{"id":{"repo_id":"lsu-thes","oai_identifier":"oai:repository.lsu.edu:gradschool_dissertations-1776"},"canonical_url":"https://search.dev.ndltd.org/etd/lsu-thes/oai:repository.lsu.edu:gradschool_dissertations-1776","repository":{"repo_id":"lsu-thes","name":"Lousiana State University","base_url":"https://repository.lsu.edu/do/oai/"},"display":{"title":"A study of dropout characteristics and school-level effects on dropout prevention","abstract":"This sequential, three-phase study used quantitative analyses to examine the characteristics of student dropouts and the characteristics of schools successful and unsuccessful in mediating dropouts. Narrative profiles were created to describe types of students and types of dropouts. Phase I consisted of three parts, each using the student as the unit of analysis. Part One examined the profile of all Louisiana dropouts. Part Two involved the creation of clusters of dropouts and non-dropouts combined. Part Three focused on the creation of dropout clusters. In Phase II, the percents of potential dropouts were calculated for 301 schools using the dropout characteristics from Phase I. The purpose of this phase was to classify schools into one of nine cells in a 3 x 3 contingency table that crossed three levels of Percent of Actual Dropouts with three levels of Percent of Potential Dropouts. In Phase III, a MANOVA was conducted using a 1 x 4 design. The levels of the independent variable were four school categories from the Phase II contingency table: consistently high dropouts schools, consistently low dropouts schools, schools more effective in dropout prevention, and schools less effective dropout prevention. The cluster analysis results for the non-dropouts and dropouts yielded three clusters: \"high achievers,\" \"average achievers,\" and \"low achievers.\" The cluster analysis for the dropouts also resulted in three clusters: \"quiet dropouts,\" \"typical\" dropouts, and \"high-achieving pushouts.\" The MANOVA produced overall significant differences among the set of dependent variables (attendance rate, class size, student achievement, suspension rate, teacher certification, and teacher test scores). The planned contrasts results showed that consistently low dropouts schools had significantly higher student achievement than the less effective schools, while the more effective schools had significantly higher attendance rates and student achievement than the consistently high dropouts schools. These findings have two major implications for dropout prevention. First, dropout prevention programs should have components that reach all types of potential dropouts. Second, more extensive efforts should be made to obtain the reasons individual students drop out. Students who drop out for like reasons could be studied to develop prevention measures for similar students.","abstract_html":"This sequential, three-phase study used quantitative analyses to examine the characteristics of student dropouts and the characteristics of schools successful and unsuccessful in mediating dropouts. Narrative profiles were created to describe types of students and types of dropouts. Phase I consisted of three parts, each using the student as the unit of analysis. Part One examined the profile of all Louisiana dropouts. Part Two involved the creation of clusters of dropouts and non-dropouts combined. Part Three focused on the creation of dropout clusters. In Phase II, the percents of potential dropouts were calculated for 301 schools using the dropout characteristics from Phase I. The purpose of this phase was to classify schools into one of nine cells in a 3 x 3 contingency table that crossed three levels of Percent of Actual Dropouts with three levels of Percent of Potential Dropouts. In Phase III, a MANOVA was conducted using a 1 x 4 design. The levels of the independent variable were four school categories from the Phase II contingency table: consistently high dropouts schools, consistently low dropouts schools, schools more effective in dropout prevention, and schools less effective dropout prevention. The cluster analysis results for the non-dropouts and dropouts yielded three clusters: "high achievers," "average achievers," and "low achievers." The cluster analysis for the dropouts also resulted in three clusters: "quiet dropouts," "typical" dropouts, and "high-achieving pushouts." The MANOVA produced overall significant differences among the set of dependent variables (attendance rate, class size, student achievement, suspension rate, teacher certification, and teacher test scores). The planned contrasts results showed that consistently low dropouts schools had significantly higher student achievement than the less effective schools, while the more effective schools had significantly higher attendance rates and student achievement than the consistently high dropouts schools. These findings have two major implications for dropout prevention. First, dropout prevention programs should have components that reach all types of potential dropouts. Second, more extensive efforts should be made to obtain the reasons individual students drop out. Students who drop out for like reasons could be studied to develop prevention measures for similar students.","abstract_has_math":false,"creators":["Crain-Dorough, Mindy L."],"institution":"Educational Leadership, Research and Counseling","degree_name":"Doctor of Philosophy (PhD)","degree_level":"Dissertation","degree_discipline":"Education","degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2003,"date_issued":"2003-01-01T08:00:00Z","date_published":"2003-01-01T08:00:00Z","updated_at":"2026-07-24T02:58:17Z","subjects":["reasons for dropping out","cluster analysis","dropout types","dropouts and ethnicity"],"languages":[],"rights":["unrestricted","Release the entire work immediately for access worldwide."],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["etd-0710103-021510","https://repository.lsu.edu/gradschool_dissertations/777"],"render_values":[{"text":"etd-0710103-021510","href":null,"code":true},{"text":"https://repository.lsu.edu/gradschool_dissertations/777","href":"https://repository.lsu.edu/gradschool_dissertations/777","code":true}]}]},"links":{"outbound_url":"https://doi.org/10.31390/gradschool_dissertations.777","outbound_label":"DOI","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Crain-Dorough, Mindy L."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2003-06-30"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2022-05-12T23:09:57Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Education"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Philosophy (PhD)"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["Educational Leadership, Research and Counseling"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["reasons for dropping out","cluster analysis","dropout types","dropouts and ethnicity"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["unrestricted","Release the entire work immediately for access worldwide."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["etd-0710103-021510","10.31390/gradschool_dissertations.777","https://repository.lsu.edu/gradschool_dissertations/777"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["This sequential, three-phase study used quantitative analyses to examine the characteristics of student dropouts and the characteristics of schools successful and unsuccessful in mediating dropouts. Narrative profiles were created to describe types of students and types of dropouts. Phase I consisted of three parts, each using the student as the unit of analysis. Part One examined the profile of all Louisiana dropouts. Part Two involved the creation of clusters of dropouts and non-dropouts combined. Part Three focused on the creation of dropout clusters. In Phase II, the percents of potential dropouts were calculated for 301 schools using the dropout characteristics from Phase I. The purpose of this phase was to classify schools into one of nine cells in a 3 x 3 contingency table that crossed three levels of Percent of Actual Dropouts with three levels of Percent of Potential Dropouts. In Phase III, a MANOVA was conducted using a 1 x 4 design. The levels of the independent variable were four school categories from the Phase II contingency table: consistently high dropouts schools, consistently low dropouts schools, schools more effective in dropout prevention, and schools less effective dropout prevention. The cluster analysis results for the non-dropouts and dropouts yielded three clusters: \"high achievers,\" \"average achievers,\" and \"low achievers.\" The cluster analysis for the dropouts also resulted in three clusters: \"quiet dropouts,\" \"typical\" dropouts, and \"high-achieving pushouts.\" The MANOVA produced overall significant differences among the set of dependent variables (attendance rate, class size, student achievement, suspension rate, teacher certification, and teacher test scores). The planned contrasts results showed that consistently low dropouts schools had significantly higher student achievement than the less effective schools, while the more effective schools had significantly higher attendance rates and student achievement than the consistently high dropouts schools. These findings have two major implications for dropout prevention. First, dropout prevention programs should have components that reach all types of potential dropouts. Second, more extensive efforts should be made to obtain the reasons individual students drop out. Students who drop out for like reasons could be studied to develop prevention measures for similar students."]},{"key":"dc:title","label":"Title","values":["A study of dropout characteristics and school-level effects on dropout prevention"]}]}],"canonical_facts":{"dc:creator":["Crain-Dorough, Mindy L."],"dc:date":["2003-06-30"],"dc:date.available":["2022-05-12T23:09:57Z"],"dc:description.abstract":["This sequential, three-phase study used quantitative analyses to examine the characteristics of student dropouts and the characteristics of schools successful and unsuccessful in mediating dropouts. Narrative profiles were created to describe types of students and types of dropouts. Phase I consisted of three parts, each using the student as the unit of analysis. Part One examined the profile of all Louisiana dropouts. Part Two involved the creation of clusters of dropouts and non-dropouts combined. Part Three focused on the creation of dropout clusters. In Phase II, the percents of potential dropouts were calculated for 301 schools using the dropout characteristics from Phase I. The purpose of this phase was to classify schools into one of nine cells in a 3 x 3 contingency table that crossed three levels of Percent of Actual Dropouts with three levels of Percent of Potential Dropouts. In Phase III, a MANOVA was conducted using a 1 x 4 design. The levels of the independent variable were four school categories from the Phase II contingency table: consistently high dropouts schools, consistently low dropouts schools, schools more effective in dropout prevention, and schools less effective dropout prevention. The cluster analysis results for the non-dropouts and dropouts yielded three clusters: \"high achievers,\" \"average achievers,\" and \"low achievers.\" The cluster analysis for the dropouts also resulted in three clusters: \"quiet dropouts,\" \"typical\" dropouts, and \"high-achieving pushouts.\" The MANOVA produced overall significant differences among the set of dependent variables (attendance rate, class size, student achievement, suspension rate, teacher certification, and teacher test scores). The planned contrasts results showed that consistently low dropouts schools had significantly higher student achievement than the less effective schools, while the more effective schools had significantly higher attendance rates and student achievement than the consistently high dropouts schools. These findings have two major implications for dropout prevention. First, dropout prevention programs should have components that reach all types of potential dropouts. Second, more extensive efforts should be made to obtain the reasons individual students drop out. Students who drop out for like reasons could be studied to develop prevention measures for similar students."],"dc:identifier":["etd-0710103-021510","10.31390/gradschool_dissertations.777","https://repository.lsu.edu/gradschool_dissertations/777"],"dc:rights":["unrestricted","Release the entire work immediately for access worldwide."],"dc:subject":["reasons for dropping out","cluster analysis","dropout types","dropouts and ethnicity"],"dc:title":["A study of dropout characteristics and school-level effects on dropout prevention"],"thesis:degree_discipline":["Education"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Doctor of Philosophy (PhD)"],"thesis:institution_name":["Educational Leadership, Research and Counseling"]},"updated_at":"2026-07-24T02:58:17Z"}