{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,15]],"date-time":"2025-12-15T19:09:15Z","timestamp":1765825755449,"version":"3.40.3"},"publisher-location":"Cham","reference-count":28,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319985718"},{"type":"electronic","value":"9783319985725"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1007\/978-3-319-98572-5_27","type":"book-chapter","created":{"date-parts":[[2018,8,13]],"date-time":"2018-08-13T14:39:10Z","timestamp":1534171150000},"page":"355-369","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":31,"title":["Predicting Learners\u2019 Success in a Self-paced MOOC Through Sequence Patterns of Self-regulated Learning"],"prefix":"10.1007","author":[{"given":"Jorge","family":"Maldonado-Mahauad","sequence":"first","affiliation":[]},{"given":"Mar","family":"P\u00e9rez-Sanagust\u00edn","sequence":"additional","affiliation":[]},{"given":"Pedro Manuel","family":"Moreno-Marcos","sequence":"additional","affiliation":[]},{"given":"Carlos","family":"Alario-Hoyos","sequence":"additional","affiliation":[]},{"given":"Pedro J.","family":"Mu\u00f1oz-Merino","sequence":"additional","affiliation":[]},{"given":"Carlos","family":"Delgado-Kloos","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2018,8,14]]},"reference":[{"key":"27_CR1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-662-49851-4","volume-title":"Process mining: data science in action","author":"WMP Van der Aalst","year":"2016","unstructured":"Van der Aalst, W.M.P.: Process mining: data science in action. Springer, Heidelberg (2016)"},{"issue":"2","key":"27_CR2","doi-asserted-by":"publisher","first-page":"139","DOI":"10.1024\/1010-0652.23.2.139","volume":"23","author":"M Bannert","year":"2009","unstructured":"Bannert, M.: Promoting self-regulated learning through prompts. Zeitschrift f\u00fcr P\u00e4dagogische Psychol. 23(2), 139\u2013145 (2009)","journal-title":"Zeitschrift f\u00fcr P\u00e4dagogische Psychol."},{"issue":"3","key":"27_CR3","doi-asserted-by":"publisher","first-page":"218","DOI":"10.1111\/jcal.12130","volume":"32","author":"PG de Barba","year":"2016","unstructured":"de Barba, P.G., et al.: The role of students\u2019 motivation and participation in predicting performance in a MOOC. J. Comput. Assist. Learn. 32(3), 218\u2013231 (2016)","journal-title":"J. Comput. Assist. Learn."},{"issue":"2","key":"27_CR4","doi-asserted-by":"publisher","first-page":"161","DOI":"10.1016\/S0959-4752(96)00015-1","volume":"7","author":"M Boekaerts","year":"1997","unstructured":"Boekaerts, M.: Self-regulated learning: a new concept embraced by researchers, policy makers, educators, teachers, and students. Learn. Instr. 7(2), 161\u2013186 (1997)","journal-title":"Learn. Instr."},{"issue":"14","key":"27_CR5","doi-asserted-by":"publisher","first-page":"3677","DOI":"10.1109\/TSP.2016.2546228","volume":"64","author":"CG Brinton","year":"2016","unstructured":"Brinton, C.G., et al.: Mining MOOC clickstreams: video-watching behavior vs. in-video quiz performance. IEEE Trans. Signal Process. 64(14), 3677\u20133692 (2016)","journal-title":"IEEE Trans. Signal Process."},{"key":"27_CR6","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1016\/j.iheduc.2017.01.004","volume":"33","author":"J Broadbent","year":"2017","unstructured":"Broadbent, J.: Comparing online and blended learner\u2019s self-regulated learning strategies and academic performance. Internet High. Educ. 33, 24\u201332 (2017)","journal-title":"Internet High. Educ."},{"key":"27_CR7","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.iheduc.2015.04.007","volume":"27","author":"J Broadbent","year":"2015","unstructured":"Broadbent, J., Poon, W.L.: Self-regulated learning strategies & academic achievement in online higher education learning environments: a systematic review. Internet High. Educ. 27, 1\u201313 (2015)","journal-title":"Internet High. Educ."},{"key":"27_CR8","doi-asserted-by":"crossref","unstructured":"Chuang, I., Ho, A.D.: HarvardX and MITx: Four Years of Open Online Courses\u2013Fall 2012-Summer 2016 (2016)","DOI":"10.2139\/ssrn.2889436"},{"key":"27_CR9","doi-asserted-by":"crossref","unstructured":"Corrin, L., et al.: Using learning analytics to explore help-seeking learner profiles in MOOCs. In: Proceedings of the Seventh International Learning Analytics & Knowledge Conference, pp. 424\u2013428 (2017)","DOI":"10.1145\/3027385.3027448"},{"key":"27_CR10","doi-asserted-by":"publisher","first-page":"327","DOI":"10.1016\/j.compedu.2018.05.019","volume":"125","author":"D Davis","year":"2018","unstructured":"Davis, D., et al.: Activating learning at scale: a review of innovations in online learning strategies. Comput. Educ. 125, 327\u2013344 (2018)","journal-title":"Comput. Educ."},{"key":"27_CR11","unstructured":"Grainger, B.: Massive open online course (MOOC) report 2013. University of London. (2013)"},{"key":"27_CR12","first-page":"40","volume":"940","author":"CW G\u00fcnther","year":"2012","unstructured":"G\u00fcnther, C.W., Rozinat, A.: Disco: discover your processes. Bus. Process Manag. 940, 40\u201344 (2012)","journal-title":"Bus. Process Manag."},{"key":"27_CR13","doi-asserted-by":"publisher","first-page":"83","DOI":"10.1016\/j.compedu.2015.10.019","volume":"91","author":"N Hood","year":"2015","unstructured":"Hood, N., et al.: Context counts: how learners\u2019 contexts influence learning in a MOOC. Comput. Educ. 91, 83\u201391 (2015)","journal-title":"Comput. Educ."},{"key":"27_CR14","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1016\/j.compedu.2016.10.001","volume":"104","author":"RF Kizilcec","year":"2017","unstructured":"Kizilcec, R.F., et al.: Self-regulated learning strategies predict learner behavior and goal attainment in Massive Open Online Courses. Comput. Educ. 104, 18\u201333 (2017)","journal-title":"Comput. Educ."},{"key":"27_CR15","first-page":"1","volume":"19","author":"S Kocdar","year":"2018","unstructured":"Kocdar, S., et al.: Measuring self-regulation in self-paced open and distance learning environments. Int. Rev. Res. Open Distrib. Learn. 19, 1 (2018)","journal-title":"Int. Rev. Res. Open Distrib. Learn."},{"key":"27_CR16","doi-asserted-by":"crossref","unstructured":"Kovanovi\u0107, V. et al.: Penetrating the black box of time-on-task estimation. In: Proceedings of the Fifth International Conference Learning Analytics and Knowledge - LAK 2015. October, pp. 184\u2013193 (2015)","DOI":"10.1145\/2723576.2723623"},{"issue":"1","key":"27_CR17","doi-asserted-by":"publisher","first-page":"159","DOI":"10.2307\/2529310","volume":"33","author":"JR Landis","year":"1977","unstructured":"Landis, J.R., Koch, G.G.: The measurement of observer agreement for categorical data. Biometrics. 33(1), 159\u2013174 (1977)","journal-title":"Biometrics."},{"key":"27_CR18","doi-asserted-by":"publisher","first-page":"40","DOI":"10.1016\/j.iheduc.2015.12.003","volume":"29","author":"A Littlejohn","year":"2016","unstructured":"Littlejohn, A., et al.: Learning in MOOCs: motivations and self-regulated learning in MOOCs. Internet High. Educ. 29, 40\u201348 (2016)","journal-title":"Internet High. Educ."},{"key":"27_CR19","doi-asserted-by":"publisher","first-page":"179","DOI":"10.1016\/j.chb.2017.11.011","volume":"80","author":"J Maldonado-Mahauad","year":"2018","unstructured":"Maldonado-Mahauad, J., et al.: Mining theory-based patterns from Big data: identifying self-regulated learning strategies in Massive Open Online Courses. Comput. Hum. Behav. 80, 179\u2013196 (2018)","journal-title":"Comput. Hum. Behav."},{"key":"27_CR20","doi-asserted-by":"crossref","unstructured":"Maldonado, J.J., et al.: Exploring differences in how learners navigate in MOOCs based on self-regulated learning and learning styles: A process mining approach. In: Computing Conference (CLEI), 2016 XLII Latin American, pp. 1\u201312 (2016)","DOI":"10.1109\/CLEI.2016.7833356"},{"key":"27_CR21","doi-asserted-by":"publisher","first-page":"269","DOI":"10.1007\/3-540-32392-9_28","volume-title":"Intelligent Information Processing and Web Mining. Advances in Soft Computing","author":"A-D Mezaour","year":"2005","unstructured":"Mezaour, A.-D.: Filtering web documents for a thematic warehouse case study: eDot a food risk data warehouse (extended). In: K\u0142opotek, M.A., Wierzcho\u0144, S.T., Trojanowski, K. (eds.) Intelligent Information Processing and Web Mining. Advances in Soft Computing, vol. 31, pp. 269\u2013278. Springer, Berlin, Heidelberg (2005). https:\/\/doi.org\/10.1007\/3-540-32392-9_28"},{"issue":"5","key":"27_CR22","first-page":"1","volume":"37","author":"PM Moreno-Marcos","year":"2018","unstructured":"Moreno-Marcos, P.M., et al.: Analysing the predictive power for anticipating assignment grades in a massive open online course. Behav. Inf. Technol. 37(5), 1\u201316 (2018)","journal-title":"Behav. Inf. Technol."},{"key":"27_CR23","doi-asserted-by":"crossref","unstructured":"Pardo, A. et al.: Generating actionable predictive models of academic performance. In: Proceedings of the Sixth International Conference on Learning Analytics & Knowledge, pp. 474\u2013478 (2016)","DOI":"10.1145\/2883851.2883870"},{"issue":"6217","key":"27_CR24","doi-asserted-by":"publisher","first-page":"34","DOI":"10.1126\/science.1261627","volume":"347","author":"J Reich","year":"2015","unstructured":"Reich, J.: Rebooting MOOC research. Science 347(6217), 34\u201335 (2015)","journal-title":"Science"},{"key":"27_CR25","doi-asserted-by":"crossref","unstructured":"Sinha, T. et al.: Your click decides your fate: Inferring information processing and attrition behavior from mooc video clickstream interactions. arXiv Prepr. arXiv1407.7131. (2014)","DOI":"10.3115\/v1\/W14-4102"},{"key":"27_CR26","first-page":"4","volume":"2016","author":"B Xu","year":"2016","unstructured":"Xu, B., Yang, D.: Motivation classification and grade prediction for MOOCs learners. Comput. Intell. Neurosci. 2016, 4 (2016)","journal-title":"Comput. Intell. Neurosci."},{"key":"27_CR27","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1016\/j.iheduc.2015.11.003","volume":"29","author":"JW You","year":"2016","unstructured":"You, J.W.: Identifying significant indicators using LMS data to predict course achievement in online learning. Internet High. Educ. 29, 23\u201330 (2016)","journal-title":"Internet High. Educ."},{"key":"27_CR28","doi-asserted-by":"crossref","unstructured":"Zhao, C., et al.: Discover learning behavior patterns to predict certification. In: 2016 11th International Conference on Computer Science & Education (ICCSE), pp. 69\u201373 (2016)","DOI":"10.1109\/ICCSE.2016.7581557"}],"container-title":["Lecture Notes in Computer Science","Lifelong Technology-Enhanced Learning"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-98572-5_27","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,7]],"date-time":"2024-03-07T16:18:31Z","timestamp":1709828311000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-319-98572-5_27"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783319985718","9783319985725"],"references-count":28,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-98572-5_27","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2018]]},"assertion":[{"value":"14 August 2018","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"EC-TEL","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"European Conference on Technology Enhanced Learning","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Leeds","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"United Kingdom","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3 September 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6 September 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ectel2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.ec-tel.eu\/index.php?id=805","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"142","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}