Source: UNIVERSITY OF FLORIDA submitted to
SOCIAL STRUCTURAL INFLUENCES ON EDUCATIONAL PROCESSES AND OUTCOMES IN RURAL AMERICA
Sponsoring Institution
National Institute of Food and Agriculture
Project Status
TERMINATED
Funding Source
HATCH
Reporting Frequency
Annual
Accession No.
0216677
Grant No.
(N/A)
Project No.
FLA-AEC-004809
Proposal No.
(N/A)
Multistate No.
(N/A)
Program Code
(N/A)
Project Start Date
Oct 1, 2008
Project End Date
Sep 30, 2013
Grant Year
(N/A)
Project Director
Israel, G.
Recipient Organization
UNIVERSITY OF FLORIDA
G022 MCCARTY HALL
GAINESVILLE,FL 32611
Performing Department
Agricultural Education and Communication
Non Technical Summary
It is widely believed that the prosperity of the nation?s people and economy rests, in large part, on the availability of human capital. Since most human capital is generated through formal education, the quality of public K-20 education is of paramount importance in preparing America?s youth to be productive professionals and engaged citizens. Furthermore, the need for skilled professionals in science and math-oriented jobs is increasing in the technology-driven global economy, and policymakers are concerned that the supply of skilled workers will fall short of demand. The quality of public education also is critical to maintaining agricultural and natural resource-based industries in increasingly competitive regional and global markets. An educated and skilled pool of workers is the key feature supporting America?s effort to progress in the technologically sophisticated global environment. Though public schools are the primary factor in math and science education, there also is evidence that families and communities share responsibility for promoting students? academic success. Considerable effort has been directed at understanding educational outcomes and assessing the efficacy of interventions inside and outside the school, but significant gaps remain. These include limited understanding of how attributes of curricula and programs affect educational outcomes and how family, school, and community factors moderate or mediate these affects. This gap is especially apparent when the scope and rigor of the research is considered. For example, few large-scale, systematic studies have examined how well Career and Technical Education (CTE) students? achievement compares with those enrolled in other academic curricula and whether the former are prepared to compete for science and math-oriented positions in college and industry. In a similar manner, more attention has been devoted to reading achievement than to math and science at the elementary level. In addition, despite the well-documented effects of community resources, there are few studies that have examined the mechanisms of how rural location moderates the relationship between educational programs and student outcomes. This research project examines characteristics of curricula and programs that might facilitate or hinder educational outcomes during the K-12 years. These relationships are assessed in the context of social structures and processes that occur within families, schools, and communities. Obtaining a better understanding of the effects of curricula, family, school, and community factors on educational outcomes can help school officials, parents, and local leaders identify policies and programs that are likely to be effective in enhancing educational achievement.
Animal Health Component
(N/A)
Research Effort Categories
Basic
(N/A)
Applied
(N/A)
Developmental
(N/A)
Classification

Knowledge Area (KA)Subject of Investigation (SOI)Field of Science (FOS)Percent
90360993020100%
Knowledge Area
903 - Communication, Education, and Information Delivery;

Subject Of Investigation
6099 - People and communities, general/other;

Field Of Science
3020 - Education;
Goals / Objectives
This research project examines characteristics of curricula and programs that might facilitate or hinder educational outcomes during the K-12 years. These relationships are assessed in the context of social structures and processes that occur within families, schools, and communities. Obtaining a better understanding of the effects of curricula, family, school, and community factors on educational outcomes can help school officials, parents, and local leaders identify policies and programs that are likely to be effective in enhancing educational achievement. Key objectives for the research project are twofold: 1) to identify educational curricula and processes that are effective in increasing student achievement, high school completion, college attendance and employment opportunities, and 2) to develop conceptual and statistical models, including multi-level models using HLM, to identify attributes of families and communities that mediate or moderate the effects of curricula and processes on educational outcomes. The results from this project will be disseminated using a multi-faceted approach. The researchers plan to publish manuscripts in appropriate refereed journals such as Sociology of Education, Rural Sociology, Southern Rural Sociology, and Journal of Research in Rural Education. Summaries of the research findings will be prepared for distribution to educational agencies and/or Extension organizations in the form of trade journal articles (e.g., School Business Affairs, Phi Delta Kappan), policy briefs (e.g., Rural Realities) and fact sheets. Finally, the researchers will work with UF/IFAS communication services to develop press releases for the mass media. The findings from this research can have an important impact on educational policy and practice. One reason is that there are few studies that use rigorous statistical analysis to test the utility of curricula on student outcomes. For example, assessing how students benefit in different CTE formulations, such as occupation-only concentrations versus dual concentrations, and under which contexts can provide valuable guidance to the design of high school curricula. Such findings can help educational administrators and funding agencies make better inform decisions on the allocation of resources for programs and curricula. Similarly, this research will be relevant to the ongoing discussion about the effect of the "No Child Left Behind" legislation. Should, for example, parents' involvement in school events act as an important moderator of students' achievement, then educational administrators and policy makers must consider how the allocation of scarce resources to improving the engagement of parents can impact school outcomes. On the other hand, should teacher certification prove to be a significant moderator, then a different set of policy decisions are implied. This project will develop and test models that can better address what difference schools are making and identify the types of programs and operating conditions that are helping students to excel.
Project Methods
Given the two objectives, first, to identify educational curricula and processes that are effective in increasing student outcomes and, second, to develop conceptual and statistical models to identify attributes of families and communities that mediate or moderate the effects of curricula and processes on educational outcomes, a series of studies are proposed. Studies using Florida Department of Education (FDOE) data: 1. Analysis of attributes of career and technical education (CTE) programs that influence learning processes and student outcomes, including achievement, high school completion, and college attendance. 2. Analyses of school factors and teacher qualifications, and student background attributes to assess which factors are important moderators or mediators in the relationship between CTE program attributes and student outcomes. 3. Analyses of community attributes to assess which factors are important moderators or mediators in the relationship between CTE program attributes and student outcomes. Studies using ECLS-K data: 4. A set of studies to assess attributes of kindergarten through eighth grade curricula that influence student achievement. 5. Analyses of school factors and teacher qualifications, and student background attributes to assess which factors are important moderators or mediators in the relationship between program attributes and student outcomes. 6. Analyses of family and community attributes (both structure and process) to assess which factors are important moderators or mediators in the relationship between program attributes and student outcomes. The first three analyses will focus on secondary students and use data from the FDOE's data warehouse. To assess student achievement in CTE programs, a cohort of students enrolled in 10th grade CTE programs in 2006-2007 and an equal-size random sample of non-CTE students will be selected. Data on Educational Curriculum (which includes program, subject and course identifiers), as well as that on student transcripts, will be used for analyzing curriculum patterns and classifying CTE students. The second three analyses will focus on a nationally-representative sample of kindergarten students who participated in the ECLS-K. The research will employ hierarchal linear models (HLM) to measure change in math and science test scores. Fort the secondary students involved in CTE programs, individual growth curves for the FCAT math test scores of students will be explored. Then HLM will be used to estimate growth trajectories for students in CTE and non-CTE programs. Similarly, individual growth curves for standardized math and science IRT tests of the ECLS-K students will be explored and then HLM will be used to estimate growth trajectories. Mixed models, such as HLM, are normal theory models that include random effects and/or specific correlation structures among the dependent variables -- repeated measures and nested models are two common examples. These models are often used to control extraneous variation from naturally occurring clusters such as students within schools/communities or repeated measures on a subject.

Progress 10/01/12 to 09/30/13

Outputs
Target Audience: Nothing Reported Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided? Nothing Reported How have the results been disseminated to communities of interest? Nothing Reported What do you plan to do during the next reporting period to accomplish the goals? Nothing Reported

Impacts
What was accomplished under these goals? Due to other opportunities and changing priorities, no new research was initiated in the final year of the project. A very small amount of time was spent revising a draft of a journal article.

Publications


    Progress 10/01/08 to 09/30/13

    Outputs
    Target Audience: For the project period, 2008 - 2013, the target audiences included educational researchers and practitioners, expecially those with a rural focus. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided? Graduate students who were involved in the project developed skills in writing SAS macros to create new variables in datasets and in merging very large data files for multi-level statistical analysis. How have the results been disseminated to communities of interest? Presentations were made to interested members of four professional societies. These were the American Association for Agricultural Education, American Evaluation Association, Southern Rural Sociological Association, and the Rural Sociological Society. What do you plan to do during the next reporting period to accomplish the goals? Nothing Reported

    Impacts
    What was accomplished under these goals? In 2008-09, work on the project involved developing a partnership with the Florida Department of Education (FDOE). FDOE agreed to provide data from its data warehouse to allow the PIs to conduct studies on Career & Technical Education (CTE) students (n = ~75,000) and a sample of non-CTE students (n = ~75,000) in high schools. After obtaining the data, work was conducted to explore the data, e.g., examining growth curves of math achievement on the Florida math FCAT for individual students, assess data quality, and merge data elements into multi-level (i.e., community, school, student) analytic files. In addition, extensive work was conducted using student transcript data to develop key explanatory variables on level/type of CTE participation (occupational concentrator, occupational explorer, and coursetaker). One substantive study was completed, which compared student achievement on Florida's FCAT science test across CTE participants in the agriculture, health science, and technology education (STEM) occupational clusters. The initial data analysis revealed that students in agriculture programs scored slightly lower on the FCAT science test than those in health programs and somewhat lower than those in STEM programs. On the other hand, concentrators in agriculture programs scored on par with those in health programs and slightly lower than those in STEM programs after controlling for student and school factors. In 2009-10, the study initiated during the first year of the project was completed. Later, a fourth cluster, Education and Training was added to the analysis. This study was presented at the 2010 conference of the Southern Agricultural Education Research Conference and published in the proceedings. A second study which explores the science achievement of CTE and Non-CTE students across Florida's rural and urban areas also was conducted. The purpose was to examine the effects of community location on 11th grade standardized science test scores, as well as mediating compositional and structural attributes of schools and communities for CTE and non-CTE students in Florida. Using hierarchical linear modeling, we find that students living in the most rural locations (non-metropolitan counties with a town of less than 20,000 residents) scored on par with peers residing in more populous metropolitan and nonmetropolitan counties. In addition, CTE students who complete an occupational concentration showed higher achievement than non-concentrators and non-CTE students. The study, "Rural location effects on high school achievement," was presented at the 2010 conference of the Rural Sociological Society. Another study was conducted during the 2010-2011 to explore growth models for math achievement using test scores from 6th – 10th grade. The analysis showed that, controlling for a college prep curriculum and relevant demongraphics, CTE concentrators had higher initial scores than CTE explorers and the later had higher initial scores than CTE coursetakers. However, the slopes in the growth models were not significantly different. Furthermore, the findings of this study were causally confounded and, consequently, this line of research was discontinued. One paper was presented at the 2011 conference of the American Evaluation Association on “Evaluating curricular implementation and student achievement on mathematics achievement.” During 2010-2012, final edits were completed for the journal article, “CTE impact on science achievement: Does level of involvement and specialization matter?” which was published in Career and technical education research journal in 2012. No new research activities were conducted after 2011.

    Publications


      Progress 10/01/11 to 09/30/12

      Outputs
      OUTPUTS: During this period, final edits were completed for the journal article published in 2012. No new research activities were conducted. PARTICIPANTS: Nothing significant to report during this reporting period. TARGET AUDIENCES: Nothing significant to report during this reporting period. PROJECT MODIFICATIONS: Nothing significant to report during this reporting period.

      Impacts
      No outcomes/impacts to report at this time.

      Publications

      • Israel, G. D., Myers, B., *Lamm, A. J., & Galindo-Gonzalez, S. 2012. CTE impact on science achievement: Does level of involvement and specialization matter Career and Technical Education Research Journal, 37(1), 3-20. doi: 10.5328/cter37.1.3


      Progress 10/01/10 to 09/30/11

      Outputs
      OUTPUTS: I collected data for an experiment to test alternatives for obtaining survey responses via the Web and postal mail and analyzed the data for a fourth year. The Year 4 study built on the previous year's findings and focused on comparing two mixed-mode strategies with the traditional mail only approach for respondents who had previously provided both postal and email addresses. The mixed mode groups were 1) postal pre-letter followed by two email contacts and then a final postal follow-up with a paper survey and 2) three email contacts with a final postal follow-up. Data collection was on-going at the end of FY2011. Some results from the analysis of previously collected data were presented at the conference of the American Association for Public Opinion Research. The presentation focused on assessing differences in item nonresponse in questionnaires completed via the Web and paper forms (returned via the mail). This analysis was conducted because item nonresponse is an important dimension of data quality. The analysis used pooled data from 2008-2010. Overall item nonresponse was higher for paper questionnaires than for web questionnaires. In addition, question type also impacted item nonresponse with open-ended questions showing the highest rate of item nonresponse, followed by screened items. In the case of open-ended items, paper surveys had significantly higher item nonresponse than did the same items on the Web version of the survey. The findings from this study will be published in the April, 2012, issue of Survey Practice. I also attended the coordinating committee meeting and shared research results on used postal mail and the Web and ideas for improving responses to open-ended questions in surveys. PARTICIPANTS: Nothing significant to report during this reporting period. TARGET AUDIENCES: Nothing significant to report during this reporting period. PROJECT MODIFICATIONS: Nothing significant to report during this reporting period.

      Impacts
      Scientists who attended the presentation (n of approximately 50) learned about the effect of response mode (Web versus mail) on item nonresponse, which then helps them to make more informed decisions about survey design and implementation. In addition, I have incorporated the findings into a course on evaluation methods and in professional development workshops for Extension agents and specialists, so that graduate students and Extension faculty are better informed about options for conducting useful surveys.

      Publications

      • Israel, G. D. 2011. Strategies for Obtaining Survey Responses from Extension Clients: Exploring the Role of E-mail Requests. Journal of extension, 49(3), available at: http://www.joe.org/joe/2011june/a7.php.


      Progress 10/01/09 to 09/30/10

      Outputs
      OUTPUTS: Research continued on the project involving a partnership with the Florida Department of Education (FDOE). FDOE provided data from its data warehouse to allow the PIs to conduct studies on Career & Technical Education (CTE) students (n = ~75,000) and a sample of non-CTE students (n = ~75,000) in high schools. After obtaining the data, work was conducted to explore the data, create composite variables, and merge data elements into multi-level (i.e., community, school, student) analytic files. A study was completed, which compared student achievement on Florida's FCAT science test across CTE participants in the agriculture, health science, and technology education (STEM) occupational clusters. Later, a fourth cluster, Education and Training was added to the analysis. The data analysis revealed that students in agriculture programs scored slightly lower on the FCAT science test than those in health programs and somewhat lower than those in STEM programs. On the other hand, concentrators in agriculture programs scored on par with those in health programs and slightly lower than those in STEM programs after controlling for student and school factors. This study was presented at the conference of the Southern Agricultural Education Research Conference and published in the proceedings. A second study which explores the science achievement of CTE and Non-CTE students across Florida's rural and urban areas also was conducted. The purpose was to examine the effects of community location on 11th grade standardized science test scores, as well as mediating compositional and structural attributes of schools and communities for CTE and non-CTE students in Florida. Using hierarchical linear modeling, we find that students living in the most rural locations (non-metropolitan counties with a town of less than 20,000 residents) scored on par with peers residing in more populous metropolitan and nonmetropolitan counties. In addition, CTE students who complete an occupational concentration showed higher achievement than non-concentrators and non-CTE students. The study, "Rural location effects on high school achievement," was presented at the conference of the Rural Sociological Society. PARTICIPANTS: Nothing significant to report during this reporting period. TARGET AUDIENCES: Nothing significant to report during this reporting period. PROJECT MODIFICATIONS: Nothing significant to report during this reporting period.

      Impacts
      No outcomes/impacts to report at this time.

      Publications

      • Israel, G. D., Myers, B. E., Galindo-Gonzalez, S., & Lamm, A. J. 2010. Agricultural and Natural Resource CTE Programs and Science Achievement: How Does It Compare with Other CTE Programs 2010 Southern Region AAAE Conference Proceedings, pp. 256-271. Available at: http://aaaeonline.org/uploads/allconferences/2-5-2010_130_Final_Proce edings.pdf


      Progress 10/01/08 to 09/30/09

      Outputs
      OUTPUTS: Initial work on the project involved developing a partnership with the Florida Department of Education (FDOE). FDOE agreed to provide data from its data warehouse to allow the PIs to conduct studies on Career & Technical Education (CTE) students (n = ~75,000) and a sample of non-CTE students (n = ~75,000) in high schools. After obtaining the data, work was conducted to explore the data, e.g., examining growth curves of math achievement on the Florida math FCAT for individual students, assess data quality, and merge data elements into multi-level (i.e., community, school, student) analytic files. In addition, extensive work was conducted using student transcript data to develop key explanatory variables on level/type of CTE participation (occupational concentrator, occupational explorer, and coursetaker). One substantive study was completed, which compared student achievement on Florida's FCAT science test across CTE participants in the agriculture, health science, and technology education (STEM) occupational clusters. The data analysis revealed that students in agriculture programs scored slightly lower on the FCAT science test than those in health programs and somewhat lower than those in STEM programs. On the other hand, concentrators in agriculture programs scored on par with those in health programs and slightly lower than those in STEM programs after controlling for student and school factors. A second study which explores the science achievement of CTE and Non-CTE students across Florida's rural and urban areas was initiated. PARTICIPANTS: In addition to the PIs, two individuals (Sebastian Galindo-Gonzalez and Alexa Lamm) worked on the project, each worked 2.5 person months of data processing and analysis. These individuals also experienced professional development thorugh the experience gained with the project. A partner organization was the Florida Department of Education, which provided data for the research. A professor emeritus in statistics, Ramon Littell, joined the project team as a collaborator. He has advised the research team in conducting multi-level models using SAS. TARGET AUDIENCES: Nothing significant to report during this reporting period. PROJECT MODIFICATIONS: Nothing significant to report during this reporting period.

      Impacts
      No outcomes/impacts to report at this time.

      Publications

      • No publications reported this period