{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,16]],"date-time":"2026-02-16T09:11:46Z","timestamp":1771233106963,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":45,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,3,18]],"date-time":"2024-03-18T00:00:00Z","timestamp":1710720000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100006374","name":"National Science Foundation","doi-asserted-by":"publisher","award":["#DUE-2000405"],"award-info":[{"award-number":["#DUE-2000405"]}],"id":[{"id":"10.13039\/501100006374","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,3,18]]},"DOI":"10.1145\/3636555.3636890","type":"proceedings-article","created":{"date-parts":[[2024,3,5]],"date-time":"2024-03-05T18:11:20Z","timestamp":1709662280000},"page":"349-359","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":10,"title":["Investigating Algorithmic Bias on Bayesian Knowledge Tracing and Carelessness Detectors"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0692-1209","authenticated-orcid":false,"given":"Andres Felipe","family":"Zambrano","sequence":"first","affiliation":[{"name":"Graduate School of Education, University of Pennsylvania, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7334-4256","authenticated-orcid":false,"given":"Jiayi","family":"Zhang","sequence":"additional","affiliation":[{"name":"Graduate School of Education, University of Pennsylvania, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3051-3232","authenticated-orcid":false,"given":"Ryan S.","family":"Baker","sequence":"additional","affiliation":[{"name":"Graduate School of Education, University of Pennsylvania, USA"}]}],"member":"320","published-online":{"date-parts":[[2024,3,18]]},"reference":[{"key":"e_1_3_2_1_1_1","first-page":"33","article-title":"Predicting Student Participation in STEM Careers: The Role of Affect and Engagement during Middle School","volume":"12","author":"Victoria Almeda Ma.","year":"2020","unstructured":"Ma. Victoria Almeda and Ryan S. Baker. 2020. Predicting Student Participation in STEM Careers: The Role of Affect and Engagement during Middle School. Journal of Educational Data Mining 12, 2 (2020), 33\u201347.","journal-title":"Journal of Educational Data Mining"},{"key":"e_1_3_2_1_2_1","volume-title":"Proceedings of the 16th International Conference on Educational Data Mining.","author":"Almoubayyed Husni","year":"2023","unstructured":"Husni Almoubayyed, Stephen E. Fancsali, and Steve Ritter. 2023. Generalizing Predictive Models of Reading Ability in Adaptive Mathematics Software. In Proceedings of the 16th International Conference on Educational Data Mining."},{"key":"e_1_3_2_1_3_1","volume-title":"Big Data and Education","author":"Baker Ryan S.","unstructured":"Ryan S. Baker. 2023. Big Data and Education. 7th Edition. Philadelphia, PA: University of Pennsylvania.","edition":"7"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-69132-7_44"},{"key":"e_1_3_2_1_5_1","volume-title":"UMAP 2010, Big Island, HI, USA, June 20-24, 2010. Proceedings 18","author":"Baker Ryan S. J. d.","year":"2010","unstructured":"Ryan S. J. d. Baker, Albert T. Corbett, Sujith M Gowda, Angela Z Wagner, Benjamin A MacLaren, Linda R Kauffman, Aaron P Mitchell, and Stephen Giguere. 2010. Contextual slip and prediction of student performance after use of an intelligent tutor. In User Modeling, Adaptation, and Personalization: 18th International Conference, UMAP 2010, Big Island, HI, USA, June 20-24, 2010. Proceedings 18, Springer, 52\u201363."},{"key":"e_1_3_2_1_6_1","volume-title":"Baker and Aaron Hawn","author":"Ryan","year":"2022","unstructured":"Ryan S. Baker and Aaron Hawn. 2022. Algorithmic bias in education. International Journal of Artificial Intelligence in Education (2021), 1\u201341."},{"key":"e_1_3_2_1_7_1","volume-title":"Classification and regression trees","author":"Breiman Leo","unstructured":"Leo Breiman. 2017. Classification and regression trees. Routledge."},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1080\/08957347.2012.635502"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/VAST47406.2019.8986948"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"crossref","unstructured":"Nitesh V. Chawla Kevin W. Bowyer Lawrence O. Hall and W. Philip Kegelmeyer. 2002. SMOTE: synthetic minority over-sampling technique. Journal of artificial intelligence research 16 (2002) 321\u2013357.","DOI":"10.1613\/jair.953"},{"key":"e_1_3_2_1_11_1","volume-title":"Students","author":"Clement John","unstructured":"John Clement. 1982. Students\u2019 preconceptions in introductory mechanics. American Journal of physics 50, 1, 66\u201371."},{"key":"e_1_3_2_1_12_1","unstructured":"Kimberle Crenshaw. 1991. Race gender and sexual harassment. Sothern California Law Review 65."},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1007\/BF01099821"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1111\/bjet.13217"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1037\/h0045686"},{"key":"e_1_3_2_1_16_1","unstructured":"Stephen Fancsali. 2015. Confounding Carelessness? Exploring Causal Relationships Between Carelessness Affect Behavior and Learning in Cognitive Tutor Algebra Using Graphical Causal Models. In Educational Data Mining 508\u2013511."},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/3303772.3303791"},{"key":"e_1_3_2_1_18_1","first-page":"31","article-title":"When is deep learning the best approach to knowledge tracing","volume":"12","author":"Gervet Theophile","year":"2020","unstructured":"Theophile Gervet, Ken Koedinger, Jeff Schneider, Tom Mitchell, and others. 2020. When is deep learning the best approach to knowledge tracing? Journal of Educational Data Mining 12, 3 (2020), 31\u201354.","journal-title":"Journal of Educational Data Mining"},{"key":"e_1_3_2_1_19_1","first-page":"22","article-title":"Characterizing intersectional group fairness with worst-case comparisons. In Artificial Intelligence Diversity, Belonging, Equity, and Inclusion","volume":"14","author":"Ghosh Avijit","year":"2021","unstructured":"Avijit Ghosh, Lea Genuit, and Mary Reagan. 2021. Characterizing intersectional group fairness with worst-case comparisons. In Artificial Intelligence Diversity, Belonging, Equity, and Inclusion, Proceedings of Machine Learning Research 14, 22\u201334.","journal-title":"Proceedings of Machine Learning Research"},{"key":"e_1_3_2_1_20_1","volume-title":"Towards Fair Educational Data Mining: A Case Study on Detecting At-Risk Students","author":"Hu Qian","year":"2020","unstructured":"Qian Hu and Huzefa Rangwala. 2020. Towards Fair Educational Data Mining: A Case Study on Detecting At-Risk Students. International Educational Data Mining Society (2020)."},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-52240-7_23"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.18608\/jla.2023.7983"},{"key":"e_1_3_2_1_23_1","volume-title":"Kizilcec and Hansol Lee","author":"Ren\u00e9","year":"2022","unstructured":"Ren\u00e9 F. Kizilcec and Hansol Lee. 2022. Algorithmic fairness in education. In The ethics of artificial intelligence in education. Routledge, 174\u2013202."},{"key":"e_1_3_2_1_24_1","unstructured":"Matt J. Kusner Joshua Loftus Chris Russell and Ricardo Silva. 2017. Counterfactual fairness. Advances in neural information processing systems 30."},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/3576050.3576119"},{"key":"e_1_3_2_1_26_1","volume-title":"Scikit-learn: Machine learning in Python. Journal of machine Learning research 12","author":"Pedregosa Fabian","year":"2011","unstructured":"Fabian Pedregosa, Ga\u00ebl Varoquaux, Alexandre Gramfort, Vincent Michel, Bertrand Thirion, Olivier Grisel, Mathieu Blondel, Peter Prettenhofer, Ron Weiss, Vincent Dubourg, and others. 2011. Scikit-learn: Machine learning in Python. Journal of machine Learning research 12, (2011), 2825\u20132830."},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1111\/bjet.12156"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1007\/s40593-014-0034-8"},{"key":"e_1_3_2_1_29_1","first-page":"1","article-title":"Who's Learning? Using Demographics in EDM Research","volume":"12","author":"Paquette Luc","year":"2020","unstructured":"Luc Paquette, Jaclyn Ocumpaugh, Ziyue Li, Alexandra Andres, and Ryan Baker. 2020. Who's Learning? Using Demographics in EDM Research. Journal of Educational Data Mining 12, 3 (2020), 1\u201330.","journal-title":"Journal of Educational Data Mining"},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11257-017-9193-2"},{"key":"e_1_3_2_1_31_1","first-page":"249","volume-title":"Cognitive Tutor: Applied research in mathematics education. Psychonomic bulletin & review 14","author":"Ritter Steven","year":"2007","unstructured":"Steven Ritter, Jhon R. Anderson, Kenneth R. Koedinger, and Albert Corbett. 2007. Cognitive Tutor: Applied research in mathematics education. Psychonomic bulletin & review 14, 249-255."},{"issue":"1","key":"e_1_3_2_1_32_1","first-page":"1","article-title":"Unbias me! Mitigating Algorithmic Bias for Less-studied Demographic Groups in the Context of Language Learning Technology","volume":"6","author":"Rzepka Nathalie","year":"2023","unstructured":"Nathalie Rzepka, Linda Fernsel, Hans-Georg M\u00fcller, Katrarina Simbeck, and Niels Pinkwart. 2023. Unbias me! Mitigating Algorithmic Bias for Less-studied Demographic Groups in the Context of Language Learning Technology. Computer-Based Learning in Context 6, 1, 1-23.","journal-title":"Computer-Based Learning in Context"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"crossref","unstructured":"Nathalie Rzepka Katharina Simbeck Hans-Georg M\u00fcller and Niels Pinkwart. 2022. Fairness of In-session Dropout Prediction. In CSEDU (2) 316\u2013326.","DOI":"10.5220\/0010962100003182"},{"key":"e_1_3_2_1_34_1","volume-title":"Educational Data Mining","author":"San Pedro Maria Ofelia","year":"2013","unstructured":"Maria Ofelia San Pedro, Ryan Baker, Alex Bowers, and Neil Heffernan. 2013. Predicting college enrollment from student interaction with an intelligent tutoring system in middle school. In Educational Data Mining 2013."},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1007\/s40593-014-0015-y"},{"key":"e_1_3_2_1_36_1","unstructured":"Maria Ofelia San Pedro Jaclyn Ocumpaugh Ryan S Baker and Neil T Heffernan. 2014. Predicting STEM and Non-STEM College Major Enrollment from Middle School Interaction with Mathematics Educational Software. In Educational Data Mining 276\u2013279."},{"key":"e_1_3_2_1_37_1","volume-title":"Proceedings of the 28th International Conference on Computers in Education.","author":"Scruggs Richard","unstructured":"Richard Scruggs, Ryan S. Baker, and Bruce M. McLaren. 2020. Extending Deep Knowledge Tracing: Inferring Interpretable Knowledge and Predicting Post System Performance. In Proceedings of the 28th International Conference on Computers in Education."},{"key":"e_1_3_2_1_38_1","unstructured":"David Sculley Jasper Snoek Alex Wiltschko and Ali Rahimi. 2018. Winner's curse? On pace progress and empirical rigor."},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1109\/TLT.2022.3196278"},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/3506860.3506902"},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1145\/3531146.3533101"},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1145\/3430895.3460139"},{"key":"e_1_3_2_1_43_1","volume-title":"Educational data mining","author":"Yudelson Michael","year":"2014","unstructured":"Michael Yudelson, Steve Fancsali, Steve Ritter, Susan Berman, Tristan Nixon, and Ambarish Joshi. 2014. Better data beats big data. In Educational data mining 2014."},{"key":"e_1_3_2_1_44_1","volume-title":"Proceedings of the 14th International Conference on Educational Data Mining. EDM","author":"Zhang Jiayi","year":"2021","unstructured":"Jiayi Zhang, Rohini Das, Ryan Baker, and Richard Scruggs. 2021. Knowledge tracing models\u2019 predictive performance when a student starts a skill. In Proceedings of the 14th International Conference on Educational Data Mining. EDM, Paris, France, 625\u2013629."},{"key":"e_1_3_2_1_45_1","first-page":"76","article-title":"Using Machine Learning to Detect SMART Model Cognitive Operations in Mathematical Problem-Solving Process","volume":"14","author":"Zhang Jiayi","year":"2022","unstructured":"Jiayi Zhang, Juliana Ma. Alexandra L. Andres, Stephen Hutt, Ryan S. Baker, Jaclyn Ocumpaugh, Nidhi Nasiar, Caitlin Mills, Jamiella Brooks, Sheela Sethuaman, Tyron Young, and others. 2022. Using Machine Learning to Detect SMART Model Cognitive Operations in Mathematical Problem-Solving Process. Journal of Educational Data Mining 14, 3 (2022), 76\u2013108.","journal-title":"Journal of Educational Data Mining"}],"event":{"name":"LAK '24: The 14th Learning Analytics and Knowledge Conference","location":"Kyoto Japan","acronym":"LAK '24"},"container-title":["Proceedings of the 14th Learning Analytics and Knowledge Conference"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3636555.3636890","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3636555.3636890","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,17]],"date-time":"2025-09-17T01:15:51Z","timestamp":1758071751000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3636555.3636890"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,3,18]]},"references-count":45,"alternative-id":["10.1145\/3636555.3636890","10.1145\/3636555"],"URL":"https:\/\/doi.org\/10.1145\/3636555.3636890","relation":{},"subject":[],"published":{"date-parts":[[2024,3,18]]},"assertion":[{"value":"2024-03-18","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}