{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,11]],"date-time":"2025-11-11T13:56:57Z","timestamp":1762869417838,"version":"3.41.2"},"reference-count":45,"publisher":"Emerald","issue":"1","license":[{"start":{"date-parts":[[2024,8,21]],"date-time":"2024-08-21T00:00:00Z","timestamp":1724198400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["DTA"],"published-print":{"date-parts":[[2025,1,14]]},"abstract":"<jats:sec><jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title><jats:p>Educational data mining (EDM) discovers significant patterns from educational data and thus can help understand the relations between learners and their educational settings. However, most previous data mining techniques focus on prediction of learning performance of learners without integrating learning patterns identification techniques.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title><jats:p>This study proposes a new framework for identifying learning patterns and predicting learning performance. Two modules, the learning patterns identification module and the deep learning prediction models (DNN), are integrated into this framework to identify the difference of learning performance and predicting learning performance from profiles of students.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Findings<\/jats:title><jats:p>Experimental results from survey data indicate that the proposed identifying learning patterns module could facilitate identifying valuable difference (change) patterns from student\u2019s profiles. The proposed learning performance prediction module which adapts DNN also performs better than traditional machine techniques in prediction performance metrics.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title><jats:p>To our best knowledge, the framework is the only educational system in the literature for identifying learning patterns and predicting learning performance.<\/jats:p><\/jats:sec>","DOI":"10.1108\/dta-09-2023-0539","type":"journal-article","created":{"date-parts":[[2024,8,20]],"date-time":"2024-08-20T10:11:57Z","timestamp":1724148717000},"page":"111-133","source":"Crossref","is-referenced-by-count":1,"title":["Novel framework for learning performance prediction using pattern identification and deep learning"],"prefix":"10.1108","volume":"59","author":[{"given":"Cheng-Hsiung","family":"Weng","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8994-3598","authenticated-orcid":false,"given":"Cheng-Kui","family":"Huang","sequence":"additional","affiliation":[]}],"member":"140","published-online":{"date-parts":[[2024,8,21]]},"reference":[{"key":"key2025011207574656300_ref001","first-page":"487","article-title":"Fast algorithms for mining association rules","volume":"1215","year":"1994","journal-title":"Proceedings of 20th International Conference. Very Large Data Bases, VLDB"},{"issue":"2","key":"key2025011207574656300_ref002","doi-asserted-by":"publisher","first-page":"207","DOI":"10.1145\/170036.170072","article-title":"Mining association rules between sets of items in large databases","volume":"22","year":"1993","journal-title":"ACM SIGMOD Record"},{"key":"key2025011207574656300_ref003","doi-asserted-by":"publisher","first-page":"226","DOI":"10.1016\/j.compedu.2017.05.021","article-title":"Data mining in educational technology classroom research: can it make a contribution?","volume":"113","year":"2017","journal-title":"Computers and Education"},{"key":"key2025011207574656300_ref004","unstructured":"Baker, R.S.J.D. (2010), \u201cData mining for education\u201d, in McGaw, B., Baker, E. and Peterson, P. (Eds), International Encyclopedia of Education, 3rd ed., Elsevier, Oxford."},{"issue":"1","key":"key2025011207574656300_ref005","first-page":"3","article-title":"The state of educational data mining in 2009: a review and future visions","volume":"1","year":"2009","journal-title":"JEDM-Journal of Educational Data Mining"},{"issue":"2","key":"key2025011207574656300_ref006","doi-asserted-by":"publisher","first-page":"5251","DOI":"10.1016\/j.sbspro.2010.03.855","article-title":"Data mining application on students' data","volume":"2","year":"2010","journal-title":"Procedia-Social and Behavioral Sciences"},{"key":"key2025011207574656300_ref007","doi-asserted-by":"crossref","unstructured":"Castro, F., Vellido, A., Nebot, \u00c0. and Mugica, F. (2007), \u201cApplying data mining techniques to e-learning problems\u201d, in Evolution of Teaching and Learning Paradigms in Intelligent Environment, Springer Berlin Heidelberg, pp.\u00a0183-221.","DOI":"10.1007\/978-3-540-71974-8_8"},{"key":"key2025011207574656300_ref008","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2023.106644","article-title":"Feature-based deep neural network approach for predicting mortality risk in patients with COVID-19","volume":"124","year":"2023","journal-title":"Engineering Applications of Artificial Intelligence"},{"issue":"2","key":"key2025011207574656300_ref009","doi-asserted-by":"publisher","first-page":"26","DOI":"10.1016\/s1874-8651(09)60010-7","article-title":"Efficient algorithm based on itemset-lattice and bitmap index for finding frequent itemsets","volume":"28","year":"2008","journal-title":"Systems Engineering-Theory and Practice"},{"key":"key2025011207574656300_ref010","doi-asserted-by":"publisher","first-page":"148","DOI":"10.1016\/j.engappai.2013.09.006","article-title":"An efficient method for mining frequent itemsets with double constraints","volume":"27","year":"2014","journal-title":"Engineering Applications of Artificial Intelligence"},{"key":"key2025011207574656300_ref011","doi-asserted-by":"publisher","first-page":"449","DOI":"10.1016\/j.procs.2015.02.043","article-title":"Identifying knowledge indicators in higher education organization","volume":"46","year":"2015","journal-title":"Procedia Computer Science"},{"first-page":"18","article-title":"Data mining in personalizing distance education courses","year":"2004","key":"key2025011207574656300_ref012"},{"issue":"2","key":"key2025011207574656300_ref013","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/335191.335372","article-title":"Mining frequent patterns without candidate generation","volume":"29","year":"2000","journal-title":"ACM SIGMOD Record"},{"key":"key2025011207574656300_ref014","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2020\/7286187","article-title":"Learning feature fusion in deep learning-based object detector","volume":"2020","year":"2020","journal-title":"Journal of Engineering"},{"issue":"4","key":"key2025011207574656300_ref044","doi-asserted-by":"crossref","first-page":"363","DOI":"10.1142\/S0129065794000372","article-title":"Neural networks, a comprehensive foundation","volume":"5","year":"1994","journal-title":"International Journal of Neural Systems"},{"issue":"3","key":"key2025011207574656300_ref015","doi-asserted-by":"publisher","first-page":"267","DOI":"10.1016\/j.compedu.2003.08.004","article-title":"The relationship of learning traits, motivation and performance-learning response dynamics","volume":"42","year":"2004","journal-title":"Computers and Education"},{"first-page":"137","article-title":"Text categorization with support vector machines: learning with many relevant features","year":"1998","key":"key2025011207574656300_ref043"},{"first-page":"971","article-title":"Dnn-based scoring of language learners' proficiency using learners' shadowings and native listeners' responsive shadowings","year":"2018","key":"key2025011207574656300_ref016"},{"key":"key2025011207574656300_ref017","doi-asserted-by":"publisher","first-page":"500","DOI":"10.1016\/j.procs.2015.07.372","article-title":"Classification and prediction based data mining algorithms to predict slow learners in education sector","volume":"57","year":"2015","journal-title":"Procedia Computer Science"},{"key":"key2025011207574656300_ref018","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2021\/9958203","article-title":"Performance prediction for higher education students using deep learning","volume":"2021","year":"2021","journal-title":"Complexity"},{"first-page":"368","article-title":"Relative risk and odds ratio: a data mining perspective","year":"2005","key":"key2025011207574656300_ref019"},{"issue":"5","key":"key2025011207574656300_ref020","doi-asserted-by":"publisher","first-page":"5154","DOI":"10.1016\/j.eswa.2010.10.047","article-title":"An improved frequent pattern growth method for mining association rules","volume":"38","year":"2011","journal-title":"Expert Systems with Applications"},{"first-page":"2469","article-title":"Threats of adversarial attacks in DNN-based modulation recognition","year":"2020","key":"key2025011207574656300_ref021"},{"issue":"1","key":"key2025011207574656300_ref022","doi-asserted-by":"publisher","first-page":"1362","DOI":"10.1016\/j.eswa.2011.08.018","article-title":"An improved association rules mining method","volume":"39","year":"2012","journal-title":"Expert Systems with Applications"},{"issue":"2","key":"key2025011207574656300_ref023","doi-asserted-by":"publisher","first-page":"65","DOI":"10.1016\/j.iheduc.2011.01.001","article-title":"Web mining and higher education: introduction to the special issue","volume":"14","year":"2011","journal-title":"The Internet and Higher Education"},{"issue":"14","key":"key2025011207574656300_ref024","doi-asserted-by":"publisher","first-page":"6400","DOI":"10.1016\/j.eswa.2014.04.024","article-title":"Student data mining solution\u2013knowledge management system related to higher education institutions","volume":"41","year":"2014","journal-title":"Expert Systems with Applications"},{"key":"key2025011207574656300_ref025","doi-asserted-by":"publisher","first-page":"203","DOI":"10.1016\/j.procs.2014.08.031","article-title":"A semantic rule-based approach supported by process mining for personalised adaptive learning","volume":"37","year":"2014","journal-title":"Procedia Computer Science"},{"issue":"4","key":"key2025011207574656300_ref026","first-page":"47","article-title":"Data mining technology for the evaluation of learning content interaction","volume":"3","year":"2004","journal-title":"International Journal on E-Learning"},{"key":"key2025011207574656300_ref045","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1109\/ISCSLP.2012.6423452","volume-title":"2012 8th International Symposium on Chinese Spoken Language Processing","year":"2012"},{"first-page":"441","article-title":"H-mine: hyper-structure mining of frequent patterns in large databases","year":"2001","key":"key2025011207574656300_ref027"},{"issue":"1","key":"key2025011207574656300_ref028","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1080\/00220670209598786","article-title":"An introduction to logistic regression analysis and reporting","volume":"96","year":"2002","journal-title":"The Journal of Educational Research"},{"issue":"1","key":"key2025011207574656300_ref029","doi-asserted-by":"publisher","first-page":"81","DOI":"10.1007\/bf00116251","article-title":"Induction of decision trees","volume":"1","year":"1986","journal-title":"Machine Learning"},{"issue":"6","key":"key2025011207574656300_ref030","doi-asserted-by":"publisher","first-page":"1701","DOI":"10.1016\/j.tele.2018.04.015","article-title":"Educational data mining: a review of evaluation process in the e-learning","volume":"35","year":"2018","journal-title":"Telematics and Informatics"},{"issue":"1","key":"key2025011207574656300_ref031","doi-asserted-by":"publisher","first-page":"135","DOI":"10.1016\/j.eswa.2006.04.005","article-title":"Educational data mining: a survey from 1995 to 2005","volume":"33","year":"2007","journal-title":"Expert Systems with Applications"},{"issue":"3","key":"key2025011207574656300_ref032","doi-asserted-by":"publisher","DOI":"10.1002\/widm.1355","article-title":"Educational data mining and learning analytics: an updated survey","volume":"10","year":"2020","journal-title":"Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery"},{"key":"key2025011207574656300_ref033","doi-asserted-by":"publisher","first-page":"458","DOI":"10.1016\/j.compedu.2013.06.009","article-title":"Predicting students' final performance from participation in on-line discussion forums","volume":"68","year":"2013","journal-title":"Computers and Education"},{"key":"key2025011207574656300_ref034","doi-asserted-by":"publisher","first-page":"354","DOI":"10.1016\/j.compedu.2014.10.008","article-title":"Practical guidelines for designing and evaluating educationally oriented recommendations","volume":"81","year":"2015","journal-title":"Computers and Education"},{"issue":"8","key":"key2025011207574656300_ref035","doi-asserted-by":"publisher","first-page":"1832","DOI":"10.1016\/j.engappai.2013.06.003","article-title":"Association rule mining using binary particle swarm optimization","volume":"26","year":"2013","journal-title":"Engineering Applications of Artificial Intelligence"},{"key":"key2025011207574656300_ref036","doi-asserted-by":"publisher","first-page":"262","DOI":"10.1016\/j.protcy.2012.02.053","article-title":"Evaluating the achievements of computer engineering department of distance education students with data mining methods","volume":"1","year":"2012","journal-title":"Procedia Technology"},{"issue":"10","key":"key2025011207574656300_ref037","doi-asserted-by":"publisher","first-page":"9468","DOI":"10.1016\/j.eswa.2012.02.112","article-title":"Predicting and analyzing secondary education placement-test scores: a data mining approach","volume":"39","year":"2012","journal-title":"Expert Systems with Applications"},{"issue":"6","key":"key2025011207574656300_ref038","doi-asserted-by":"publisher","first-page":"507","DOI":"10.1016\/j.knosys.2008.03.011","article-title":"Index-BitTableFI: an improved algorithm for mining frequent itemsets","volume":"21","year":"2008","journal-title":"Knowledge-Based Systems"},{"volume-title":"Introduction to Data Mining","year":"2006","key":"key2025011207574656300_ref039"},{"key":"key2025011207574656300_ref040","unstructured":"Tang, T.Y. and McCalla, G. (2002), \u201cStudent modeling for a web-based learning environment: a data mining approach\u201d, in AAAI\/IAAI, pp.\u00a0967-968."},{"key":"key2025011207574656300_ref041","doi-asserted-by":"publisher","first-page":"168","DOI":"10.1016\/j.chb.2014.09.034","article-title":"Participation-based student final performance prediction model through interpretable Genetic Programming: integrating learning analytics, educational data mining and theory","volume":"47","year":"2015","journal-title":"Computers in Human Behavior"},{"first-page":"60","article-title":"Web usage mining for a better web-based learning environment","year":"2001","key":"key2025011207574656300_ref042"}],"container-title":["Data Technologies and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/DTA-09-2023-0539\/full\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/DTA-09-2023-0539\/full\/html","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T23:15:24Z","timestamp":1753398924000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.emerald.com\/dta\/article\/59\/1\/111-133\/1239315"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8,21]]},"references-count":45,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2024,8,21]]},"published-print":{"date-parts":[[2025,1,14]]}},"alternative-id":["10.1108\/DTA-09-2023-0539"],"URL":"https:\/\/doi.org\/10.1108\/dta-09-2023-0539","relation":{},"ISSN":["2514-9288"],"issn-type":[{"type":"print","value":"2514-9288"}],"subject":[],"published":{"date-parts":[[2024,8,21]]}}}