the five credits-requirements variables must be divided by 100 before they can be used. Variable question names and titles are as follows: