{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T16:39:15Z","timestamp":1774456755672,"version":"3.50.1"},"reference-count":173,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2024,11,19]],"date-time":"2024-11-19T00:00:00Z","timestamp":1731974400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>Educational Data Mining (EDM) applies advanced data mining techniques to analyse data from educational settings, traditionally aimed at improving student performance. However, EDM\u2019s potential extends to enhancing administrative functions in educational organisations. This systematisation of knowledge (SoK) explores the use of EDM in organisational administration, examining peer-reviewed and non-peer-reviewed studies to provide a comprehensive understanding of its impact. This review highlights how EDM can revolutionise decision-making processes, supporting data-driven strategies that enhance administrative efficiency. It outlines key data mining techniques used in tasks like resource allocation, staff evaluation, and institutional planning. Challenges related to EDM implementation, such as data privacy, system integration, and the need for specialised skills, are also discussed. While EDM offers benefits like increased efficiency and informed decision-making, this review notes potential risks, including over-reliance on data and misinterpretation. The role of EDM in developing robust administrative frameworks that align with organisational goals is also explored. This study provides a critical overview of the existing literature and identifies areas for future research, offering insights to optimise educational administration through effective EDM use and highlighting its growing significance in shaping the future of educational organisations.<\/jats:p>","DOI":"10.3390\/info15110738","type":"journal-article","created":{"date-parts":[[2024,11,19]],"date-time":"2024-11-19T11:58:07Z","timestamp":1732017487000},"page":"738","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["SoK: The Impact of Educational Data Mining on Organisational Administration"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2646-3949","authenticated-orcid":false,"given":"Hamad","family":"Almaghrabi","sequence":"first","affiliation":[{"name":"Department of Computer Science and Information Technology, School of Computing, Engineering and Mathematical Sciences, La Trobe University, Bundoora, VIC 3086, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9519-886X","authenticated-orcid":false,"given":"Ben","family":"Soh","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Information Technology, School of Computing, Engineering and Mathematical Sciences, La Trobe University, Bundoora, VIC 3086, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9034-6774","authenticated-orcid":false,"given":"Alice","family":"Li","sequence":"additional","affiliation":[{"name":"La Trobe Business School, La Trobe University, Bundoora, VIC 3086, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2957-402X","authenticated-orcid":false,"given":"Idrees","family":"Alsolbi","sequence":"additional","affiliation":[{"name":"Data Science Department, College of Computing, Umm Al-Qura University, Makkah 24382, Saudi Arabia"}]}],"member":"1968","published-online":{"date-parts":[[2024,11,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1111\/jpim.12545","article-title":"Big data for creating and capturing value in the digitalized environment: Unpacking the effects of volume, variety, and veracity on firm performance","volume":"38","author":"Cappa","year":"2021","journal-title":"J. Prod. Innov. Manag."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Almaghrabi, H., Soh, B., and Li, A. (2024). Using ML to Predict User Satisfaction with ICT Technology for Educational Institution Administration. Information, 15.","DOI":"10.3390\/info15040218"},{"key":"ref_3","first-page":"4544","article-title":"Imminent Challenges of Adoption of Big Data in Educational Systems in Sub-Saharan Africa Nations","volume":"8","author":"Umezuruike","year":"2020","journal-title":"Int. J. Recent Technol. Eng."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"61905","DOI":"10.1109\/ACCESS.2022.3179356","article-title":"Artificial intelligence applications in K-12 education: A systematic literature review","volume":"10","author":"Zafari","year":"2022","journal-title":"IEEE Access"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"2971","DOI":"10.1007\/s10639-020-10102-w","article-title":"Utilizing crowdsourcing and machine learning in education: Literature review","volume":"25","author":"Alenezi","year":"2020","journal-title":"Educ. Inf. Technol."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1919","DOI":"10.18421\/TEM104-56","article-title":"Machine Learning Algorithm to Predict Student\u2019s Performance: A Systematic Literature Review","volume":"10","author":"Sandra","year":"2021","journal-title":"TEM J."},{"key":"ref_7","unstructured":"de Baker, R.S.J., Barnes, T., and Beck, J.E. (2008, January 20\u201321). Educational data mining 2008. Proceedings of the 1st International Conference on Educational Data Mining, Montr\u00e9al, QC, Canada."},{"key":"ref_8","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. Educ. Data Min."},{"key":"ref_9","unstructured":"Romero, C., Ventura, S., Espejo, P.G., and Herv\u00e1s, C. (2008, January 20\u201321). Data mining algorithms to classify students. Proceedings of the 1st International Conference on Educational Data Mining, Montr\u00e9al, QC, Canada."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Xiao, W., Ji, P., and Hu, J. (2022). A survey on educational data mining methods used for predicting students\u2019 performance. Eng. Rep., 4.","DOI":"10.1002\/eng2.12482"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Dake, D.K., and Buabeng-Andoh, C. (2022). Using Machine Learning Techniques to Predict Learner Drop-out Rate in Higher Educational Institutions. Mob. Inf. Syst., 2022.","DOI":"10.1155\/2022\/2670562"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Costa, A.G., Queiroga, E., Primo, T.T., Mattos, J.C.B., and Cechinel, C. (2020, January 19\u201323). Prediction analysis of student dropout in a Computer Science course using Educational Data Mining. Proceedings of the 2020 XV Conferencia Latinoamericana de Tecnologias de Aprendizaje (LACLO), Loja, Ecuador.","DOI":"10.1109\/LACLO50806.2020.9381166"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2059","DOI":"10.1007\/s11192-014-1506-1","article-title":"What is the best database for computer science journal articles?","volume":"102","author":"Cavacini","year":"2015","journal-title":"Scientometrics"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Garousi, V., Felderer, M., M\u00e4ntyl\u00e4, M.V., and Rainer, A. (2019). Benefitting from the Grey Literature in Software Engineering Research. arXiv.","DOI":"10.1007\/978-3-030-32489-6_14"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1016\/j.infsof.2018.09.006","article-title":"Guidelines for including grey literature and conducting multivocal literature reviews in software engineering","volume":"106","author":"Garousi","year":"2019","journal-title":"Inf. Softw. Technol."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Neto, G.T.G., Santos, W.B., Endo, P.T., and Fagundes, R.A. (2019, January 19\u201320). Multivocal literature reviews in software engineering: Preliminary findings from a tertiary study. Proceedings of the 2019 ACM\/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM), Porto de Galinhas, Brazil.","DOI":"10.1109\/ESEM.2019.8870142"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1016\/j.jss.2017.12.013","article-title":"Smells in software test code: A survey of knowledge in industry and academia","volume":"138","author":"Garousi","year":"2018","journal-title":"J. Syst. Softw."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"82","DOI":"10.1109\/TLT.2016.2639508","article-title":"Combining university student self-regulated learning indicators and engagement with online learning events to predict academic performance","volume":"10","author":"Pardo","year":"2016","journal-title":"IEEE Trans. Learn. Technol."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Panic, N., Leoncini, E., de Belvis, G., Ricciardi, W., and Boccia, S. (2013). Evaluation of the endorsement of the preferred reporting items for systematic reviews and meta-analysis (PRISMA) statement on the quality of published systematic review and meta-analyses. PLoS ONE, 8.","DOI":"10.1371\/journal.pone.0083138"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"873","DOI":"10.1093\/ptj\/89.9.873","article-title":"Reprint-Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement","volume":"89","author":"Moher","year":"2009","journal-title":"Phys. Ther."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"n71","DOI":"10.1136\/bmj.n71","article-title":"The PRISMA 2020 statement: An updated guideline for reporting systematic reviews","volume":"372","author":"Page","year":"2021","journal-title":"bmj"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Maphosa, M., and Maphosa, V. (2020, January 24\u201325). Educational data mining in higher education in sub-Saharan Africa: A systematic literature review and research agenda. Proceedings of the 2nd International Conference on Intelligent and Innovative Computing Applications, Plaine Magnien, Mauritius.","DOI":"10.1145\/3415088.3415096"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1016\/j.infsof.2008.09.009","article-title":"Systematic literature reviews in software engineering\u2014A systematic literature review","volume":"51","author":"Kitchenham","year":"2009","journal-title":"Inf. Softw. Technol."},{"key":"ref_24","unstructured":"Keele, S., and Charters, S. (2007). Guidelines for Performing Systematic Literature Reviews in Software Engineering, EBSE. EBSE Technical Report."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1258\/jicp.2011.011025","article-title":"Methodological support for business process redesign in health care: A literature review protocol","volume":"15","author":"Vanwersch","year":"2011","journal-title":"Int. J. Care Pathw."},{"key":"ref_26","unstructured":"Tyndall, J. (2024, September 25). AACODS Checklist. Available online: https:\/\/fac.flinders.edu.au\/dspace\/api\/core\/bitstreams\/e94a96eb-0334-4300-8880-c836d4d9a676\/content."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1455","DOI":"10.1007\/s10639-020-10309-x","article-title":"Behind the scenes of educational data mining","volume":"26","author":"Barhoom","year":"2021","journal-title":"Educ. Inf. Technol."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"119","DOI":"10.14257\/ijdta.2016.9.8.13","article-title":"Mining educational data to predict student\u2019s academic performance using ensemble methods","volume":"9","author":"Amrieh","year":"2016","journal-title":"Int. J. Database Theory Appl."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Villegas-Ch, W., Luj\u00e1n-Mora, S., and Buena\u00f1o-Fernandez, D. (2018, January 11\u201314). Towards the integration of business intelligence tools applied to educational data mining. Proceedings of the 2018 IEEE World Engineering Education Conference (EDUNINE), Buenos Aires, Argentina.","DOI":"10.1109\/EDUNINE.2018.8450954"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"256","DOI":"10.1108\/JEA-10-2020-0216","article-title":"Artificial intelligence in educational leadership: A symbiotic role of human-artificial intelligence decision-making","volume":"59","author":"Wang","year":"2021","journal-title":"J. Educ. Adm."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Ayub, M., Toba, H., Wijanto, M.C., and Yong, S. (2017, January 1\u20132). Modelling online assessment in management subjects through educational data mining. Proceedings of the 2017 International Conference on Data and Software Engineering (ICoDSE), Palembang, Indonesia.","DOI":"10.1109\/ICODSE.2017.8285881"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"106189","DOI":"10.1016\/j.chb.2019.106189","article-title":"Predicting academic performance of students from VLE big data using deep learning models","volume":"104","author":"Waheed","year":"2020","journal-title":"Comput. Hum. Behav."},{"key":"ref_33","unstructured":"Chau, V.T.N., and Phung, N.H. (March, January 27). A knowledge-driven educational decision support system. Proceedings of the 2012 IEEE RIVF International Conference on Computing & Communication Technologies, Research, Innovation, and Vision for the Future, Ho Chi Minh City, Vietnam."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Lee Hern\u00e1ndez, L.E., Cast\u00e1n-Rocha, J.A., Ibarra-Mart\u00ednez, S., Ter\u00e1n-Villanueva, J.D., Trevi\u00f1o-Berrones, M.G., and Laria-Menchaca, J. (2023). Cluster Analysis Using k-Means in School Dropout. Data Analytics and Computational Intelligence: Novel Models, Algorithms and Applications, Springer.","DOI":"10.1007\/978-3-031-38325-0_1"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1007\/s13278-023-01117-5","article-title":"Effectiveness of data augmentation to predict students at risk using deep learning algorithms","volume":"13","author":"Fahd","year":"2023","journal-title":"Soc. Netw. Anal. Min."},{"key":"ref_36","first-page":"321","article-title":"Early detecting students at risk using machine learning predictive models","volume":"Volume 2","author":"Wahdan","year":"2021","journal-title":"Proceedings of International Conference on Emerging Technologies and Intelligent Systems: ICETIS 2021"},{"key":"ref_37","first-page":"5.222","article-title":"Using data mining methods in knowledge management in educational field","volume":"10","author":"Oprea","year":"2011","journal-title":"Fascicle Manag. Technol. Eng."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"18","DOI":"10.17718\/tojde.1137114","article-title":"Classification of Students\u2019Achievement via Machine Learning by Using System Logs in Learning Management System","volume":"23","author":"Koyuncu","year":"2022","journal-title":"Turk. Online J. Distance Educ."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"12855","DOI":"10.1007\/s10639-022-11120-6","article-title":"Practical early prediction of students\u2019 performance using machine learning and eXplainable AI","volume":"27","author":"Jang","year":"2022","journal-title":"Educ. Inf. Technol."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"204","DOI":"10.52866\/ijcsm.2023.04.04.016","article-title":"Enhancing Student\u2019s Performance Classification Using Ensemble Modeling","volume":"4","author":"Nafea","year":"2023","journal-title":"Iraqi J. Comput. Sci. Math."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"042073","DOI":"10.1088\/1742-6596\/1881\/4\/042073","article-title":"Research on information construction and management of education management based on data mining","volume":"1881","author":"Zheng","year":"2021","journal-title":"J. Phys. Conf. Ser."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"67","DOI":"10.3991\/ijet.v13i11.9599","article-title":"An Educational Data Mining Model for Supervision of Network Learning Process","volume":"13","author":"Chen","year":"2018","journal-title":"Int. J. Emerg. Technol. Learn."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Gomede, E., Gaffo, F.H., Brigan\u00f3, G.U., de Barros, R.M., and Mendes, L.d.S. (2018). Application of computational intelligence to improve education in smart cities. Sensors, 18.","DOI":"10.3390\/s18010267"},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Thaher, T., Zaguia, A., Al Azwari, S., Mafarja, M., Chantar, H., Abuhamdah, A., Turabieh, H., Mirjalili, S., and Sheta, A. (2021). An enhanced evolutionary student performance prediction model using whale optimization algorithm boosted with sine-cosine mechanism. Appl. Sci., 11.","DOI":"10.3390\/app112110237"},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Siddique, A., Jan, A., Majeed, F., Qahmash, A.I., Quadri, N.N., and Wahab, M.O.A. (2021). Predicting academic performance using an efficient model based on fusion of classifiers. Appl. Sci., 11.","DOI":"10.3390\/app112411845"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"10217","DOI":"10.1149\/10701.10217ecst","article-title":"Using Classification Data Mining for Predicting Student Performance","volume":"107","author":"Sajja","year":"2022","journal-title":"ECS Trans."},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Sanvitha Kasthuriarachchi, K., Liyanage, S., and Bhatt, C.M. (2018). A data mining approach to identify the factors affecting the academic success of tertiary students in Sri Lanka. Software Data Engineering for Network eLearning Environments: Analytics and Awareness Learning Services, Springer.","DOI":"10.1007\/978-3-319-68318-8_9"},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Buena\u00f1o-Fern\u00e1ndez, D., Gil, D., and Luj\u00e1n-Mora, S. (2019). Application of machine learning in predicting performance for computer engineering students: A case study. Sustainability, 11.","DOI":"10.3390\/su11102833"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"120079","DOI":"10.1016\/j.eswa.2023.120079","article-title":"Performance and early drop prediction for higher education students using machine learning","volume":"225","author":"Christou","year":"2023","journal-title":"Expert Syst. Appl."},{"key":"ref_50","first-page":"1","article-title":"A Study of Prediction Accuracy of English Test Performance Using Data Mining and Analysis","volume":"7","author":"Duan","year":"2023","journal-title":"Ann. Emerg. Technol. Comput. AETIC"},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Llaur\u00f3, A., Fonseca, D., Villegas, E., Al\u00e1ez, M., and Romero, S. (2021, January 26\u201329). Educational data mining application for improving the academic tutorial sessions, and the reduction of early dropout in undergraduate students. Proceedings of the Ninth International Conference on Technological Ecosystems for Enhancing Multiculturality (TEEM\u201921), Barcelona, Spain.","DOI":"10.1145\/3486011.3486449"},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Chytas, K., Tsolakidis, A., Triperina, E., Karanikolas, N.N., and Skourlas, C. (2023). An Integrated Platform for Educational and Research Management Using Institutional Digital Resources. Proceedings of the Novel & Intelligent Digital Systems Conferences, Springer.","DOI":"10.1007\/978-3-031-44146-2_27"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"390","DOI":"10.1016\/j.sbspro.2014.07.117","article-title":"Improving quality of educational processes providing new knowledge using data mining techniques","volume":"147","author":"Chalaris","year":"2014","journal-title":"Procedia-Soc. Behav. Sci."},{"key":"ref_54","unstructured":"Afrin, F., Rahaman, M.S., and Hamilton, M. (2020). Mining Student Responses to Infer Student Satisfaction Predictors. arXiv."},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Harsono, S., Utami, E., and Yaqin, A. (2024, January 22\u201323). The Association Rule Methods and K-Means Clustering For Optimization Mapping Of New Students Admission. Proceedings of the 2024 IEEE International Conference on Artificial Intelligence and Mechatronics Systems (AIMS), Virtual.","DOI":"10.1109\/AIMS61812.2024.10513089"},{"key":"ref_56","first-page":"3240","article-title":"Teacher support and student motivation to learn with Artificial Intelligence (AI) based chatbot","volume":"32","author":"Chiu","year":"2023","journal-title":"Interact. Learn. Environ."},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Yu, W. (2021, January 24\u201326). Application of Big Data Technology in the Innovation of University Education Management Work. Proceedings of the 2021 4th International Conference on Information Systems and Computer Aided Education, Dalian, China.","DOI":"10.1145\/3482632.3483067"},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"106649","DOI":"10.1016\/j.engappai.2023.106649","article-title":"Predicting secondary school student performance using a double particle swarm optimization-based categorical boosting model","volume":"124","author":"Fan","year":"2023","journal-title":"Eng. Appl. Artif. Intell."},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"Kovalev, S., Kolodenkova, A., and Muntyan, E. (2020, January 14\u201317). Educational data mining: Current problems and solutions. Proceedings of the 2020 V International Conference on Information Technologies in Engineering Education (Inforino), Moscow, Russia.","DOI":"10.1109\/Inforino48376.2020.9111699"},{"key":"ref_60","doi-asserted-by":"crossref","unstructured":"Moscoso-Zea, O., Sampedro, A., and Luj\u00e1n-Mora, S. (2016, January 8\u201310). Datawarehouse design for educational data mining. Proceedings of the 2016 15th International Conference on Information Technology Based Higher Education and Training (ITHET), Istanbul, Turkey.","DOI":"10.1109\/ITHET.2016.7760754"},{"key":"ref_61","first-page":"56","article-title":"School\u2019s performance evaluation based on data mining","volume":"1","author":"Almuniri","year":"2017","journal-title":"Int. J. Eng. Inf. Syst."},{"key":"ref_62","doi-asserted-by":"crossref","unstructured":"Agasisti, T., and Bowers, A.J. (2017). Data analytics and decision making in education: Towards the educational data scientist as a key actor in schools and higher education institutions. Handbook of Contemporary Education Economics, Edward Elgar Publishing.","DOI":"10.4337\/9781785369070.00014"},{"key":"ref_63","doi-asserted-by":"crossref","unstructured":"Stasyshin, V.M., and Stasyshin, T.V. (2018). Analysis of Educational Data in the Decision-Making Support System of University, IEEE.","DOI":"10.1109\/APEIE.2018.8545835"},{"key":"ref_64","doi-asserted-by":"crossref","unstructured":"Ma, Y. (2022, January 17\u201319). Utilization of Data Mining Technology in University Students Management. Proceedings of the 2022 International Symposium on Advances in Informatics, Electronics and Education (ISAIEE), Frankfurt, Germany.","DOI":"10.1109\/ISAIEE57420.2022.00140"},{"key":"ref_65","doi-asserted-by":"crossref","unstructured":"Stefanova, K., and Kabakchieva, D. (2017, January 27\u201329). Educational data mining perspectives within university big data environment. Proceedings of the 2017 International Conference on Engineering, Technology and Innovation (ICE\/ITMC), Madeira Island, Portugal.","DOI":"10.1109\/ICE.2017.8279898"},{"key":"ref_66","doi-asserted-by":"crossref","unstructured":"Jerabek, M., Kubat, J., and Fabera, V. (2020). Smart, Smarter, and Smartest City: The Method to Comparison of Cities, Springer.","DOI":"10.1007\/978-3-030-34272-2_3"},{"key":"ref_67","first-page":"79","article-title":"Mining and its applications in Data Educational Management System","volume":"12","author":"Nisha","year":"2018","journal-title":"J. Sci."},{"key":"ref_68","doi-asserted-by":"crossref","unstructured":"Ahmad, S.F., Alam, M.M., Rahmat, M.K., Mubarik, M.S., and Hyder, S.I. (2022). Academic and Administrative Role of Artificial Intelligence in Education. Sustainability, 14.","DOI":"10.3390\/su14031101"},{"key":"ref_69","doi-asserted-by":"crossref","unstructured":"Li, S. (2020, January 21\u201322). Analysis on the application and challenge of educational big data in university teaching management. Proceedings of the 2020 Conference on Education, Language and Inter-cultural Communication (ELIC 2020), Zhengzhou, China.","DOI":"10.2991\/assehr.k.201127.030"},{"key":"ref_70","first-page":"427","article-title":"Expert system in enhancing efficiency in basic educational management using data mining techniques","volume":"12","author":"Inusah","year":"2021","journal-title":"IJACSA Int. J. Adv. Comput. Sci. Appl."},{"key":"ref_71","doi-asserted-by":"crossref","unstructured":"Murphy, R.F. (2019). Artificial Intelligence Applications to Support K-12 Teachers and Teaching, Rand Corporation.","DOI":"10.7249\/PE315"},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"11499","DOI":"10.1007\/s10639-022-11068-7","article-title":"Dropout prediction in Moocs using deep learning and machine learning","volume":"27","author":"Basnet","year":"2022","journal-title":"Educ. Inf. Technol."},{"key":"ref_73","first-page":"613","article-title":"Research on Construction of Educational Management Model Based on Data Mining Technology","volume":"26","author":"Zhao","year":"2022","journal-title":"J. Appl. Sci. Eng."},{"key":"ref_74","doi-asserted-by":"crossref","unstructured":"Wu, L. (2022, January 3\u20134). Educational Integrated Management System based on Artificial Intelligence and Multimedia. Proceedings of the 2022 IEEE 2nd International Conference on Mobile Networks and Wireless Communications (ICMNWC), Tumkur, India.","DOI":"10.1109\/ICMNWC56175.2022.10031814"},{"key":"ref_75","doi-asserted-by":"crossref","unstructured":"Liu, C., Wang, H., and Yuan, Z. (2022). A Method for Predicting the Academic Performances of College Students Based on Education System Data. Mathematics, 10.","DOI":"10.3390\/math10203737"},{"key":"ref_76","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Yun, Y., An, R., Cui, J., Dai, H., and Shang, X. (2021). Educational data mining techniques for student performance prediction: Method review and comparison analysis. Front. Psychol., 12.","DOI":"10.3389\/fpsyg.2021.698490"},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"100270","DOI":"10.1016\/j.bdr.2021.100270","article-title":"Educational Big Data: Predictions, Applications and Challenges","volume":"26","author":"Bai","year":"2021","journal-title":"Big Data Res."},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"335","DOI":"10.1016\/j.jbusres.2018.02.012","article-title":"Educational data mining: Predictive analysis of academic performance of public school students in the capital of Brazil","volume":"94","author":"Fernandes","year":"2019","journal-title":"J. Bus. Res."},{"key":"ref_79","doi-asserted-by":"crossref","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","author":"Kaur","year":"2015","journal-title":"Proc. Procedia Comput. Sci."},{"key":"ref_80","doi-asserted-by":"crossref","unstructured":"Moodley, R., Chiclana, F., Carter, J., and Caraffini, F. (2020). Using data mining in educational administration: A case study on improving school attendance. Appl. Sci., 10.","DOI":"10.3390\/app10093116"},{"key":"ref_81","doi-asserted-by":"crossref","unstructured":"Garg, S., Aleem, A., and Gore, M.M. Employing Deep Neural Network for Early Prediction of Students\u2019 Performance. Proceedings of the Intelligent Systems: Proceedings of ICMIB 2020.","DOI":"10.1007\/978-981-33-6081-5_44"},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"5882","DOI":"10.1109\/ACCESS.2024.3350169","article-title":"Prediction of Students\u2019 Academic Performance in the Programming Fundamentals Course Using Long Short-Term Memory Neural Networks","volume":"12","author":"Vives","year":"2024","journal-title":"IEEE Access"},{"key":"ref_83","first-page":"11","article-title":"Predicting student performance based on Lecture Materials data using Neural Network Models","volume":"3120","author":"Leelaluk","year":"2022","journal-title":"Ceur Workshop Proc."},{"key":"ref_84","doi-asserted-by":"crossref","unstructured":"Liu, T., Wang, C., Chang, L., and Gu, T. (2022). Predicting high-risk students using learning behavior. Mathematics, 10.","DOI":"10.3390\/math10142483"},{"key":"ref_85","doi-asserted-by":"crossref","unstructured":"Arun, D., Namratha, V., Ramyashree, B., Jain, Y.P., and Choudhury, A.R. (2021, January 27\u201329). Student academic performance prediction using educational data mining. Proceedings of the 2021 International Conference on Computer Communication and Informatics (ICCCI), Coimbatore, India.","DOI":"10.1109\/ICCCI50826.2021.9457021"},{"key":"ref_86","unstructured":"Zhang, Y., Jing, R., and Lan, L. (2023, January 13\u201315). Analysis of Student Learning Behavior Portrait Based on Big Data Technology. Proceedings of the 3rd International Conference on New Media Development and Modernized Education, NMDME 2023, Xi\u2019an, China."},{"key":"ref_87","doi-asserted-by":"crossref","unstructured":"Huang, H., and Li, B. (2024). Design and implementation of student management system of integrated programmable device programming system. Sci. Rep., 14.","DOI":"10.1038\/s41598-024-62844-z"},{"key":"ref_88","doi-asserted-by":"crossref","unstructured":"Desai, U., Ramasamy, V., and Kiper, J. (2021, January 15\u201317). Evaluation of student collaboration on canvas LMS using educational data mining techniques. Proceedings of the 2021 ACM Southeast Conference, Virtual.","DOI":"10.1145\/3409334.3452042"},{"key":"ref_89","doi-asserted-by":"crossref","first-page":"11645","DOI":"10.1007\/s10639-023-12238-x","article-title":"A data-driven precision teaching intervention mechanism to improve secondary school students\u2019 learning effectiveness","volume":"29","author":"Wang","year":"2023","journal-title":"Educ. Inf. Technol."},{"key":"ref_90","doi-asserted-by":"crossref","first-page":"2317","DOI":"10.1016\/j.matpr.2021.11.416","article-title":"Learning analytics using deep learning techniques for efficiently managing educational institutes","volume":"51","author":"Veluri","year":"2022","journal-title":"Mater. Today Proc."},{"key":"ref_91","doi-asserted-by":"crossref","first-page":"3782","DOI":"10.1016\/j.matpr.2021.07.382","article-title":"Classification and prediction of student performance data using various machine learning algorithms","volume":"80","author":"Pallathadka","year":"2023","journal-title":"Mater. Today Proc."},{"key":"ref_92","doi-asserted-by":"crossref","first-page":"212818","DOI":"10.1109\/ACCESS.2020.3040858","article-title":"Educational data mining for tutoring support in higher education: A web-based tool case study in engineering degrees","volume":"8","author":"Prada","year":"2020","journal-title":"IEEE Access"},{"key":"ref_93","doi-asserted-by":"crossref","first-page":"43","DOI":"10.51976\/ijari.221406","article-title":"Using data mining to predict primary school student performance","volume":"2","author":"Singh","year":"2019","journal-title":"IJARIIE"},{"key":"ref_94","doi-asserted-by":"crossref","unstructured":"Wang, Z., Zhu, C., Ying, Z., Zhang, Y., Wang, B., Jin, X., and Yang, H. (2018, January 10\u201312). Design and implementation of early warning system based on educational big data. Proceedings of the 2018 5th International Conference on Systems and Informatics (ICSAI), Nanjing, China.","DOI":"10.1109\/ICSAI.2018.8599357"},{"key":"ref_95","doi-asserted-by":"crossref","first-page":"9056947","DOI":"10.1155\/2021\/9056947","article-title":"Model construction and research on decision support system for education management based on data mining","volume":"2021","author":"Wang","year":"2021","journal-title":"Comput. Intell. Neurosci."},{"key":"ref_96","doi-asserted-by":"crossref","unstructured":"Romero-Rodr\u00edguez, J.M., Alonso-Garc\u00eda, S., Mar\u00edn-Mar\u00edn, J.A., and G\u00f3mez-Garc\u00eda, G. (2020). Considerations on the implications of the internet of things in spanish universities: The usefulness perceived by professors. Future Internet, 12.","DOI":"10.3390\/fi12080123"},{"key":"ref_97","doi-asserted-by":"crossref","unstructured":"Ray, S., and Saeed, M. (2018). Applications of educational data mining and learning analytics tools in handling big data in higher education. Applications of Big Data Analytics: Trends, Issues, and Challenges, Springer.","DOI":"10.1007\/978-3-319-76472-6_7"},{"key":"ref_98","doi-asserted-by":"crossref","unstructured":"Chen, S., Pian, Y., and Zheng, Y. (2023, January 15\u201317). Challenges and Strategies for Designing More Effective Educational Data Mining Applications. Proceedings of the 2023 Twelfth International Conference of Educational Innovation through Technology (EITT), Fuzhou, China.","DOI":"10.1109\/EITT61659.2023.00040"},{"key":"ref_99","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1108\/SASBE-12-2021-0231","article-title":"Blockchain integration into electronic document management (EDM) system in construction common data environment","volume":"13","author":"Kiu","year":"2024","journal-title":"Smart Sustain. Built Environ."},{"key":"ref_100","doi-asserted-by":"crossref","unstructured":"Fernandez-Medina, C., P\u00e9rez-P\u00e9rez, J.R., \u00c1lvarez-Garc\u00eda, V.M., and Paule-Ruiz, M.D.P. (2013, January 1\u20133). Assistance in computer programming learning using educational data mining and learning analytics. Proceedings of the 18th ACM Conference on Innovation and Technology in Computer Science Education, Canterbury, UK.","DOI":"10.1145\/2462476.2462496"},{"key":"ref_101","doi-asserted-by":"crossref","unstructured":"Moreno-Guerrero, A.J., L\u00f3pez-Belmonte, J., Mar\u00edn-Mar\u00edn, J.A., and Soler-Costa, R. (2020). Scientific development of educational artificial intelligence in Web of Science. Future Internet, 12.","DOI":"10.3390\/fi12080124"},{"key":"ref_102","doi-asserted-by":"crossref","first-page":"513","DOI":"10.1044\/2018_AJA-IMIA3-18-0020","article-title":"Toward better outcomes in audiology distance education: An educational data mining approach","volume":"27","author":"Penteado","year":"2018","journal-title":"Am. J. Audiol."},{"key":"ref_103","unstructured":"Uguz, C. (2016). Exploring Methodologies for Utilizing Click-Track Data Using Educational Data Mining and Evidence Centered Design in Online Professional Development Environments. [Ph.D. Thesis, University of Virginia]."},{"key":"ref_104","doi-asserted-by":"crossref","unstructured":"Chandra, D.G., and Raman, A.C. (2014, January 7\u20139). Educational Data Mining on Learning Management Systems Using SCORM. Proceedings of the 2014 Fourth International Conference on Communication Systems and Network Technologies, Bhopal, India.","DOI":"10.1109\/CSNT.2014.91"},{"key":"ref_105","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1007\/s41686-017-0013-1","article-title":"Implementing a digital learning initiative: A case study in K-12 classrooms","volume":"2","author":"Stork","year":"2018","journal-title":"J. Form. Des. Learn."},{"key":"ref_106","unstructured":"Kellogg, S.B. (2014). Patterns of Peer Interaction and Mechanisms Governing Social Network Structure in Two Massively Open Online Courses for Educators. [Ph.D. Thesis, North Carolina State University]."},{"key":"ref_107","doi-asserted-by":"crossref","unstructured":"Rawal, A., and Thomas, A. (2017, January 5\u20137). Educational Data Mining Practices in Indian Academia. Proceedings of the 10th Innovations in Software Engineering Conference, Jaipur, India.","DOI":"10.1145\/3021460.3021493"},{"key":"ref_108","doi-asserted-by":"crossref","unstructured":"Ganga, X. (2021, January 25\u201327). Educational Artificial Intelligence (EAI) Connotation, Key Technology and Application Trend-Interpretation and analysis of the two reports entitled \u201cPreparing for the Future of Artificial Intelligence\u201d and \u201cThe National Artificial Intelligence Research and Development Strategic Plan\u201d. Proceedings of the 2021 International Conference on Intelligent Computing, Automation and Applications (ICAA), Nanjing, China.","DOI":"10.1109\/ICAA53760.2021.00046"},{"key":"ref_109","doi-asserted-by":"crossref","unstructured":"Liu, D., and Huang, M. (2021, January 24\u201326). Engineering Certification Practice Teaching Management and Data Mining Based on Complex Hierarchical Model. Proceedings of the 2021 4th International Conference on Information Systems and Computer Aided Education, Dalian, China.","DOI":"10.1145\/3482632.3482651"},{"key":"ref_110","doi-asserted-by":"crossref","unstructured":"Sweta, S., and Sweta, S. (2021). Educational data mining in e-learning system. Modern Approach to Educational Data Mining and Its Applications, Springer.","DOI":"10.1007\/978-981-33-4681-9"},{"key":"ref_111","doi-asserted-by":"crossref","unstructured":"Alvarado-Uribe, J., Mej\u00eda-Almada, P., Masetto Herrera, A.L., Molontay, R., Hilliger, I., Hegde, V., Montemayor Gallegos, J.E., Ram\u00edrez D\u00edaz, R.A., and Ceballos, H.G. (2022). Student dataset from Tecnologico de Monterrey in Mexico to predict dropout in higher education. Data, 7.","DOI":"10.3390\/data7090119"},{"key":"ref_112","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1007\/978-3-030-95987-6_9","article-title":"IiCE: A Proposed System Based on IoTaaS to Study Administrative Efficiency in Primary Schools","volume":"Volume 421","author":"Almaghrabi","year":"2022","journal-title":"Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST"},{"key":"ref_113","doi-asserted-by":"crossref","first-page":"1212","DOI":"10.1080\/01969722.2022.2080340","article-title":"Change-Detection Machine Learning Model for Educational Management","volume":"54","author":"Huang","year":"2023","journal-title":"Cybern. Syst."},{"key":"ref_114","doi-asserted-by":"crossref","unstructured":"Udupi, P.K., Sharma, N., and Jha, S. (2016, January 7\u20139). Educational data mining and big data framework for e-learning environment. Proceedings of the 2016 5th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO), Noida, India.","DOI":"10.1109\/ICRITO.2016.7784961"},{"key":"ref_115","doi-asserted-by":"crossref","unstructured":"Hidayat, N., Wardoyo, R., and Azhari, S. (2018, January 17\u201318). Educational Data Mining (EDM) as a Model for Students\u2019 Evaluation in Learning Environment. Proceedings of the 2018 Third International Conference on Informatics and Computing (ICIC), Palembang, Indonesia.","DOI":"10.1109\/IAC.2018.8780459"},{"key":"ref_116","doi-asserted-by":"crossref","first-page":"905","DOI":"10.1007\/s10639-022-11152-y","article-title":"Educational data mining to predict students\u2019 academic performance: A survey study","volume":"28","author":"Batool","year":"2023","journal-title":"Educ. Inf. Technol."},{"key":"ref_117","doi-asserted-by":"crossref","first-page":"107939","DOI":"10.1016\/j.cie.2022.107939","article-title":"A machine learning-based iterative design approach to automate user satisfaction degree prediction in smart product-service system","volume":"165","author":"Cong","year":"2022","journal-title":"Comput. Ind. Eng."},{"key":"ref_118","first-page":"131","article-title":"Using educational data mining techniques to identify profiles in self-regulated learning: An empirical evaluation","volume":"23","author":"Araka","year":"2022","journal-title":"Int. Rev. Res. Open Distrib. Learn."},{"key":"ref_119","doi-asserted-by":"crossref","first-page":"103676","DOI":"10.1016\/j.compedu.2019.103676","article-title":"An overview and comparison of supervised data mining techniques for student exam performance prediction","volume":"143","author":"Tomasevic","year":"2020","journal-title":"Comput. Educ."},{"key":"ref_120","first-page":"124","article-title":"The alternating decision tree learning algorithm","volume":"99","author":"Freund","year":"1999","journal-title":"ICML"},{"key":"ref_121","doi-asserted-by":"crossref","first-page":"8439","DOI":"10.1021\/acs.est.0c07484","article-title":"Estimation of unit process data for life cycle assessment using a decision tree-based approach","volume":"55","author":"Zhao","year":"2021","journal-title":"Environ. Sci. Technol."},{"key":"ref_122","first-page":"612","article-title":"Evaluating the impact of GINI index and information gain on classification using decision tree classifier algorithm","volume":"11","author":"Tangirala","year":"2020","journal-title":"Int. J. Adv. Comput. Sci. Appl."},{"key":"ref_123","doi-asserted-by":"crossref","first-page":"3397","DOI":"10.1080\/10106049.2020.1861664","article-title":"Assessment of Gini-, entropy-and ratio-based classification trees for groundwater potential modelling and prediction","volume":"37","author":"Rahmati","year":"2022","journal-title":"Geocarto Int."},{"key":"ref_124","doi-asserted-by":"crossref","unstructured":"Guruler, H., and Istanbullu, A. (2014). Modeling student performance in higher education using data mining. Educational Data Mining: Applications and Trends, Springer.","DOI":"10.1007\/978-3-319-02738-8_4"},{"key":"ref_125","doi-asserted-by":"crossref","first-page":"298","DOI":"10.5573\/IEIESPC.2020.9.4.298","article-title":"Development and optimization of deep belief networks applied for academic performance prediction with larger datasets","volume":"9","author":"Sokkhey","year":"2020","journal-title":"IEIE Trans. Smart Process. Comput."},{"key":"ref_126","doi-asserted-by":"crossref","unstructured":"Chitti, M., Chitti, P., and Jayabalan, M. (2020, January 14\u201317). Need for interpretable student performance prediction. Proceedings of the 2020 13th International Conference on Developments in eSystems Engineering (DeSE), Virtual.","DOI":"10.1109\/DeSE51703.2020.9450735"},{"key":"ref_127","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Mach. Learn."},{"key":"ref_128","unstructured":"Allevato, A., Thornton, M., Edwards, S., and Perez-Quinones, M. (2008, January 20\u201321). Mining data from an automated grading and testing system by adding rich reporting capabilities. Proceedings of the Educational Data Mining, Montreal, QC, Canada."},{"key":"ref_129","first-page":"54","article-title":"Educational data mining: Student performance prediction in academic","volume":"8","author":"Salal","year":"2019","journal-title":"Int. J. Eng. Adv. Technol."},{"key":"ref_130","doi-asserted-by":"crossref","first-page":"25","DOI":"10.5815\/ijmecs.2017.08.04","article-title":"Evaluation of data mining techniques for predicting student\u2019s performance","volume":"8","author":"Kumar","year":"2017","journal-title":"Int. J. Mod. Educ. Comput. Sci."},{"key":"ref_131","doi-asserted-by":"crossref","first-page":"8064844","DOI":"10.1155\/2022\/8064844","article-title":"Improving Random Forest Algorithm for University Academic Affairs Management System Platform Construction","volume":"2022","author":"Dai","year":"2022","journal-title":"Adv. Multimed."},{"key":"ref_132","first-page":"1","article-title":"Prediction of Students\u2019 Performance in E-Learning Environment Using Random Forest","volume":"7","author":"Abubakar","year":"2017","journal-title":"Int. J. Innov. Comput."},{"key":"ref_133","first-page":"59","article-title":"Educational data mining: RT and RF classification models for higher education professional courses","volume":"8","author":"Algur","year":"2016","journal-title":"Int. J. Inf. Eng. Electron. Bus."},{"key":"ref_134","doi-asserted-by":"crossref","unstructured":"Senthil, S., and Lin, W.M. (2017, January 2\u20133). Applying classification techniques to predict students\u2019 academic results. Proceedings of the 2017 IEEE International Conference on Current Trends in Advanced Computing (ICCTAC), Bangalore, India.","DOI":"10.1109\/ICCTAC.2017.8249986"},{"key":"ref_135","doi-asserted-by":"crossref","first-page":"76","DOI":"10.1016\/j.iheduc.2018.02.002","article-title":"Centralized student performance prediction in large courses based on low-cost variables in an institutional context","volume":"37","author":"Sandoval","year":"2018","journal-title":"Internet High. Educ."},{"key":"ref_136","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1186\/s40561-022-00192-z","article-title":"Educational data mining: Prediction of students\u2019 academic performance using machine learning algorithms","volume":"9","year":"2022","journal-title":"Smart Learn. Environ."},{"key":"ref_137","doi-asserted-by":"crossref","first-page":"101483","DOI":"10.1016\/j.tele.2020.101483","article-title":"Do information and service quality affect perceived privacy protection, satisfaction, and loyalty? Evidence from a Chinese O2O-based mobile shopping application","volume":"56","author":"Kim","year":"2021","journal-title":"Telemat. Inform."},{"key":"ref_138","doi-asserted-by":"crossref","unstructured":"Rovira, S., Puertas, E., and Igual, L. (2017). Data-driven system to predict academic grades and dropout. PLoS ONE, 12.","DOI":"10.1371\/journal.pone.0171207"},{"key":"ref_139","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1109\/TIT.1967.1053964","article-title":"Nearest neighbor pattern classification","volume":"13","author":"Cover","year":"1967","journal-title":"IEEE Trans. Inf. Theory"},{"key":"ref_140","doi-asserted-by":"crossref","first-page":"85","DOI":"10.3102\/1076998616666808","article-title":"Tools for educational data mining: A review","volume":"42","author":"Slater","year":"2017","journal-title":"J. Educ. Behav. Stat."},{"key":"ref_141","doi-asserted-by":"crossref","first-page":"100068","DOI":"10.1016\/j.caeai.2022.100068","article-title":"Personalized education and Artificial Intelligence in the United States, China, and India: A systematic review using a Human-In-The-Loop model","volume":"3","author":"Bhutoria","year":"2022","journal-title":"Comput. Educ. Artif. Intell."},{"key":"ref_142","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1556\/606.2021.00374","article-title":"Predicting students\u2019 academic performance using a modified kNN algorithm","volume":"16","author":"Jawthari","year":"2021","journal-title":"Pollack Period."},{"key":"ref_143","unstructured":"Gazalba, I., and Reza, N.G.I. (2017, January 1\u20132). Comparative analysis of k-nearest neighbor and modified k-nearest neighbor algorithm for data classification. Proceedings of the 2017 2nd International Conferences on Information Technology, Information Systems and Electrical Engineering (ICITISEE), Yogyakarta, Indonesia."},{"key":"ref_144","unstructured":"Steinwart, I., and Christmann, A. (2008). Support Vector Machines, Springer Science & Business Media."},{"key":"ref_145","first-page":"140","article-title":"Data mining in education: Data classification and decision tree approach","volume":"2","author":"Agarwal","year":"2012","journal-title":"Int. J. e-Educ. e-Bus. e-Manag. e-Learn."},{"key":"ref_146","doi-asserted-by":"crossref","first-page":"1827","DOI":"10.1016\/j.promfg.2020.01.256","article-title":"Predicting student retention using support vector machines","volume":"39","author":"Cardona","year":"2019","journal-title":"Procedia Manuf."},{"key":"ref_147","doi-asserted-by":"crossref","first-page":"7076","DOI":"10.1109\/ACCESS.2021.3049157","article-title":"An unsupervised ensemble clustering approach for the analysis of student behavioral patterns","volume":"9","author":"Li","year":"2021","journal-title":"IEEE Access"},{"key":"ref_148","first-page":"210","article-title":"A multi-class support vector machine approach for students academic performance prediction","volume":"4","author":"Asogbon","year":"2016","journal-title":"Int. J. Multidiscip. Curr. Res."},{"key":"ref_149","unstructured":"Yegnanarayana, B. (2009). Artificial Neural Networks, PHI Learning Pvt. Ltd."},{"key":"ref_150","doi-asserted-by":"crossref","first-page":"601","DOI":"10.1109\/TSMCC.2010.2053532","article-title":"Educational data mining: A review of the state of the art","volume":"40","author":"Romero","year":"2010","journal-title":"IEEE Trans. Syst. Man Cybern. Part C Appl. Rev."},{"key":"ref_151","doi-asserted-by":"crossref","unstructured":"Lin, Y.W., Zhou, Y., Faghri, F., Shaw, M.J., and Campbell, R.H. (2019). Analysis and prediction of unplanned intensive care unit readmission using recurrent neural networks with long short-term memory. PLoS ONE, 14.","DOI":"10.1371\/journal.pone.0218942"},{"key":"ref_152","doi-asserted-by":"crossref","first-page":"100074","DOI":"10.1016\/j.caeai.2022.100074","article-title":"Explainable artificial intelligence in education","volume":"3","author":"Khosravi","year":"2022","journal-title":"Comput. Educ. Artif. Intell."},{"key":"ref_153","first-page":"12","article-title":"Data mining in education","volume":"Volume 3","author":"Romero","year":"2013","journal-title":"Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery"},{"key":"ref_154","unstructured":"Rish, I. (2001, January 4\u201310). An empirical study of the naive Bayes classifier. Proceedings of the IJCAI 2001 Workshop on Empirical Methods in Artificial Intelligence, Seattle, WA, USA."},{"key":"ref_155","doi-asserted-by":"crossref","first-page":"121555","DOI":"10.1016\/j.eswa.2023.121555","article-title":"Research on learning behavior patterns from the perspective of educational data mining: Evaluation, prediction and visualization","volume":"237","author":"Feng","year":"2024","journal-title":"Expert Syst. Appl."},{"key":"ref_156","doi-asserted-by":"crossref","unstructured":"Jalota, C., and Agrawal, R. (2019, January 14\u201316). Analysis of educational data mining using classification. Proceedings of the 2019 International Conference on Machine Learning, Big Data, Cloud and Parallel Computing (COMITCon), Faridabad, India.","DOI":"10.1109\/COMITCon.2019.8862214"},{"key":"ref_157","doi-asserted-by":"crossref","unstructured":"Asad, R., Altaf, S., Ahmad, S., Shah Noor Mohamed, A., Huda, S., and Iqbal, S. (2023). Achieving personalized precision education using the Catboost Model during the COVID-19 lockdown period in pakistan. Sustainability, 15.","DOI":"10.3390\/su15032714"},{"key":"ref_158","doi-asserted-by":"crossref","first-page":"104631","DOI":"10.1016\/j.compedu.2022.104631","article-title":"Exploring the factors influencing teachers\u2019 instructional data use with electronic data systems","volume":"191","author":"Luo","year":"2022","journal-title":"Comput. Educ."},{"key":"ref_159","first-page":"42","article-title":"A Strategy to Improve The Usage of ICT in The Kingdom of Saudi Arabia Primary School","volume":"3","author":"Almalki","year":"2012","journal-title":"Int. J. Adv. Comput. Sci. Appl."},{"key":"ref_160","doi-asserted-by":"crossref","first-page":"201","DOI":"10.32890\/mjli2018.15.1.8","article-title":"The Influence of Principals\u2019 Technology Leadership and Professional Development on Teachers\u00e2\u20ac\u2122 Technology Integration in Secondary Schools","volume":"15","author":"Thannimalai","year":"2018","journal-title":"Malays. J. Learn. Instr."},{"key":"ref_161","doi-asserted-by":"crossref","unstructured":"Chen, T., Peng, L., Yin, X., Rong, J., Yang, J., and Cong, G. (2020). Analysis of User Satisfaction with Online Education Platforms in China during the COVID-19 Pandemic. Healthcare, 8.","DOI":"10.3390\/healthcare8030200"},{"key":"ref_162","doi-asserted-by":"crossref","first-page":"275","DOI":"10.1177\/1741143217732793","article-title":"Improving school administration through information technology? How digitalisation changes the bureaucratic features of public school administration","volume":"47","author":"Dormann","year":"2017","journal-title":"Educ. Manag. Adm. Leadersh."},{"key":"ref_163","doi-asserted-by":"crossref","unstructured":"Mandal, S., and Khan, D.A. (2020, January 10\u201312). A Study of Security Threats in Cloud: Passive Impact of COVID-19 Pandemic. Proceedings of the 2020 International Conference on Smart Electronics and Communication (ICOSEC), Trichy, India.","DOI":"10.1109\/ICOSEC49089.2020.9215374"},{"key":"ref_164","doi-asserted-by":"crossref","first-page":"547","DOI":"10.14742\/ajet.626","article-title":"A change agent\u2019s facilitation process for overcoming the barriers of ICT adoption for educational administration\u2014The case of a rural-Bangladesh vocational institution","volume":"30","author":"Khalid","year":"2014","journal-title":"Australas. J. Educ. Technol."},{"key":"ref_165","doi-asserted-by":"crossref","first-page":"752","DOI":"10.18178\/ijmlc.2020.10.6.1001","article-title":"Towards machine learning based analysis of quality of user experience (QoUE)","volume":"10","author":"Nwakanma","year":"2020","journal-title":"Int. J. Mach. Learn. Comput."},{"key":"ref_166","unstructured":"Baker, R.S.J. (2005). Encyclopedia of Data Warehousing and Mining, IGI Global Scientific Publishing."},{"key":"ref_167","doi-asserted-by":"crossref","unstructured":"Guo, B., Zhang, R., Xu, G., Shi, C., and Yang, L. (2015, January 27\u201329). Predicting students performance in educational data mining. Proceedings of the 2015 International Symposium on Educational Technology (ISET), Wuhan, China.","DOI":"10.1109\/ISET.2015.33"},{"key":"ref_168","doi-asserted-by":"crossref","first-page":"1471","DOI":"10.1016\/j.procs.2020.03.358","article-title":"An intelligent prediction system for educational data mining based on ensemble and filtering approaches","volume":"167","author":"Ashraf","year":"2020","journal-title":"Procedia Comput. Sci."},{"key":"ref_169","unstructured":"H\u00e4m\u00e4l\u00e4inen, W., and Vinni, M. (2011). Classifiers for educational data mining. Handbook of Educational Data Mining, CRC Press."},{"key":"ref_170","doi-asserted-by":"crossref","first-page":"120323","DOI":"10.1016\/j.eswa.2023.120323","article-title":"Lessons from debiasing data for fair and accurate predictive modeling in education","volume":"228","author":"Sha","year":"2023","journal-title":"Expert Syst. Appl."},{"key":"ref_171","unstructured":"Baker, R., and de Carvalho, A. (2008, January 20\u201321). Labeling student behavior faster and more precisely with text replays. Proceedings of the Educational Data Mining, the 1st International Conference on Educational Data Mining, Montreal, QC, Canada."},{"key":"ref_172","doi-asserted-by":"crossref","unstructured":"Anshari, M., Syafrudin, M., and Fitriyani, N.L. (2022). Fourth Industrial Revolution between Knowledge Management and Digital Humanities. Information, 13.","DOI":"10.3390\/info13060292"},{"key":"ref_173","doi-asserted-by":"crossref","first-page":"012023","DOI":"10.1088\/1742-6596\/1810\/1\/012023","article-title":"Educational big data infrastructure: Opportunities, design and challenges","volume":"1810","author":"Putrama","year":"2021","journal-title":"J. Phys. Conf. 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