First, relatively new consortia may still be planning and determining objectives, target population, and program elements. Some practitioners and researchers have suggested that consortia must devote at least one year to planning before enrollment can begin (Walter 1991). Other research indicates that consortia may spend an average of three to five years on planning and full implementation (Dutton 1991). More than one-fourth of the survey respondents had received their first Title IIIE grant for FY 1993--the year for which student counts were requested--and the remainder had received their first grant one year before. Thus, in fall 1993, we might expect that some consortia would not yet be prepared to identify Tech-Prep students. About one-third of consortia lacked a definition for identifying Tech-Prep students at the time of the national survey. Even among those that could report they had defined participation by the fall 1993 survey, some may have only begun counting participants that fall and thus could not respond to survey questions about participation in school year 1992-1993.
Second, some consortia may not have the capacity to collect data on student participation. Even consortia that have developed a definition for identifying which students are in Tech-Prep, and that have students participating in the program as it is defined by them, may be unable to assemble the information. Member districts may lack computerized files that enable them to determine the number of students meeting the Tech-Prep definition--for example, students who take a vocational course and related applied academic courses. Some consortia may not operate as a cohesive unit. Consortium staff may lack the leverage to request or require student-level data collection efforts of individual member districts. Lack of cooperation among districts and schools may prevent student counts from being collected and reported.
Third, the organization of a Tech-Prep program can affect the capacity to measure participation. Consortia that implement Tech-Prep as a distinct program may find it easier to document participation. When participants are defined by their "choice" of Tech-Prep as a path, school or consortia staff can count application forms, for example, to determine the number of participating students. Consortia that make Tech-Prep components broadly available to all students, and in which students participate to different degrees, may have greater difficulty identifying who is a Tech-Prep student.
The "maturity" of a consortium seems to influence its ability to measure participation, just as it affects the likelihood of having developed a definition on which the counts are based (see Chapter V). Data from the fall 1993 survey confirm that older consortia are more likely to be able to identify Tech-Prep students. Forty five percent of the early grantees--those that received their first Title IIIE grant in FY 1992--were able to report Tech-Prep enrollments, whereas only 9 percent of the FY 1993 grantees were able to do so (Figure VI.1).
Although individual consortium differences probably explain some of the variation in reporting capacity, state policies influence reporting capacity as well. State agencies, in Ohio, for example, provide guidance to local consortia on developing curricula and defining core programs and participation criteria. Because Ohio has encouraged consortia to implement programs carefully and fully before enrolling and "counting" students, none of the 13 consortia in the state were yet prepared to report participation numbers for the fall 1993 survey. In California, where few Title IIIE grants were awarded in time for FY 1992, most consortia were still in the planning stages; only one consortium had formulated and applied a definition of participation by the time of the national survey. Consortia and state agencies in Oregon have developed a simple statewide definition for counting Tech-Prep students1 and have made individual schools and regional vocational committees responsible for collecting these enrollment figures. This strategy probably explains why more than half of the consortia in Oregon were able to report the number of participating students.
The survey findings indicate that in almost all consortia containing multiple school districts--the majority of consortia--only some member districts are able to determine Tech-Prep enrollments (Table VI.1). Although 36 percent of consortia nationwide could report student participation, they could do so for only 17 percent of their consortium districts. This pattern suggests that Tech-Prep is unevenly implemented across member districts in many consortia. Some consortia may be in a pilot phase, concentrating implementation efforts in a few schools or districts. In others, districts are at different implementation stages, with only the more advanced districts able to document Tech-Prep participants. Consortia with many member districts (intuitively, the most likely to have uneven implementation) have the smallest proportion of districts that can report enrollments.
| Numbera | Percentage that Can Report | |||
| State | Consortia | Districts | Consortia | Districts |
| Alabama | 27 | 102 | 52 | 31 |
| Alaska | 2 | 2 | 0 | 0 |
| Arizona | 15 | 67 | 40 | 30 |
| Arkansas | 13 | 58 | 62 | 29 |
| California | 44 | 210 | 2 | 1 |
| Colorado | 13 | 59 | 23 | 5 |
| Connecticut | 9 | 58 | 56 | 40 |
| Delaware | 1 | 14 | 0 | 0 |
| District of Columbia | 1 | 1 | 100 | 100 |
| Florida | 16 | 36 | 56 | 39 |
| Georgia | 46 | 94 | 30 | 23 |
| Hawaii | 4 | 4 | 0 | 0 |
| Idaho | 6 | 93 | 0 | 0 |
| Illinois | 28 | 323 | 32 | 13 |
| Indiana | 13 | 275 | 62 | 14 |
| Iowa | 5 | 36 | 60 | 17 |
| Kansas | 6 | 58 | 33 | 10 |
| Kentucky | 38 | 51 | 34 | 26 |
| Louisiana | 12 | 28 | 42 | 36 |
| Maine | 6 | 143 | 17 | 8 |
| Maryland | 15 | 23 | 53 | 44 |
| Massachusetts | 9 | 57 | 67 | 51 |
| Michigan | 37 | 489 | 19 | 11 |
| Minnesota | 18 | 209 | 17 | 3 |
| Mississippi | 14 | 72 | 7 | 4 |
| Missouri | 12 | 257 | 0 | 0 |
| Montana | 3 | 20 | 33 | 5 |
| Nebraska | 6 | 37 | 83 | 30 |
| Nevada | 3 | 9 | 100 | 33 |
| New Hampshire | 2 | 14 | 0 | 0 |
| New Jersey | 15 | 162 | 53 | 30 |
| New Mexico | 10 | 38 | 60 | 45 |
| New York | 26 | 166 | 46 | 34 |
| North Carolina | 42 | 65 | 55 | 54 |
| North Dakota | 1 | 53 | 0 | 0 |
| Ohio | 13 | 145 | 0 | 0 |
| Oklahoma | 10 | 59 | 40 | 9 |
| Oregon | 7 | 77 | 57 | 61 |
| Pennsylvania | 18 | 239 | 28 | 9 |
| Rhode Island | 1 | 20 | 100 | 100 |
| South Carolina | 16 | 93 | 63 | 73 |
| South Dakota | 4 | 58 | 0 | 0 |
| Tennessee | 14 | 114 | 71 | 54 |
| Texas | 25 | 692 | 52 | 14 |
| Utah | 8 | 40 | 38 | 20 |
| Vermont | 4 | 11 | 25 | 9 |
| Virginia | 21 | 124 | 10 | 2 |
| Washington | 15 | 105 | 7 | 4 |
| West Virginia | 11 | 32 | 36 | 15 |
| Wisconsin | 12 | 291 | 42 | 12 |
| Wyoming | 3 | 3 | 33 | 33 |
| Puerto Rico | 1 | 1 | 100 | 100 |
| Virgin Islands | 1 | 2 | 0 | 0 |
| Total | 702 | 5,489 | 36 | 17 |
aNumbers based on survey respondents.