{"id":676,"date":"2022-07-24T10:41:53","date_gmt":"2022-07-24T10:41:53","guid":{"rendered":"https:\/\/educationaldatamining.org\/edm2022\/?page_id=676"},"modified":"2022-07-24T10:44:22","modified_gmt":"2022-07-24T10:44:22","slug":"nominated-best-papers","status":"publish","type":"page","link":"https:\/\/educationaldatamining.org\/edm2022\/nominated-best-papers\/","title":{"rendered":"Nominated Best Papers"},"content":{"rendered":"\n<p><strong>Best paper nominees \u2013 Full<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\"><li>Predicting Reading Comprehension Scores of Elementary School Students<ul><li>Yuyang Nie, Helene Deacon, Alona Fyshe and Carrie Demmans Epp (Session 4, July 24)<br><\/li><\/ul><\/li><li>Addressing Competing Objectives in Allocating Funds to Scholarships and Need-based Financial Aid<ul><li>Vinthuy Phan, Laura Wright and Bridgette Decent (Session 5, July 24)<br><\/li><\/ul><\/li><li>Detecting SMART Model Cognitive Operations in Mathematical Problem-Solving Process<ul><li>Jiayi Zhang, Juliana Ma. Alexandra L. Andres, Stephen Hutt, Ryan S. Baker, Jaclyn Ocumpaugh, Caitlin Mills, Jamiella Brooks, Sheela Sethuraman and Tyron Young (Session 10, July 25)<br><\/li><\/ul><\/li><li>Investigating Temporal Dynamics Underlying Successful Collaborative Problem Solving Behaviors with Multilevel Vector Autoregression<ul><li>Guojing Zhou, Robert Moulder, Chen Sun and Sidney D\u2019Mello (Session 14, July 26)<\/li><\/ul><\/li><\/ul>\n\n\n\n<p><\/p>\n\n\n\n<p><\/p>\n\n\n\n<p><strong>Best paper nominees \u2013 Short<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\"><li>Admitting you have a problem is the first step: Modeling when and why students seek help in programming assignments<ul><li>Zhikai Gao, Bradley Erickson, Yiqiao Xu, Collin Lynch, Sarah Heckman and Tiffany Barnes (Session 6, July 24)<br><\/li><\/ul><\/li><li>Towards Real Interpretability of Student Success Prediction Combining Methods of XAI and Social Science<ul><li>Lea Cohausz (Session 7, July 24)<br><\/li><\/ul><\/li><li>The AI Teacher Test: Measuring the Pedagogical Ability of Blender and GPT-3 in Educational Dialogues<ul><li>Ana\u00efs Tack and Chris Piech (Session 9, July 25)<br><\/li><\/ul><\/li><li>Log mining for course recommendation in limited information scenarios<ul><li>Juan Sanguino, Ruben Manrique, Olga Mari\u00f1o, Mario Linares and Nicolas Cardozo (Session 13, July 26)<\/li><\/ul><\/li><\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Best paper nominees \u2013 Full Predicting Reading Comprehension Scores of Elementary School Students Yuyang Nie, Helene Deacon, Alona Fyshe and Carrie Demmans Epp (Session 4,<a href=\"https:\/\/educationaldatamining.org\/edm2022\/nominated-best-papers\/\" class=\"more-link\">View More<\/a><\/p>\n","protected":false},"author":13,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-676","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/educationaldatamining.org\/edm2022\/wp-json\/wp\/v2\/pages\/676","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/educationaldatamining.org\/edm2022\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/educationaldatamining.org\/edm2022\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/educationaldatamining.org\/edm2022\/wp-json\/wp\/v2\/users\/13"}],"replies":[{"embeddable":true,"href":"https:\/\/educationaldatamining.org\/edm2022\/wp-json\/wp\/v2\/comments?post=676"}],"version-history":[{"count":2,"href":"https:\/\/educationaldatamining.org\/edm2022\/wp-json\/wp\/v2\/pages\/676\/revisions"}],"predecessor-version":[{"id":680,"href":"https:\/\/educationaldatamining.org\/edm2022\/wp-json\/wp\/v2\/pages\/676\/revisions\/680"}],"wp:attachment":[{"href":"https:\/\/educationaldatamining.org\/edm2022\/wp-json\/wp\/v2\/media?parent=676"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}