{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,9]],"date-time":"2024-09-09T11:45:24Z","timestamp":1725882324207},"publisher-location":"Cham","reference-count":28,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319557045"},{"type":"electronic","value":"9783319557052"}],"license":[{"start":{"date-parts":[[2017,1,1]],"date-time":"2017-01-01T00:00:00Z","timestamp":1483228800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017]]},"DOI":"10.1007\/978-3-319-55705-2_27","type":"book-chapter","created":{"date-parts":[[2017,3,20]],"date-time":"2017-03-20T23:38:59Z","timestamp":1490053139000},"page":"340-351","source":"Crossref","is-referenced-by-count":2,"title":["Predicting Student Examinee Rate in Massive Open Online Courses"],"prefix":"10.1007","author":[{"given":"Wei","family":"Lu","sequence":"first","affiliation":[]},{"given":"Tongtong","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Min","family":"Jiao","sequence":"additional","affiliation":[]},{"given":"Xiaoying","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Shan","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Xiaoyong","family":"Du","sequence":"additional","affiliation":[]},{"given":"Hong","family":"Chen","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2017,3,22]]},"reference":[{"unstructured":"Academic & university news \u2014 times higher education (the). https:\/\/www.timeshighereducation.com\/news\/mooc-completion-rates-below-7\/2003710.article\/","key":"27_CR1"},{"unstructured":"China university MOOC. http:\/\/www.icourse163.org\/","key":"27_CR2"},{"unstructured":"Coursera. https:\/\/www.coursera.org","key":"27_CR3"},{"unstructured":"Data driven education workshop. https:\/\/nips.cc\/Conferences\/2013\/","key":"27_CR4"},{"unstructured":"edX. https:\/\/www.edx.org\/","key":"27_CR5"},{"unstructured":"Udacity. https:\/\/cn.udacity.com\/","key":"27_CR6"},{"unstructured":"XuetangX. http:\/\/www.xuetangx.com\/","key":"27_CR7"},{"unstructured":"KDD Cup 2015, MOOC dropout prediction. https:\/\/biendata.com\/competition\/kddcup2015\/","key":"27_CR8"},{"doi-asserted-by":"crossref","unstructured":"Amnueypornsakul, B., Bhat, S., Chinprutthiwong, P.: Predicting attrition along the way: the UIUC model. In: Empirical Methods in Natural Language Processing Workshop on Modeling Large Scale Social Interaction in Massively Open Online Courses (2014)","key":"27_CR9","DOI":"10.3115\/v1\/W14-4110"},{"key":"27_CR10","volume-title":"An Introduction to Support Vector Machines and Other Kernel-Based Learning Methods","author":"N Cristianini","year":"2010","unstructured":"Cristianini, N., Shawe-Taylor, J.: An Introduction to Support Vector Machines and Other Kernel-Based Learning Methods. Cambridge University Press, Cambridge (2010)"},{"unstructured":"The Free Encyclopedia, Massive open online course. https:\/\/en.wikipedia.org\/w\/index.php?title=Massive_open_online_course&oldid=694372484\/","key":"27_CR11"},{"doi-asserted-by":"crossref","unstructured":"Fei, M., Yeung, D.: Temporal models for predicting student dropout in massive open online courses. In: IEEE International Conference on Data Mining Workshop, pp. 256\u2013263 (2015)","key":"27_CR12","DOI":"10.1109\/ICDMW.2015.174"},{"volume-title":"Statistical Models Theory and Practice","year":"2009","unstructured":"Freedman, D. (ed.): Statistical Models Theory and Practice. Cambridge University Press, Cambridge (2009)","key":"27_CR13"},{"doi-asserted-by":"crossref","unstructured":"Kloft, M., Stiehler, F., Zheng, Z., Pinkwart, N.: Predicting MOOC dropout over weeks using machine learning methods. In: Empirical Methods in Natural Language Processing Workshop on Modeling Large Scale Social Interaction in Massively Open Online Courses (2014)","key":"27_CR14","DOI":"10.3115\/v1\/W14-4111"},{"key":"27_CR15","doi-asserted-by":"crossref","first-page":"322","DOI":"10.1016\/j.knosys.2015.05.019","volume":"85","author":"O Luaces","year":"2015","unstructured":"Luaces, O., D\u00edez, J., Alonso-Betanzos, A., Lora, A.T., Bahamonde, A.: A factorization approach to evaluate open-response assignments in moocs using preference learning on peer assessments. Knowl.-Based Syst. 85, 322\u2013328 (2015)","journal-title":"Knowl.-Based Syst."},{"doi-asserted-by":"crossref","unstructured":"Manh\u00e3es, L.M.B., da Cruz, S.M.S., Zimbr\u00e3o, G.: WAVE: an architecture for predicting dropout in undergraduate courses using EDM. In: Symposium on Applied Computing, pp. 243\u2013247 (2014)","key":"27_CR16","DOI":"10.1145\/2554850.2555135"},{"doi-asserted-by":"crossref","unstructured":"Nesterko, S.O., Seaton, D.T., Reich, J., McIntyre, J., Han, Q., Chuang, I.L., Ho, A.D.: Due dates in MOOCs: does stricter mean better? In: First (2014) ACM Conference on Learning @ Scale, L@S 2014, Atlanta, GA, USA, 4\u20135 March 2014, pp. 193\u2013194 (2014)","key":"27_CR17","DOI":"10.1145\/2556325.2567877"},{"doi-asserted-by":"crossref","unstructured":"Qiu, J., Tang, J., Liu, T.X., Gong, J., Zhang, C., Zhang, Q., Xue, Y.: Modeling and predicting learning behavior in MOOCs. In: Proceedings of the Ninth ACM International Conference on Web Search and Data Mining, pp. 93\u2013102 (2016)","key":"27_CR18","DOI":"10.1145\/2835776.2835842"},{"unstructured":"Ramesh, A., Goldwasser, D., Huang, B., Daum\u00e9 III., H., Getoor, L.: Learning latent engagement patterns of students in online courses. In: Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 27\u201331 July 2014, Qu\u00e9bec City, Qu\u00e9bec, Canada, pp. 1272\u20131278 (2014)","key":"27_CR19"},{"unstructured":"Shah, N.B., Bradley, J., Parekh, A., Wainwright, M.J., Ramchandran, K.: A case for ordinal peer-evaluation in MOOCs. In: Neural Information Processing Systems (NIPS): Workshop on Data Driven Education (2013)","key":"27_CR20"},{"doi-asserted-by":"crossref","unstructured":"Sharkey, M., Sanders, R.: A process for predicting MOOC attrition (2014)","key":"27_CR21","DOI":"10.3115\/v1\/W14-4109"},{"doi-asserted-by":"crossref","unstructured":"She, J., Tong, Y., Chen, L.: Utility-aware social event-participant planning. In: SIGMOD 2015, pp. 1629\u20131643 (2015)","key":"27_CR22","DOI":"10.1145\/2723372.2749446"},{"issue":"9","key":"27_CR23","doi-asserted-by":"crossref","first-page":"2281","DOI":"10.1109\/TKDE.2016.2565468","volume":"28","author":"J She","year":"2016","unstructured":"She, J., Tong, Y., Chen, L., Cao, C.C.: Conflict-aware event-participant arrangement and its variant for online setting. IEEE Trans. Knowl. Data Eng. 28(9), 2281\u20132295 (2016)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"unstructured":"Taylor, C., Veeramachaneni, K., O\u2019Reilly, U.: Likely to stop? Predicting stopout in massive open online courses. CoRR, abs\/1408.3382 (2014)","key":"27_CR24"},{"issue":"12","key":"27_CR25","first-page":"1053","volume":"9","author":"Y Tong","year":"2016","unstructured":"Tong, Y., She, J., Ding, B., Chen, L., Wo, T., Xu, K.: Online minimum matching in real-time spatial data: experiments and analysis. PVLDB 9(12), 1053\u20131064 (2016)","journal-title":"PVLDB"},{"doi-asserted-by":"crossref","unstructured":"Tong, Y., She, J., Ding, B., Wang, L., Chen, L.: Online mobile micro-task allocation in spatial crowdsourcing. In: ICDE 2016, pp. 49\u201360 (2016)","key":"27_CR26","DOI":"10.1109\/ICDE.2016.7498228"},{"issue":"6","key":"27_CR27","doi-asserted-by":"crossref","first-page":"1151","DOI":"10.1007\/s11280-015-0377-6","volume":"19","author":"Y Tong","year":"2016","unstructured":"Tong, Y., She, J., Meng, R.: Bottleneck-aware arrangement over event-based social networks: the max-min approach. World Wide Web 19(6), 1151\u20131177 (2016)","journal-title":"World Wide Web"},{"issue":"3","key":"27_CR28","first-page":"614","volume":"52","author":"J Zhuoxuan","year":"2015","unstructured":"Zhuoxuan, J., Yan, Z., Xiaoming, L.: Learning behavior analysis and prediction based on MOOC data. J. Comput. Res. Dev. 52(3), 614\u2013628 (2015)","journal-title":"J. Comput. Res. Dev."}],"container-title":["Lecture Notes in Computer Science","Database Systems for Advanced Applications"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-55705-2_27","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,9,19]],"date-time":"2019-09-19T20:47:28Z","timestamp":1568926048000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-319-55705-2_27"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017]]},"ISBN":["9783319557045","9783319557052"],"references-count":28,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-55705-2_27","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2017]]}}}