{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T02:31:56Z","timestamp":1773973916189,"version":"3.50.1"},"reference-count":43,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"am","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"name":"NSF","award":["2323419"],"award-info":[{"award-number":["2323419"]}]},{"name":"NSF","award":["2205891"],"award-info":[{"award-number":["2205891"]}]},{"name":"NSF","award":["2235731"],"award-info":[{"award-number":["2235731"]}]},{"DOI":"10.13039\/100000183","name":"Army Research Office under Cooperative Agreement","doi-asserted-by":"publisher","award":["W911NF-24-2-0133"],"award-info":[{"award-number":["W911NF-24-2-0133"]}],"id":[{"id":"10.13039\/100000183","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2025]]},"DOI":"10.1109\/access.2025.3568171","type":"journal-article","created":{"date-parts":[[2025,5,8]],"date-time":"2025-05-08T17:40:01Z","timestamp":1746726001000},"page":"82407-82420","source":"Crossref","is-referenced-by-count":2,"title":["Improving Student Learning Outcome Tracing at HBCUs Using Tabular Generative AI and Deep Knowledge Tracing"],"prefix":"10.1109","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-1490-1107","authenticated-orcid":false,"given":"Ming-Mu","family":"Kuo","sequence":"first","affiliation":[{"name":"ECE Department, CREDIT Center, Prairie View A&#x0026;M University, Prairie View, TX, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-1548-055X","authenticated-orcid":false,"given":"Xiangfang","family":"Li","sequence":"additional","affiliation":[{"name":"ECE Department, CREDIT Center, Prairie View A&#x0026;M University, Prairie View, TX, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pamela","family":"Obiomon","sequence":"additional","affiliation":[{"name":"ECE Department, CREDIT Center, Prairie View A&#x0026;M University, Prairie View, TX, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1577-3359","authenticated-orcid":false,"given":"Lijun","family":"Qian","sequence":"additional","affiliation":[{"name":"ECE Department, CREDIT Center, Prairie View A&#x0026;M University, Prairie View, TX, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3742-0071","authenticated-orcid":false,"given":"Xishuang","family":"Dong","sequence":"additional","affiliation":[{"name":"ECE Department, CREDIT Center, Prairie View A&#x0026;M University, Prairie View, TX, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","volume-title":"Examination of Athletic Academic Support Services of NCAA DI HBCUs","author":"Harrell","year":"2020"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.5771\/9781475818970"},{"key":"ref3","volume-title":"COE\u2014Undergraduate Retention and Graduation Rates","year":"2021"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.5555\/2969239.2969296"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ICCOINS49721.2021.9497185"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/3038912.3052580"},{"key":"ref7","first-page":"384","article-title":"A self-attentive model for knowledge tracing","volume-title":"Proc. 12th Int. Conf. Educ. Data Mining","author":"Pandey"},{"key":"ref8","first-page":"156","article-title":"Graph-based knowledge tracing: Modeling Student proficiency using graph neural network","volume-title":"Proc. IEEE\/WIC\/ACM Int. Conf. Web Intell. (WI)","author":"Nakagawa"},{"key":"ref9","article-title":"Modeling tabular data using conditional GAN","author":"Xu","year":"2019","journal-title":"arXiv:1907.00503"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1312.6114"},{"key":"ref11","article-title":"Denoising diffusion probabilistic models","author":"Ho","year":"2020","journal-title":"arXiv:2006.11239"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1177\/21582440241242180"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyg.2021.698490"},{"key":"ref14","article-title":"Mixed-type tabular data synthesis with score-based diffusion in latent space","author":"Zhang","year":"2023","journal-title":"arXiv:2310.09656"},{"key":"ref15","article-title":"Language models are realistic tabular data generators","author":"Borisov","year":"2022","journal-title":"arXiv:2210.06280"},{"key":"ref16","article-title":"TabDDPM: Modelling tabular data with diffusion models","author":"Kotelnikov","year":"2022","journal-title":"arXiv:2209.15421"},{"key":"ref17","article-title":"STaSy: Score-based tabular data synthesis","author":"Kim","year":"2022","journal-title":"arXiv:2210.04018"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1145\/3303772.3303786"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1145\/3231644.3231647"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1145\/3386527.3405945"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1080\/01969722.2023.2166259"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1016\/j.matpr.2021.07.382"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1080\/01969722.2023.2166243"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2024.3446653"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1016\/j.stueduc.2024.101406"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TELFOR59449.2023.10372727"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-97-6810-3_8"},{"key":"ref28","article-title":"Generative adversarial networks","author":"Goodfellow","year":"2014","journal-title":"arXiv:1406.2661"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2017.2765202"},{"key":"ref30","article-title":"Tutorial on variational autoencoders","author":"Doersch","year":"2016","journal-title":"arXiv:1606.05908"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM59182.2024.00040"},{"key":"ref32","article-title":"Improved denoising diffusion probabilistic models","author":"Nichol","year":"2021","journal-title":"arXiv:2102.09672"},{"key":"ref33","article-title":"Machine learning for synthetic data generation: A review","author":"Lu","year":"2023","journal-title":"arXiv:2302.04062"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2024.112223"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1145\/3569576"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1186\/s40537-020-00305-w"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/VAST.2015.7347684"},{"key":"ref38","article-title":"TabDiff: A mixed-type diffusion model for tabular data generation","author":"Shi","year":"2024","journal-title":"arXiv:2410.20626"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.4236\/am.2020.113018"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1186\/s13040-021-00244-z"},{"key":"ref41","article-title":"Better to be in agreement than in bad company: A critical analysis of many kappa-like tests assessing one-million 2\u00d72 contingency tables","author":"Sergio Panse Silveira","year":"2022","journal-title":"arXiv:2203.09628"},{"key":"ref42","volume-title":"Deep Learning","author":"Goodfellow","year":"2016"},{"key":"ref43","article-title":"Score-based generative modeling through stochastic differential equations","author":"Song","year":"2020","journal-title":"arXiv:2011.13456"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"https:\/\/ieeexplore.ieee.org\/ielam\/6287639\/10820123\/10993361-aam.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6287639\/10820123\/10993361.pdf?arnumber=10993361","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,16]],"date-time":"2025-05-16T17:46:17Z","timestamp":1747417577000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10993361\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":43,"URL":"https:\/\/doi.org\/10.1109\/access.2025.3568171","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]}}}