{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T15:42:40Z","timestamp":1774366960956,"version":"3.50.1"},"reference-count":64,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"2","license":[{"start":{"date-parts":[[2019,4,1]],"date-time":"2019-04-01T00:00:00Z","timestamp":1554076800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2019,4,1]],"date-time":"2019-04-01T00:00:00Z","timestamp":1554076800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2019,4,1]],"date-time":"2019-04-01T00:00:00Z","timestamp":1554076800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"Spanish Government","award":["TIN2016-75944-R"],"award-info":[{"award-number":["TIN2016-75944-R"]}]},{"DOI":"10.13039\/501100013774","name":"Universitat Oberta de Catalunya","doi-asserted-by":"crossref","award":["2018NG001"],"award-info":[{"award-number":["2018NG001"]}],"id":[{"id":"10.13039\/501100013774","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Learning Technol."],"published-print":{"date-parts":[[2019,4,1]]},"DOI":"10.1109\/tlt.2019.2912167","type":"journal-article","created":{"date-parts":[[2019,4,27]],"date-time":"2019-04-27T04:05:56Z","timestamp":1556337956000},"page":"249-263","source":"Crossref","is-referenced-by-count":104,"title":["An Early Feedback Prediction System for Learners At-Risk Within a First-Year Higher Education Course"],"prefix":"10.1109","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0380-1319","authenticated-orcid":false,"given":"David","family":"Baneres","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8698-4615","authenticated-orcid":false,"given":"M. Elena","family":"Rodriguez","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2023-7278","authenticated-orcid":false,"given":"Montse","family":"Serra","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref39","first-page":"194","article-title":"Learning analytics to identify students at-risk in MOOCs","author":"srilekshmi","year":"0","journal-title":"Proc IEEE 8th Int Conf Technol Educ"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1016\/j.compedu.2009.05.010"},{"key":"ref33","first-page":"169","article-title":"Retention: Predicting first-year success: Research in higher education","volume":"17","author":"lourens","year":"2003","journal-title":"S Afr J High Educ"},{"key":"ref32","first-page":"8","article-title":"Performance prediction of engineering students using decision trees","volume":"36","author":"kabra","year":"2011","journal-title":"Int J Comput Appl"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1016\/j.compedu.2012.08.015"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/j.compedu.2016.02.006"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1111\/exsy.12135"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1145\/2361276.2361288"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/ICBDAA.2017.8284117"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1039\/C001042C"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2013.07.007"},{"key":"ref62","author":"core team","year":"2017","journal-title":"R A Language and Environment for Statistical Computing"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/SAMI.2016.7423001"},{"key":"ref63","author":"tinto","year":"1987","journal-title":"Leaving College Rethinking the Causes and Cures of Student Attrition"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1016\/j.chb.2014.09.034"},{"key":"ref64","first-page":"418","article-title":"Student involvement: A developmental theory for higher education","volume":"40","author":"astin","year":"1999","journal-title":"J College Student Development"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1016\/j.iheduc.2018.02.001"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1145\/2330601.2330666"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TSMCC.2010.2053532"},{"key":"ref1","first-page":"3","article-title":"The state of educational data mining in 2009: A review and future visions","volume":"1","author":"baker","year":"2009","journal-title":"J Educational Data Mining"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.iheduc.2015.05.002"},{"key":"ref22","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.compedu.2016.09.005","article-title":"Models for early prediction of at-risk students in a course using standards-based grading","volume":"103","author":"farshid","year":"2016","journal-title":"Comput Educ"},{"key":"ref21","first-page":"218","article-title":"Micro-analytics for student performance prediction leveraging fine-grained learning analytics to predict performance","volume":"4","author":"azcona","year":"2015","journal-title":"International Journal of Software Engineering and Computing"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.18608\/jla.2016.33.13"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.compedu.2016.09.005"},{"key":"ref26","first-page":"586","article-title":"Predicting students' marks from Moodle logs using neural network models","volume":"1","author":"calvo-flores","year":"2006","journal-title":"Current Developments in Technology-Assisted Education"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1016\/j.compedu.2015.07.002"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1145\/1323293.1294281"},{"key":"ref51","author":"white","year":"2012","journal-title":"Hadoop The Definitive Guide"},{"key":"ref59","year":"2018"},{"key":"ref58","first-page":"309","article-title":"Local regression models","author":"cleveland","year":"1992","journal-title":"Statistical Models in S"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2005.50"},{"key":"ref56","first-page":"2825","article-title":"Scikit-learn: Machine Learning in Python","volume":"12","author":"pedregosa","year":"2011","journal-title":"J Mach Learn Res"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.18278\/il.3.2.5"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1145\/1656274.1656278"},{"key":"ref53","author":"kimball","year":"2011","journal-title":"The Data Warehouse Toolkit The Complete Guide to Dimensional Modeling"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/EduCon.2013.6530268"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-68318-8_1"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.iheduc.2015.10.002"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1016\/j.chb.2015.12.007"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.compedu.2009.09.008"},{"key":"ref13","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1344\/der.2018.33.235-266","article-title":"Data mining techniques applied in educational environments: Literature review","volume":"33","author":"manjarres","year":"2018","journal-title":"Digital Education Review"},{"key":"ref14","first-page":"3","article-title":"Analyzing student performance using sparse data of core bachelor courses","volume":"7","author":"saarela","year":"2015","journal-title":"JEDM-Journal of Educational Data Mining"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/ACCT.2014.105"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1080\/09645290701409939"},{"key":"ref17","first-page":"2","article-title":"Course signals at Purdue: Using learning analytics to increase student success","author":"pistilli","year":"0","journal-title":"Proceedings of the 2nd International Conference on Learning Analytics & Knowledge"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/j.iheduc.2015.11.003"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1016\/j.compedu.2013.06.009"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2006.04.005"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1002\/widm.1075"},{"key":"ref6","first-page":"30","article-title":"Let's talk learning analytics: A framework for implementation in relation to student retention","volume":"20","author":"west","year":"2016","journal-title":"Online Learning"},{"key":"ref5","first-page":"8","article-title":"Data mining algorithms to classify students","author":"romero","year":"2008","journal-title":"Educational Data Mining"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1007\/s40593-013-0010-8"},{"key":"ref7","doi-asserted-by":"crossref","first-page":"175","DOI":"10.1007\/978-3-319-02738-8_7","article-title":"Predicting student performance from combined data sources","volume":"7","author":"wolff","year":"2014","journal-title":"Educational Data Mining"},{"key":"ref49","first-page":"390","article-title":"Ethical and privacy issues in the application of learning analytics","author":"drachsler","year":"0","journal-title":"Proc 5th Int Conf Learn Analytics Knowl"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-49109-7_91"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/FIE.2015.7344361"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.18608\/jla.2014.11.3"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-13-0650-1_8"},{"key":"ref47","first-page":"472","article-title":"Supporting first generation college freshmen with small group intervention","volume":"38","author":"folger","year":"2004","journal-title":"College Student J"},{"key":"ref42","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1007\/978-1-4614-3305-7_6","article-title":"A learning management system-based early warning system for academic advising in undergraduate engineering","author":"krumm","year":"2014","journal-title":"Learning Analytics"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/TETC.2015.2504239"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1016\/j.chb.2014.04.002"},{"key":"ref43","first-page":"25","article-title":"A novel predictive modeling system to analyze students at risk of academic failure","volume":"156","author":"najdi","year":"2016","journal-title":"Int J Comput Appl"}],"container-title":["IEEE Transactions on Learning Technologies"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/4620076\/8735943\/08697134.pdf?arnumber=8697134","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,9,16]],"date-time":"2022-09-16T23:59:04Z","timestamp":1663372744000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8697134\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,4,1]]},"references-count":64,"journal-issue":{"issue":"2"},"URL":"https:\/\/doi.org\/10.1109\/tlt.2019.2912167","relation":{},"ISSN":["1939-1382","2372-0050"],"issn-type":[{"value":"1939-1382","type":"electronic"},{"value":"2372-0050","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,4,1]]}}}