JVER v25n3 - A Comparison of Selected Outcomes of Secondary Tech Prep Participants and Non-Participants in Texas
A Comparison of Selected Outcomes of Secondary Tech Prep Participants and Non-Participants in Texas
Carrie H. Brown
Region 5 Education Service Center
Beaumont, TexasAbstract
A five-year analysis of selected outcomes of cohorts of students enrolled in all regular public high schools in Texas in grades 10-12 was conducted, comparing three sub-groups of students based on participation in career and technology (CT) programs, including tech prep. One group was identified as tech prep participants while the other two groups were CT program participants (non-tech prep) and general population students. In all, over 3.4 million student records were studied, including the five multi-grade cohorts of tech prep students totaling 247,778. Results show 10th-12th grade cohorts of tech prep participants had slightly higher annual attendance rates and lower annual dropout rates than either of the non-tech prep groups. Moreover, tech prep students in their senior year had slightly higher graduation rates than the comparison groups, with an increasing percentage successfully completing college preparatory programs between 1994-95 and 1998-99. Certain ethnic, at-risk, and economically disadvantaged sub-populations demonstrated similar results.
Acknowledgement: This research was funded by grants from the Texas Higher Education Coordinating Board to the Region 5 Education Service Center using funds provided by Title III, Part E of the Carl D. Perkins Vocational and Applied Technology Education Act Amendments of 1990 and 1998. Purpose of the Study
Since 1991 the state of Texas has been engaged in the implementation of tech prep programs in the state's schools and colleges. Throughout this statewide effort a recurring concern among state and local policy makers has been whether or not participation in these programs has positive effects on educational achievement and employment. To address this question systematically, the Texas Higher Education Coordinating Board (THECB), in coordination with the Texas Education Agency (TEA), the Texas State Occupational Information Coordinating Committee, and directors of the state's tech prep consortia, developed a long-range plan for tech prep evaluation. The plan outlines three principal areas: secondary learning outcomes, postsecondary learning outcomes, and employment outcomes.
In 1997 the THECB initiated a state-level evaluation of tech prep programs, beginning with the study of secondary education outcomes. The initial phase of the evaluation reveals patterns of enrollment in tech prep programs based on the state's definition of tech prep participants; attendance, dropout, and graduation rates; type of high school graduation plan completed; and performance on the state's high school exit exam, the Texas Assessment of Academic Skills (TAAS) test, and the SAT and/or ACT tests. Addressing a lack of knowledge about the impact of tech prep, educators in the state of Texas saw these measures as critical to providing needed information about the impact of tech prep on student participation and outcomes. Of these data elements, attendance, dropout, and graduation rates by type of graduation plan are addressed in this article. Results reported here are disaggregated to assess participation by selected ethnic and special population groups.
Education Reform and Tech Prep
For the last two decades, there has been an increased focus on improving education in the nations' public schools. Aimed at addressing America's lagging student achievement in mathematics and science, high dropout rates, and the need to prepare the workforce for successful employment in changing United States and world economies, a series of national reports provided substantive rationale for this reform. The first of these, A Nation at Risk ( National Commission on Excellence in Education, 1983 ), recommended increasing academic standards and establishing core academic curricula for all students. In response, early education reforms included shifting curricula back to the basics, implementing statewide testing programs, and increasing graduation requirements ( Dornsife & Bragg, 1992 ). These reforms were reflected in Texas House Bill 72 which essentially revamped every aspect of public education bringing about a number of critical reforms, including the establishment of teacher testing, student performance standards and testing, and a well-balanced curriculum with higher minimum graduation requirements.
Other national reports, such as The Unfinished Agenda ( National Commission on Secondary Vocational Education, 1984 ), addressed the need for strengthening and improving secondary vocational education in public schools and led to the development of the national tech prep movement. Described by Parnell ( 1985 ) and Hull and Parnell ( 1991 ), the tech prep associate degree offered a method to incorporate vocational education into the restructuring of general education, while providing an alternative to traditional college preparatory programs for the middle fifty percent of students who are less likely to earn a baccalaureate degree. Title III, Part E of the Carl D. Perkins Vocational and Applied Technology Education Act Amendments of 1990, cited as the Tech Prep Education Act, provided a mechanism for states to fund the development of these articulated secondary and postsecondary education programs.
In Texas implementation of tech prep legislation resulted in the simultaneous development of 25 regional consortia coterminous with the state's workforce planning regions. This arrangement served to integrate tech prep consortia into an existing framework of partnerships designed to identify targeted career and employment opportunities and to guide related tech prep program development ( Nelson, 1994 ).
Other national-level reform initiatives have become part of the mosaic of school reform in Texas, although to varying degrees. In response to the School-to-Work Opportunities Act 27 regional partnerships were formed under the direction of the Texas Workforce Commission. Tech prep consortia and school-to-work (STW) partnerships coordinate regional activities with STW (about 40% share a single advisory board and staffs) focusing on workplace experiences and activities in grades K-8. Texas is also actively promoting linkages between tech prep and the High Schools That Work (HSTW) initiative described by Bottoms, Presson, and Johnson ( 1992 ). For example, use of tech prep funds to develop HSTW in each tech prep consortium has resulted in the doubling of sites, which now exceed 40. The overlapping goals and strategies of STW and Goals 2000-related reforms with tech prep, described by Orr ( 1998 ), confound understanding of the impact of any single initiative on student learning.
Evaluating Tech Prep Outcomes
In general, state systems for the collection and reporting of tech prep student outcomes are not well developed. There are several probable reasons for this nation-wide lag in evaluating student progress in tech prep. First, Section 346 of the Tech Prep Education Act did not require states to report information on tech prep student achievement, although inclusion of student outcome measures in state evaluation plans was recommended by the U.S. Department of Education ( Brustein, 1993 ). Consortia were therefore left to design local evaluation plans reflective of their stage of development. Bragg, Layton, and Hammons ( 1994 ) found that, in a national survey of approximately 400 consortia, few tech prep consortia were actively addressing evaluation and accountability during early stages of implementation. Similarly, Silverberg and Hershey ( 1995 ) indicated only 36% of the 702 tech prep consortia studied nationally in 1992-93 had the capacity to document and report student participation in tech prep. These and other national evaluations focused primarily on the description of tech prep education processes and identification of best practices. Early evaluation efforts in Texas followed this same pattern, consisting primarily of reporting numbers of programs and students and basic descriptions of consortium policies, procedures, and activities ( Dial, 1996 ; Dial & Strauss, 1995 ; Jackson, Dial, & Strauss, 1994 ; Opp, Cooper, & Hensley, 1995 ; Opp, Hensley, Stewart, & Rivers, 1996 ).
Another reason tech prep student evaluation systems are not well developed is that states responded to the federal tech prep initiative by adopting differing implementation strategies that included a variety of definitions of tech prep programs and student participants. Also, as is the case in Texas, consortia developed at different rates, a condition that affected capacity to report student outcomes that could be attributed to tech prep. For example, Hershey, Silverberg, Owens, and Hulsey ( 1998 ) noted in the final report of the national evaluation of tech prep that despite the growth in the percentage of consortia that could identify and report tech prep participants, a substantial number still could not provide participation rates for all member schools. More importantly, they observed that the ability of a local consortium coordinator to collect student information was dependent on the consortium's application of the definition of a tech prep participant, as well as the coordinator's ability to collect information from member schools.
Moreover, the scope of tech prep student outcome evaluation is potentially enormous, especially in states without a statewide infrastructure for data collection. In Texas, for example, coordination of consistent data collection in the state's school districts and colleges would be very difficult, if not impossible, if left to local consortium directors who would be faced with procuring information from anywhere from eight to over one-hundred school districts and up to nine colleges. Finally, since many states are implementing multiple school reform initiatives simultaneously, state or local personnel may be hesitant to report tech prep outcomes for fear of attributing student change to tech prep alone. Jacobs and Teahen ( 1998 ) drew a similar conclusion for the state of Michigan.
Consequently, reports of state-level evaluations of tech prep student outcomes are uncommon, although states such as Florida ( Hammons, 1995 , 1999 ), Minnesota ( Brown, Pucel, Twohig, Semler, & Kuchinke, 1998 ), New York ( Brodsky, Newman, Arroyo, & Fabozzi, 1997 ), and Texas ( James & Jurich, 1999 ) refer to state systems capable of this type of research. National-level evaluations of student outcomes are even more limited. Hershey et al. ( 1998 ) analyzed follow-up surveys of about 480 high school graduates from 10 tech prep sites conducted during the national evaluation process to determine trends in postsecondary enrollment and employment. They concluded that despite limitations of sampling and response rate, findings enhanced information from the national consortium surveys.
Structure of Tech Prep Programs in Texas
Through a cooperative agreement between the Texas Education Agency (TEA) and the Texas Higher Education Coordinating Board (THECB), state-level policies were developed to promote voluntary implementation of tech prep by the state's 974 public independent school districts with high schools and 57 two-year colleges, and to facilitate the voluntary integration of tech prep into everyday educational practices. To provide a framework for the local development of tech prep programs, the TEA and the THECB adopted guidelines for tech prep program approval that require joint school district and college tech prep program applications ( Texas Higher Education Coordinating Board, 1993 ). To be state-approved, programs must consist of a four-year high school curriculum and a two-year associate of applied science (AAS) degree program that addresses regional labor market needs. Tech prep plans can be expanded locally to include an additional two years, leading to baccalaureate degrees.
Since about 1995 the secondary portion of tech prep programs has been based on a choice of three graduation options, minimum, recommended, and distinguished achievement, replacing the regular and college-preparatory advanced plans. Career and technology (CT) programs can be integrated into all three graduation plans, although schools have been encouraged to engage tech prep students in the college-preparatory programs of study. In addition to academic requirements specified for each graduation option, tech prep programs generally include two or more CT courses in a sequence totaling three or more credits. At least one of these CT courses must be articulated for college credit or taken through concurrent college enrollment.
The minimum plan is a general education program that requires completion of grade-level or above academic courses totaling a minimum of 21 credits. Both the recommended and the distinguished achievement programs are college-preparatory, each requiring a minimum of 24 credits that include additional and higher-level courses in mathematics, science, and English/language arts than the minimum plan, as well as study of a language other than English. The distinguished achievement plan requires additional foreign language competence, as well as completion of four advanced measures selected from original research projects, college-level courses including tech prep articulated courses, and/or selected test data, such as Advanced Placement scores. Beginning September 1999, Texas House Bill 2401 mandated that any new tech prep programs be based on the recommended high school graduation plan.
The THECB has responsibility for designating as tech prep all AAS degree plans that meet the tech prep program requirements. Many of these degree programs contain one or more enhanced skills certificates that offer specialized skills training beyond the associate degree level. By 1999 the state had approved 657 tech prep programs including 726 AAS degree awards, 847 postsecondary certificate exit points, and 591 enhanced skill certificate awards in 23 technical subject areas ( Texas Higher Education Coordinating Board, 1999 ).
The extent of articulation of public school CT programs with these tech prep degrees has varied based on the ability of individual high schools to provide sequential curriculum that links with postsecondary programs. In fact, 39% of public school districts in Texas with grades 10-12 are rural and 51% have K-12 enrollments of less than 1,000 ( Texas Education Agency, 1999a ), and there is no disputing that these factors influence the ability of schools to offer a wide variety of tech prep programs.
Tech Prep Student Identification and Reporting
To facilitate evaluation of tech prep implementation in the state, in 1993 the TEA added a tech prep student identification code to the state's public education information management system (PEIMS), and adopted a standard definition of a secondary tech prep student. The state defines a secondary tech prep student as a student in grades 9-12 who follows an approved tech prep high school plan of study leading to postsecondary education and training and is enrolled in courses appropriate to that plan ( Texas Education Agency, 1999b ).
The Texas state coding system for CT uses the numbers 0, 1, 2, and 3. Codes 0 and 1 are course enrollment codes based on enrollment in a CT course in the fall semester. A 1 indicates a student is enrolled in one or more CT courses, a 0 indicates they are not. Code 2 is used to indicate students who have chosen to follow a CT course sequence that is not state-approved as tech prep, a 3 is used to indicate students who have chosen to follow a CT course sequence that is state-approved as tech prep ( Texas Education Agency, 1999c ). Therefore, school district personnel identify and report all high school students according to their degree of participation in CT courses and programs. Students may elect to participate in coherent sequences of CT courses at differing grade levels and their status is reported annually. In 1998-99 the number of seniors reported as participating in tech prep programs for more than their senior year increased to almost 45%. As such, this method of tech prep student identification relies heavily on the ability of school district personnel to track and report a student's intent to participate and actual participation in CT coherent sequences over a student's tenure in high school.
Methodology
In 1997 a comparative analysis of annual cohorts of high school students was initiated by the state of Texas. The study began with students enrolled in the 1994-95 school year and addressed enrollment patterns in CT programs, annual attendance rates, annual dropout rates, high school graduation rates by type of high school graduation plan, performance on the state's high school exit exam, the Texas Assessment of Academic Skills (TAAS) test, SAT and/or ACT tests, enrollment in public postsecondary institutions, and employment patterns. School year 1994-95 was selected as the baseline study year as it was the first year that any students could have benefited from a four-year high school tech prep program, assuming implementation in the 1991-92 school year.
Data Source
The TEA provided all student data from the statewide PEIMS, which is based on annual submission of data to the TEA via standardized computer files by public school districts. To enhance the quality of data, standard software edits were performed by regional education service centers and again by the TEA. A student's CT status was reported to the state based on the specified fall enrollment reporting date, typically mid-October of each year. Enrollment data for the preceding fall semester, and attendance rates, dropout rates, and graduation rates for the preceding school year were certified by the TEA in February of each year for attendance and graduation and August of each year for dropouts.
Data represent two separate cohorts of students for each school year studied, 10th-12th grade cohorts and 12th grade cohorts, and each of these was disaggregated into the three CT sub-populations under investigation in this study. Special education students were included in all calculations.
Variables as Operationalized
Total enrollments for each cohort population and for each CT sub-group were calculated by the TEA for each year of the study. The study of attendance rates and dropout rates is based on simultaneous analysis of the combined 10th-12th grade student cohorts for all regular public high schools in Texas for school years 1994-95 through 1998-99. Simultaneous analysis of multiple grade levels was used to ensure that in any given school year the population studied included all students identified that year as participating in tech prep programs, which resulted in multi-year analysis of those students identified as tech prep in more than one study year. Ninth-grade students were excluded from this study because Texas high school students do not take the high school exit-level test until the 10th grade, a variable examined for these cohort populations in additional studies.
Average annual attendance rates and average annual dropout rates were calculated by TEA for each combined 10th-12th grade student cohort and for each CT sub-group. These calculations were then disaggregated into sub-groups by ethnicity (White, Hispanic, African American, Asian/Pacific Islander, and Native American) and special population category (at-risk, economically disadvantaged, bilingual/ESL, special education, and all other students). Calculations of special population categories could have included duplicate counts since students could have been identified in multiple categories (e.g., at-risk and economically disadvantaged).
A similar process was followed for graduation rates calculated by TEA for each annual 12th grade cohort. Cohorts of students graduating at the end of the 12th grade, subdivided into the three CT classifications, were analyzed beginning in the 1994-95 school year for overall graduation rates as well as graduation rates by type of plan (i.e., regular/minimum or college-preparatory).
Annual attendance rates were based on student attendance for the entire school year, calculated by the total number of days a student was present during the school year divided by the number of days the student was in membership during the school year ( Texas Education Agency, 1999d ). A student was identified as a dropout if the individual was absent without an approved excuse or documented transfer and did not return to school by the following year, or if the student completed the school year but failed to re-enroll the following year. Not all school leavers were counted as dropouts, depending on the reason for the student's departure. The annual dropout rate was the count of dropouts during the school year summed across grades 10-12, divided by the number of students who were in membership at any time during the school year, summed across grades 10-12. Cumulative counts were used in both the numerator and denominator to neutralize the effect of student mobility. Factors affecting dropout rates were provided by school districts to the PEIMS and rates were calculated by the TEA based on this information ( Texas Education Agency, 1999d ).
Graduation rates were based on the total number of 12th grade high school graduates (including summer graduates) in the school year divided by the total number of students in membership in the 12th grade during the school year. The percentage of 12th grade graduates who were reported as having satisfied the course requirements for college preparatory programs (advanced, recommended, and distinguished achievement) was based on the sum of number of graduates in each of these categories for a school year divided by the total number of 12th grade graduates in each school year ( Texas Education Agency, 1999d ).
Data Analysis
Due to the fact that entire populations of students were studied for the specified years, descriptive statistics were utilized. Cohort groups by grade level and sub-groups of special population and race/ethnicity groups were described using frequency distributions (percentages), means, medians, and other simple descriptive statistics.
Results
Results from this five-year study of tech prep and non-tech prep student characteristics are voluminous. Consequently, results reported here are limited to secondary education outcomes, including enrollments and attendance, dropout, and graduation rates of annual cohorts and specific special population groups.
Enrollment Patterns
During the study period, the number of all participants in CT programs in the state almost doubled, increasing from just over 100,000 to almost 200,000. While the non-tech prep CT enrollment grew by 68% to a total of 135,652 in 1998-99, tech prep student enrollment grew over 200%, from 21,144 in 1994-95 to 63,817 in 1998-99, and accounted for almost 9% of the entire 10th-12th grade population of 724,235 in 1998-99. In contrast, the annual cohort populations comprised of all other, non-CT participants remained relatively stable, averaging about 527,000 per year. The number of students in the annual study population increased 12%, from 633,386 total students in grades 10-12 in 1994-95 to 724,235 students in 1998-99. Over the five-year period, over 3.4 million student records were analyzed, including 247,778 tech prep participants, which represents duplicate counts for those students included in more than one multi-grade level cohort.
The ethnic breakdown of the five 10th-12th grade cohorts averaged about 51.4% White, 32.0% Hispanic, 13.5% African American, and about 3.1% Asian/Pacific Islander and Native American combined. When compared to the ethnic profile of each of the tech prep student cohorts, the groups were not different except that the African American population was underrepresented, comprising from 9% to 11% of the tech prep population; the combined Asian/Pacific Islander and Native American population was underrepresented in the tech prep sub-population by about 1% each year.
Average Annual Attendance Rates
School attendance rates in grades 10-12 for students participating in tech prep programs were stable over the five-year period, ranging from 94.2% to 94.6% and averaging about 1% per year higher than other CT program participants. Attendance rates of tech prep students also averaged about one-half percentage point higher over the five-year study period than the attendance rates of all other non-CT participants.
Attendance rates for White, Hispanic, and African American and at-risk and economically disadvantaged groups of the CT sub-populations for the 1997-98 school year were disaggregated to examine differences between the groups. Although attendance rates for tech prep students were higher for all five sub-populations, ranging from a low of 93.1% for at-risk tech prep students to a high of 94.9% for White tech prep students, there are notable differences. For example, in the White sub-population, attendance rates for tech prep students were essentially the same as non-CT students with rates of 94.9% and 94.8% respectively, while the rate of all other CT students averaged 94%. In contrast, the two groups of non-tech prep Hispanic, at-risk, and economically disadvantaged students had roughly the same attendance rates (averaging 92.7%, 91.9%, and 92.7% respectively), which were 1% or more lower than attendance rates of tech prep students in these categories. In addition, African American students participating in tech prep programs had attendance rates of 94.5%, similar to that of White tech prep students. African American participants in non-tech prep CT programs had attendance rates higher than the non-CT students, 93.4% and 92.7% respectively.
Average Annual Dropout Rates
Results of annual dropout data reveal an overall decline in dropout rates for all student groups over the five-year period. Dropout rates for tech prep students were consistently lower than the other two groups for all five years, beginning with a rate of about 1.3% and decreasing to 1.0% in 1998-99. In contrast, CT students not participating in tech prep had dropout rates that decreased from about 2.2% to 1.4% during the study period, and the remaining student population saw annual rates decrease from about 1.8% to 1.6%.
Dropout rates for White, Hispanic, African American, at-risk, and economically disadvantaged groups of the CT sub-populations for the 1997-98 school year were disaggregated to show differences between the groups. Once again, dropout rates for tech prep participants were lower for all five sub-populations, ranging from 0.8% in the White sub-population to 1.9% in the at-risk sub-population.
Although the differences in dropout rates between groups of White CT and non-CT students and tech prep students averaged 0.2%, larger differences are evident in the remaining four sub-populations. The two groups of non-tech prep Hispanic, African American, and economically disadvantaged students had roughly the same dropout rates, averaging 2.1%, in contrast to the 1.4% average rates for tech prep students in these categories. Not surprisingly, the highest dropout rates among the non-tech prep participant groups were seen in the at-risk population, which averaged 2.7%.
Average Annual Graduation Rates
The number of seniors in each 12th grade cohort is detailed in Table 1 . The number of tech prep seniors studied increased about 167% over the study period, from about 9,000 to almost 24,000, an increase similar to the nearly 200% increase seen in the 10th-12th grade tech prep participant population. During this same time there was also a corresponding increase in non-tech prep CT seniors of 63%, similar to the 68% increase seen in the 10th-12th grade population. In contrast, the annual cohort population of all other, non-CT seniors remained relatively stable, averaging about 142,000 per year. The total number of 12th grade students increased from 183,737 in 1994-95 to 212,245 in 1998-99, reflecting an overall increase in the 12th grade study population of about 16%. In all, almost 1.0 million senior records were analyzed, including 94,426 for tech prep. The ethnic breakdown of the senior cohorts averaged about 53% White, 31% Hispanic, 13% African American, and 3% Asian/Pacific Islander and Native American, similar to that of the 10th-12th grade cohorts.
Table 1 Student Cohort Populations, Grade 12
School Years 1994-95 1995-96 1996-97 1997-98 1998-99 Total
All Years
Total All Other Students (0, 1) 145,907 138,097 139,656 142,046 141,487 707,193 Total CT Students Not Tech Prep (2) 28,896 30,584 34,843 41,324 46,978 182,625 Total Tech Prep Students (3) 8,934 17,548 20,569 23,595 23,780 94,426 Total All Sub-Populations (0, 1, 2, 3) 183,737 186,229 195,068 206,965 212,245 984,244
Senior graduation rates for tech prep participants and non-participants are shown in Figure 1. In all five graduating classes, a higher percentage of tech prep participants graduated than the other two classifications of students who did not participate in tech prep. Interestingly, the graduation rates of CT students not participating in tech prep increased from 82% to 85.5% in 1998-99, approaching within 2% the graduation rate of tech prep students, while the graduation rates of the remaining non-CT groups remained essentially constant, fluctuating between 81% and 82%.
When analyzing the percentage of graduates completing college preparatory plans an interesting pattern emerges ( see Figure 2 ). First, the percentage of tech prep graduates completing college-preparatory plans increased by 6.5% in one year (1994-95 to 1995-96), and thereafter remained higher than or equal to the rate of non-CT students, representing almost 45% of all tech prep graduates in 1998-99. Second, although relatively low in the beginning (33.4%), the number of non-tech prep CT participants graduating with these higher requirements increased steadily, approaching 40% in 1998-99.
Figure 1. Percentage grade 12 tech prep participants and non-participants graduating by school year.
Figure 2. Percentage of tech prep participant and non-participant graduates completing college preparatory plans by school year.
Graduation rates of selected sub-populations for the 1998-99 senior cohort are shown in Figure 3. In general, the graduation rates of tech prep students parallel those of the other two CT groups for all five of the sub-populations illustrated, averaging rates slightly higher than other CT participants and up to 8% higher than all other non-CT participants. The rates for the African American and at-risk subpopulations are lower overall (78.7% and 80.5%, respectively), while White and economically disadvantaged students had the highest graduation rates (90.1% and 89.0%, respectively). The graduation rate of Hispanic tech prep participants was 86.0%. Except for African American students, tech prep participants had the highest graduation rates of any group.
Figure 3. Percentage of grade 12 tech prep participants and non-participants graduating by selected sub-populations (1998-99).
Of the White tech prep students graduating in 1998-99, almost 48% completed a college preparatory plan, similar to the nearly 47% of economically disadvantaged graduates and greater than the 42% of Hispanic graduates who completed college preparatory plans. In addition to the lowest graduation rates overall, fewer African American and at-risk graduates completed college preparatory plans, 33.5% and 26.2%, respectively.
Summary and Implications for Further Research
Results of a comparative analysis of the enrollment patterns, attendance rates, dropout rates, and graduation rates of public high school cohorts in Texas show definite positive trends for students identified as participating in tech prep programs, as well as selected ethnic and special populations groups. Overall, the study shows slightly lower dropout rates, higher attendance rates, and higher graduation rates for tech prep participants than non-participants. An increase in the number of tech prep students graduating under more challenging college preparatory plans was also noted. Participation in tech prep programs by ethic and special populations groups paralleled that of the state, and these tech prep students demonstrated improvement in all areas studied relative to the non-tech prep ethnic and special population groups.
Though relatively modest, the consistent positive outcomes among tech prep participants are noteworthy. Over the study period, the number of tech prep student participants increased substantially, bringing the aggregate total of all tech prep student records analyzed to almost 250,000, including a partial duplicate count. Although the annual tech prep student population increased by about 200% during the study period, with regard to the variables studied, tech prep participants either improved (as with dropout rates) or remained relatively constant (as with attendance and graduation rates) over time. These improvements lend credence to the state's process of identification and reporting of tech prep program participants. It also provides confidence that the tech prep student population identified statewide provides a solid base for interpreting further evaluation planned by the state of Texas to determine the relative success of these students in postsecondary education and in the workplace.
Though there is mounting evidence that curriculum reform in Texas has had a positive impact on all students and careful analysis of the data suggests that participation in CT programs may positively impact student learning, additional analysis sensitive to the particular effects of tech prep is needed. For example, factors contributing to an increase in tech prep participants may be due to the integration of tech prep into all graduation options, making the program appealing to students with higher academic aspirations. On the other hand, enrollment growth may be due to an increase in the number of tech prep programs, improved program marketing, improved student identification, or a combination of these.
Additionally, tech prep articulated programs and supportive processes have been differentially implemented across the state, reflecting regional and institutional differences according to the options afforded by local control. For example, tech prep is a voluntary option for public schools in Texas and only about 50% of all public high schools report tech prep participants, including use of applied instructional methodologies. The state does not officially recognize applied academics courses, and any course may be taught by traditional or applied methodologies at the discretion of school personnel. Aggregating results for participants across such diverse applications of tech prep is likely to obscure results. Not-with-standing, results of this study are encouraging to practitioners and policy makers who support implementation of tech prep because they document consistent improvement in student outcomes for an entire high school student population in a large state undergoing extensive education reform.
References
Bottoms , G., Presson, A., & Johnson, M. (1992). Making high schools work through integration of academic and vocational education. Atlanta, GA: Southern Regional Education Board.
Bragg . D. D., Layton, J.D., & Hammons, F. (1994). Tech prep implementation in the United States: Promising trends and lingering challenges. (MDS-714). Berkeley, CA: National Center for Research in Vocational Education, University of California at Berkeley.
Brodsky , S. M., Newman, D. L., Arroyo, C. G., & Fabozzi, J. M. (1997, October). Evaluation of tech-prep in New York state. Albany, NY: New York State Department of Education.
Brown , J. M., Pucel, D. Twohig, C., Semler, S., & Kuchinke, K. P. (1998, Spring). Minnesota's tech prep outcome evaluation model. Journal of Industrial Teacher Education , 35(3), 44-99 .
Brustein , M. (1993). AVA guide to federal funding for techprep . Alexandria, VA: American Vocational Association.
Dial , M. (1996). Evaluation of tech prep system development and implementation in Texas public schools and institutions of higher education . Houston, TX: Houston Community College System.
Dial , M., & Strauss, R. (1995). Evaluation of tech prep system development and implementation in Texas public schools and institutions of higher education . Houston, TX: Decision Information Resources, Inc.
Dornsife , C. J. & Bragg, D. D. (1992, December). An historical perspective for tech prep. In D. D. Bragg (Ed.) Implementing tech prep: A guide to planning a quality initiative (pp. 2-1 - 2-17) (MSDS-241). Berkeley, CA: National Center for Research in Vocational Education, University of California at Berkeley.
Hammons , F. T. (1995). Florida tech prep education . Miami, FL: Florida International University.
Hammons , F. T. (1999). Florida tech prep evaluation . Miami, FL: Florida International University.
Hershey , A. M., Silverberg, M. K., Owens, T., & Hulsey, L. K. (1998). Focus for the future: The final report of the national tech-prep evaluation . Princeton, NJ: Mathematica Policy Research, Inc.
Hull , D., & Parnell, D. (Eds.) (1991). Tech prep associate degree: A win/win experience. Waco, TX: Center for Occupational Research and Development.
Jackson , R., Dial, M., & Strauss, R. (1994). Evaluation of tech prep system development and implementation in Texas public schools and institutions of higher education. Houston, TX: Decision Information Resources, Inc.
Jacobs , J., & Teahen, R. C. (1998). Michigan tech prep in the midst of systemic reform. Journal of Vocational Education Research , 23(2), 115-132.
James , D. W., Ed., & Jurich, S. (1999). Tech-Prep: Texas. In: More things that do make a difference for youth: a compendium of evaluations of youth programs and practices , Volume II (pp. 54-58). Washington, DC: American Youth Policy Forum.
National Commission on Excellence in Education. (1983). A nation at risk: the imperative for education reform. Washington, DC: U.S. Department of Education.
National Commission on Secondary Vocational Education. (1984). The Unfinished Agenda. The role of occupational education in the high school. Washington, DC: Office of Vocational and Adult Education, U.S Department of Education.
Nelson , C. H. (1994). Tech prep in Texas: an implementation strategy. Community College Journal of Research and Practice , 18(2), 99-112.
Opp , R., Cooper, P., & Hensley, O. (1995) Effective tech prep policies and practices: Strategic planning, evaluation of curriculum, and performance assessment (SPECAP). Lubbock, TX: Texas Tech University.
Opp , R., Hensley, O., Stewart, G., & Rivers, B. (1996). The final report on effective policies and practices in selected career fields . Lubbock, TX: Texas Tech University.
Orr , M. T. (1998). Integrating secondary and community colleges through school-to-work transition and educational reform. Journal of Vocational Education Research , 23(2), 93-113.
Parnell , D. (1985). The Neglected Majority . Washington, DC: Community College Press.
Silverberg , M. K., & Hershey, A. M. (1995). The emergence of tech-prep at the state and local levels . Princeton, NJ: Mathematica Policy Research, Inc.
Texas Education Agency. (1999a). Public Education Information Management System (PEIMS). Austin, TX: Author.
Texas Education Agency. (1999b). 1999 accountability manual Austin , TX: Author.
Texas Education Agency . (1999c). 1999-2000 PEIMS data Standards Austin, TX: Author.
Texas Education Agency. (1999d). Glossary for the academic excellence indicator system 1998-99 report . Austin, TX: Author.
Texas Higher Education Coordinating Board. (1993). Technical education program guidelines . Austin, TX: Author.
Texas Higher Education Coordinating Board. (1999). Workforce education program inventory . Austin, TX: Author.
Author
CARRIE H. BROWN is Director of Tech-Prep Statewide Technical Assistance Projects (Leadership & Evaluation), Region 5 Education Service Center, 2295 Delaware St., Beaumont, Texas 77703, [E-mail: brownpcn@lcc.net ]. Her research interests include tech prep programs and student achievement.