2026-09-20T09:25:51Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/73022 2023-07-11 col_2142_5131 col_2142_10761 com_2142_5130 com_2142_10755 com_2142_234

Zilles, Craig Xu, Tianning 2015-01-21T19:56:10Z 2015-01-21T19:56:10Z 2017-01-22T10:15:29Z 2014-12 2015-01-21 2014-12 Four studies were conducted using different data analytic techniques to give insight into how undergraduate students perform in their required courses in the computer science sequence at the University of Illinois at Urbana-Champaign. Undergraduate student data from students who majored in computer science were collected for the length of time they remained in the computer science department. Principal Components Analysis was used to determine the general patterns behind student grades as they progressed in the major, looking at whether student grades were an indication of what kind of students they were, or how much prior experience they had, or the courses that they took when they reached Illinois. Decision trees were used to determine the factors that can be used to make predictions about whether students would fail a difficult upper level course, so that vulnerable students might be detected ahead of time to be provided with extra help and resources. Current students already in the computer science program were examined to determine if there should be a threshold technical GPA for being allowed to take higher level computer science courses, by looking at the factors behind a student repeating upper level computer science courses. Finally, Support Vector Machine was used to examine and critique the current rules for letting undergraduates transfer into the computer science major, to determine whether the current standards make sense with the pattern of student performance in previous courses and whether those standards’ threshold are accurate enough for predicting their success should they transfer. Item withdrawn by Laura Spradlin (lspradl2@illinois.edu) on 2014-12-10T14:22:52Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 2 Xu_Tianning.docx: 1453752 bytes, checksum: 81d2ca5cd24a59e9dad6f4828bf78ec2 (MD5) Xu_Tianning.pdf: 1656165 bytes, checksum: 65fa1e5d7e0e7e1aa0fbac7b1c98cabb (MD5) Made available in DSpace on 2015-01-21T19:56:10Z (GMT). No. of bitstreams: 2 Tianning_Xu.pdf: 1656165 bytes, checksum: 65fa1e5d7e0e7e1aa0fbac7b1c98cabb (MD5) Xu_Tianning.docx: 1453752 bytes, checksum: 81d2ca5cd24a59e9dad6f4828bf78ec2 (MD5) Embargo set by: Seth Robbins for item 73211 Lift date: 2017-01-21T19:56:18Z Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD system U of I Only Restriction Lifted for Item 73211 on 2017-01-22T10:15:29Z. http://hdl.handle.net/2142/73022 en Copyright 2014 Tianning Xu Principal Component Analysis Support Vector Machine Decision Tree Computer Science Undergraduates Using data analytics to examine undergraduate computer science student course performance text Computer Science 1434 Computer Science 0112 University of Illinois at Urbana-Champaign Thesis M.S. MS:Computer Science -UIUC 10KS0112MS