{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/120301"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/120301","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Image and text analytic systems for accessible online learning","abstract":"Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-09-01 without embargo terms","abstract_html":"Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-09-01 without embargo terms","abstract_has_math":false,"creators":["Li, Jiaxi"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Computer Science","degree_department":null,"school":null,"contributors":["Nahrstedt, Klara","Angrave, Lawrence"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2023,"date_issued":"2023-05","date_published":"2023-05","updated_at":"2026-07-22T22:24:57Z","subjects":["Online Learning","Accessibility","Image Analysis","Text Analysis"],"languages":["en","eng"],"rights":["Copyright 2023 Jiaxi Li"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2142/120301","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Nahrstedt, Klara","Angrave, Lawrence"]},{"key":"dc:creator","label":"Author","values":["Li, Jiaxi"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2023-05","2023-04-21"]},{"key":"dc:type","label":"Dc Type","values":["text","Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Computer Science"]},{"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":["Online Learning","Accessibility","Image Analysis","Text Analysis"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en","eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2023 Jiaxi Li"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2142/120301"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-09-01 without embargo terms","The student, Jiaxi Li, accepted the attached license on 2023-04-20 at 19:05.","The student, Jiaxi Li, submitted this Thesis for approval on 2023-04-20 at 19:26.","This Thesis was approved for publication on 2023-04-21 at 16:31.","DSpace SAF Submission Ingestion Package generated from Vireo submission #19076 on 2023-09-01 at 17:09:13","Online learning has been widely used for college-level education in recent years. Although many course platforms offer accessible features such as closed captioning and embedded forums, they are not sufficient to satisfy the demands of students who are deaf and hard of hearing, or are blind or have low vision, students who have difficulty attending in-person lectures, and students who have insufficient prerequisite knowledge. To provide an interactive, accessible, and inclusive learning experience for all students, image and text analytic systems were deployed on ClassTranscribe, a web-based learning platform, to extract useful image and text content from lecture videos in an accurate and efficient manner. Reusing, remixing and transforming on the extracted items enables the generation of multimodal accessibility features including 1) Visual-based lecture delivery, 2) Audio-based lecture delivery, and 3) A glossary application. Preliminary user study results indicated a general positive opinion among students who have utilized the accessibility features for lecture learning."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Image and text analytic systems for accessible online learning"]}]}],"canonical_facts":{"dc:contributor":["Nahrstedt, Klara","Angrave, Lawrence"],"dc:creator":["Li, Jiaxi"],"dc:date":["2023-05","2023-04-21"],"dc:description":["Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-09-01 without embargo terms","The student, Jiaxi Li, accepted the attached license on 2023-04-20 at 19:05.","The student, Jiaxi Li, submitted this Thesis for approval on 2023-04-20 at 19:26.","This Thesis was approved for publication on 2023-04-21 at 16:31.","DSpace SAF Submission Ingestion Package generated from Vireo submission #19076 on 2023-09-01 at 17:09:13","Online learning has been widely used for college-level education in recent years. Although many course platforms offer accessible features such as closed captioning and embedded forums, they are not sufficient to satisfy the demands of students who are deaf and hard of hearing, or are blind or have low vision, students who have difficulty attending in-person lectures, and students who have insufficient prerequisite knowledge. To provide an interactive, accessible, and inclusive learning experience for all students, image and text analytic systems were deployed on ClassTranscribe, a web-based learning platform, to extract useful image and text content from lecture videos in an accurate and efficient manner. Reusing, remixing and transforming on the extracted items enables the generation of multimodal accessibility features including 1) Visual-based lecture delivery, 2) Audio-based lecture delivery, and 3) A glossary application. Preliminary user study results indicated a general positive opinion among students who have utilized the accessibility features for lecture learning."],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/120301"],"dc:language":["en","eng"],"dc:rights":["Copyright 2023 Jiaxi Li"],"dc:subject":["Online Learning","Accessibility","Image Analysis","Text Analysis"],"dc:title":["Image and text analytic systems for accessible online learning"],"dc:type":["text","Thesis"],"thesis:degree_discipline":["Computer Science"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:24:57Z"}