{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/97795"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/97795","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"FFA membership growth compared to a changing and growing student population","abstract":"This study compares National FFA membership growth to the growth of the overall student population (percentage growth change, PGC) by state and region from 1990 to 2014 using data provided by the National FFA Organization and the National Center for Education Statistics (NCES). Using Ragin’s (1987) method of Qualitative Comparative Analysis (QCA), student population growth and demographic changes in student race/ethnicity, locale, and free and reduced-price lunch were compared to FFA membership growth by state and region. The QCA method was also used to measure the effects of the National FFA Organization’s affiliation program. The Central Region had the largest increase in FFA membership PGC while the Southern Region had negative FFA membership PGC. Only 6% of states have both high student population growth and high FFA membership measured as a percentage of the student population. Of the states with higher FFA membership percentages, 74% also had larger White student populations, and 89% have larger rural or town student populations. Only one state using the affiliation program had negative FFA membership PGC while 22 states utilizing the affiliation program had positive FFA membership PGC.","abstract_html":"This study compares National FFA membership growth to the growth of the overall student population (percentage growth change, PGC) by state and region from 1990 to 2014 using data provided by the National FFA Organization and the National Center for Education Statistics (NCES). Using Ragin’s (1987) method of Qualitative Comparative Analysis (QCA), student population growth and demographic changes in student race/ethnicity, locale, and free and reduced-price lunch were compared to FFA membership growth by state and region. The QCA method was also used to measure the effects of the National FFA Organization’s affiliation program. The Central Region had the largest increase in FFA membership PGC while the Southern Region had negative FFA membership PGC. Only 6% of states have both high student population growth and high FFA membership measured as a percentage of the student population. Of the states with higher FFA membership percentages, 74% also had larger White student populations, and 89% have larger rural or town student populations. Only one state using the affiliation program had negative FFA membership PGC while 22 states utilizing the affiliation program had positive FFA membership PGC.","abstract_has_math":false,"creators":["Currie, Blaze Kelton"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Agricultural Education","degree_department":null,"school":null,"contributors":["Thieman, Erica B."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2017,"date_issued":"2017-08-10T20:33:28Z","date_published":"2017-08-10T20:33:28Z","updated_at":"2026-07-22T22:24:34Z","subjects":["Future Farmers of America (FFA) membership","National Future Farmers of America (FFA) Organization","Student population growth","Qualitative comparative analysis"],"languages":["eng"],"rights":["Copyright 2017 Blaze Currie"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/97795","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Thieman, Erica B."]},{"key":"dc:creator","label":"Author","values":["Currie, Blaze Kelton"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2017-08-10T20:33:28Z","2019-08-11T09:15:21Z","2017-04-27","2017-05"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Agricultural Education"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Future Farmers of America (FFA) membership","National Future Farmers of America (FFA) Organization","Student population growth","Qualitative comparative analysis"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2017 Blaze Currie"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/97795"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["This study compares National FFA membership growth to the growth of the overall student population (percentage growth change, PGC) by state and region from 1990 to 2014 using data provided by the National FFA Organization and the National Center for Education Statistics (NCES). Using Ragin’s (1987) method of Qualitative Comparative Analysis (QCA), student population growth and demographic changes in student race/ethnicity, locale, and free and reduced-price lunch were compared to FFA membership growth by state and region. The QCA method was also used to measure the effects of the National FFA Organization’s affiliation program. The Central Region had the largest increase in FFA membership PGC while the Southern Region had negative FFA membership PGC. Only 6% of states have both high student population growth and high FFA membership measured as a percentage of the student population. Of the states with higher FFA membership percentages, 74% also had larger White student populations, and 89% have larger rural or town student populations. Only one state using the affiliation program had negative FFA membership PGC while 22 states utilizing the affiliation program had positive FFA membership PGC.","Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2019-05-01","The student, Blaze Currie, accepted the attached license on 2017-04-26 at 16:23.","The student, Blaze Currie, submitted this Thesis for approval on 2017-04-26 at 16:36.","This Thesis was approved for publication on 2017-04-27 at 14:49.","DSpace SAF Submission Ingestion Package generated from Vireo submission #11099 on 2017-08-10 at 15:07:11","Made available in DSpace on 2017-08-10T20:33:28Z (GMT). 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Using Ragin’s (1987) method of Qualitative Comparative Analysis (QCA), student population growth and demographic changes in student race/ethnicity, locale, and free and reduced-price lunch were compared to FFA membership growth by state and region. The QCA method was also used to measure the effects of the National FFA Organization’s affiliation program. The Central Region had the largest increase in FFA membership PGC while the Southern Region had negative FFA membership PGC. Only 6% of states have both high student population growth and high FFA membership measured as a percentage of the student population. Of the states with higher FFA membership percentages, 74% also had larger White student populations, and 89% have larger rural or town student populations. Only one state using the affiliation program had negative FFA membership PGC while 22 states utilizing the affiliation program had positive FFA membership PGC.","Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2019-05-01","The student, Blaze Currie, accepted the attached license on 2017-04-26 at 16:23.","The student, Blaze Currie, submitted this Thesis for approval on 2017-04-26 at 16:36.","This Thesis was approved for publication on 2017-04-27 at 14:49.","DSpace SAF Submission Ingestion Package generated from Vireo submission #11099 on 2017-08-10 at 15:07:11","Made available in DSpace on 2017-08-10T20:33:28Z (GMT). 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