{"id":{"repo_id":"denver","oai_identifier":"oai:digitalcommons.du.edu:etd-2071"},"canonical_url":"https://search.dev.ndltd.org/etd/denver/oai:digitalcommons.du.edu:etd-2071","repository":{"repo_id":"denver","name":"University of Denver","base_url":"https://digitalcommons.du.edu/do/oai/"},"display":{"title":"Culturally and Linguistically Diverse Students' Standardized English Literacy Achievement and Language Redesignation Status: A Multiple Regression Analysis","abstract":"<p>The initial <em>No Child Left Behind</em> (NCLB) legislation stated that by 2014 <em>all</em> students would reach proficiency in all subjects. However, this has not been the case as NCLB has had mixed effects for culturally and linguistically diverse students (CLDs) (Hopkins, Thompson, Linquanti, Hakuta, & August, 2013). Language redesignation policies, often termed reclassification, can be considered a significant contributor as the variation in policies and practices alone has led to significantly different achievement for CLDs across the country (Hill, Weston, & Hayes, 2014; Mahoney & MacSwan, 2005) and has created an expansive achievement gap with their non-CLD White counterparts (Reardon, 2011; U.S. Department of Education, 2012). This dissertation utilizes asset-based and systems theories to refute current language redesignation policies employed for CLDs. Additionally, Cummins' (1979, 1981) developmental interdependence hypothesis serves as a theoretical framework. Multiple and hierarchical regression analyses are employed to predict CLDs' longitudinal literacy achievement in English based on language redesignation status (exited or still receiving language services), prior English language proficiency (ELP) data, native language literacy proficiency at kindergarten exit, and prior standardized English literacy achievement. By explaining the variance associated with the most significant predictors, this empirical model could provide policymakers with an evidence-based approach to the language redesignation policy framework. Specifically, those variables that are the most significant in predicting long-term achievement should be included, while new variables, such as native language literacy proficiency are identified for potential inclusion. The substantive implications of these models will provide policymakers with an objective, evidence-based process for language redesignation of CLDs into mainstream English classrooms based on longitudinal achievement data and statistical analyses.</p>","abstract_html":"&lt;p&gt;The initial &lt;em&gt;No Child Left Behind&lt;/em&gt; (NCLB) legislation stated that by 2014 &lt;em&gt;all&lt;/em&gt; students would reach proficiency in all subjects. However, this has not been the case as NCLB has had mixed effects for culturally and linguistically diverse students (CLDs) (Hopkins, Thompson, Linquanti, Hakuta, &amp; August, 2013). Language redesignation policies, often termed reclassification, can be considered a significant contributor as the variation in policies and practices alone has led to significantly different achievement for CLDs across the country (Hill, Weston, &amp; Hayes, 2014; Mahoney &amp; MacSwan, 2005) and has created an expansive achievement gap with their non-CLD White counterparts (Reardon, 2011; U.S. Department of Education, 2012). This dissertation utilizes asset-based and systems theories to refute current language redesignation policies employed for CLDs. Additionally, Cummins&#x27; (1979, 1981) developmental interdependence hypothesis serves as a theoretical framework. Multiple and hierarchical regression analyses are employed to predict CLDs&#x27; longitudinal literacy achievement in English based on language redesignation status (exited or still receiving language services), prior English language proficiency (ELP) data, native language literacy proficiency at kindergarten exit, and prior standardized English literacy achievement. By explaining the variance associated with the most significant predictors, this empirical model could provide policymakers with an evidence-based approach to the language redesignation policy framework. Specifically, those variables that are the most significant in predicting long-term achievement should be included, while new variables, such as native language literacy proficiency are identified for potential inclusion. The substantive implications of these models will provide policymakers with an objective, evidence-based process for language redesignation of CLDs into mainstream English classrooms based on longitudinal achievement data and statistical analyses.&lt;/p&gt;","abstract_has_math":false,"creators":["Weyer, Matthew R."],"institution":null,"degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":null,"degree_department":null,"school":null,"contributors":["Kristina Hesbol, Ph.D.","Susan Korach","Ryan Gildersleeve","Nicole Nicotera","Kent Seidel"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2015,"date_issued":"2015-01-01T08:00:00Z","date_published":"2015-01-01T08:00:00Z","updated_at":"2026-07-24T02:03:03Z","subjects":["Asset-based thinking","Cultural","Linguistics","Diverse students","Education policy","English language learners","English learners","Language redesignation","Education","Educational Leadership"],"languages":["en"],"rights":["<p>Copyright is held by the author. 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Language redesignation policies, often termed reclassification, can be considered a significant contributor as the variation in policies and practices alone has led to significantly different achievement for CLDs across the country (Hill, Weston, & Hayes, 2014; Mahoney & MacSwan, 2005) and has created an expansive achievement gap with their non-CLD White counterparts (Reardon, 2011; U.S. Department of Education, 2012). This dissertation utilizes asset-based and systems theories to refute current language redesignation policies employed for CLDs. Additionally, Cummins' (1979, 1981) developmental interdependence hypothesis serves as a theoretical framework. Multiple and hierarchical regression analyses are employed to predict CLDs' longitudinal literacy achievement in English based on language redesignation status (exited or still receiving language services), prior English language proficiency (ELP) data, native language literacy proficiency at kindergarten exit, and prior standardized English literacy achievement. By explaining the variance associated with the most significant predictors, this empirical model could provide policymakers with an evidence-based approach to the language redesignation policy framework. Specifically, those variables that are the most significant in predicting long-term achievement should be included, while new variables, such as native language literacy proficiency are identified for potential inclusion. The substantive implications of these models will provide policymakers with an objective, evidence-based process for language redesignation of CLDs into mainstream English classrooms based on longitudinal achievement data and statistical analyses.</p>"]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Culturally and Linguistically Diverse Students' Standardized English Literacy Achievement and Language Redesignation Status: A Multiple Regression Analysis"]}]}],"canonical_facts":{"dc:contributor":["Kristina Hesbol, Ph.D.","Susan Korach","Ryan Gildersleeve","Nicole Nicotera","Kent Seidel"],"dc:creator":["Weyer, Matthew R."],"dc:date.available":["2017-02-13T08:00:00Z"],"dc:description.abstract":["<p>The initial <em>No Child Left Behind</em> (NCLB) legislation stated that by 2014 <em>all</em> students would reach proficiency in all subjects. However, this has not been the case as NCLB has had mixed effects for culturally and linguistically diverse students (CLDs) (Hopkins, Thompson, Linquanti, Hakuta, & August, 2013). Language redesignation policies, often termed reclassification, can be considered a significant contributor as the variation in policies and practices alone has led to significantly different achievement for CLDs across the country (Hill, Weston, & Hayes, 2014; Mahoney & MacSwan, 2005) and has created an expansive achievement gap with their non-CLD White counterparts (Reardon, 2011; U.S. Department of Education, 2012). This dissertation utilizes asset-based and systems theories to refute current language redesignation policies employed for CLDs. Additionally, Cummins' (1979, 1981) developmental interdependence hypothesis serves as a theoretical framework. Multiple and hierarchical regression analyses are employed to predict CLDs' longitudinal literacy achievement in English based on language redesignation status (exited or still receiving language services), prior English language proficiency (ELP) data, native language literacy proficiency at kindergarten exit, and prior standardized English literacy achievement. By explaining the variance associated with the most significant predictors, this empirical model could provide policymakers with an evidence-based approach to the language redesignation policy framework. Specifically, those variables that are the most significant in predicting long-term achievement should be included, while new variables, such as native language literacy proficiency are identified for potential inclusion. The substantive implications of these models will provide policymakers with an objective, evidence-based process for language redesignation of CLDs into mainstream English classrooms based on longitudinal achievement data and statistical analyses.</p>"],"dc:format":["application/pdf"],"dc:identifier":["https://digitalcommons.du.edu/etd/1071"],"dc:language":["en"],"dc:rights":["<p>Copyright is held by the author. User is responsible for all copyright compliance.</p>"],"dc:subject":["Asset-based thinking","Cultural","Linguistics","Diverse students","Education policy","English language learners","English learners","Language redesignation","Education","Educational Leadership"],"dc:title":["Culturally and Linguistically Diverse Students' Standardized English Literacy Achievement and Language Redesignation Status: A Multiple Regression Analysis"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Ph.D."]},"updated_at":"2026-07-24T02:03:03Z"}