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Based on interviews with 92 MOOC learners, the study identifies three experiential domains absent from tracking logs: activities at learners’ workstations, online-but-off-platform actions, and broader life social context. Findings expand understanding of learner agency, clarify gaps between recorded log events, and challenge the view of MOOCs learners as disembodied autodidacts.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/the-life-between-big-data-log-events-learners-strategies-to-overcome-challenges-in-moocs-read-online-free/589838/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/the-life-between-big-data-log-events-learners-strategies-to-overcome-challenges-in-moocs-read-online-free/589838.png","ImageObject",300,407,{"name":92,"@type":93},"Cipher","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-29","2026-10-15",true,{"@type":102,"interactionType":103,"userInteractionCount":44},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"Why is big data in MOOCs considered incomplete for studying learning?","Question",{"text":112,"@type":113},"Because clickstream and log data cannot capture every important element of learning and participation in digital environments, so key strategies and contexts may be absent.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"What three domains are absent from MOOCs tracking logs, according to the findings?",{"text":117,"@type":113},"Practices at learners’ workstations, online activities that occur off-platform, and the wider social context beyond the MOOC.",{"name":119,"@type":110,"acceptedAnswer":120},"How does the study use interviews to investigate learners’ strategies?",{"text":121,"@type":113},"It interviews 92 MOOC learners to understand what challenges they face and which strategies help them overcome those challenges, including both trackable and invisible actions.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},589838,1792171063,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":44,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":52,"language":139,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":140,"faqs":141,"seo_title":142,"seo_description":67,"update_tm":143,"read_time":144,"preview_page_count":4},687208528416,"https://ap-avatar.wpscdn.com/davatar_9964176cb1d06d4a9deccf72a44ae3dc","AERA Open  \nJuly-September 2016, Vol. 2, No. 3, pp. 1–10 DOI: 10. 1177/2332858416657002  \n© The Author(s) 2016. [http://ero.sagepub.com](http://ero.sagepub.com)  \nThe Life Between Big Data Log Events: Learners’ Strategies to Overcome Challenges in MOOCs  \nGeorge Veletsianos  \nRoyal Roads University  \nJustin Reich  \nMassachusetts Institute of Technology  \nLaura A. Pasquini  \nUniversity of North Texas and Royal Roads University  \nBig data from massive open online courses (MOOCs) have enabled researchers to examine learning processes at almost infinite levels of granularity. Yet, such data sets do not track every important element in the learning process. Many strategies that MOOC learners use to overcome learning challenges are not captured in clickstream and log data. In this study, we interviewed 92 MOOC learners to better understand their worlds, investigate possible mechanisms of student attrition, and extend conversations about the use of big data in education. Findings reveal three important domains of the experience of MOOC students that are absent from MOOC tracking logs: the practices at learners’workstations, learners’activities online but off-platform, and the wider social context of their lives beyond the MOOC. These findings enrich our understanding of learner agency in MOOCs, clarify the spaces in-between recorded tracking log events, and challenge the view that MOOC learners are disembodied autodidacts.  \nKeywords: massive open online course, big data, strategies, online learning, persistence  \nReflecting a broader societal trend toward big data, one of the most exciting features of contemporary digital learning environments is the extensive data that they collect about student behavior and learning. These new data sets enable educational researchers to examine learning processes at almost infinite levels of granularity, from patterns across millions of learners to the moment-to-moment activities of individuals. Recently, large data sets consisting of the trace and log data that learners generate in online learning environments have been employed to understand dropout and attrition. One risk in this development is that researchers may mistakenly assume that the data automatically collected by learning platforms offer a comprehensive and complete representation of learner behaviors. Education researchers (e.g., DeBoer & Breslow, 2014; Perna et al., 2014) and others (boyd & Crawford, 2012) have warned that massive data sets do not necessarily track the most important elements of human participation in digital environments. In this research, we aim to illustrate more precisely what big data are missing about digital learning and how other data sources can enrich our understanding of these gaps.  \nThis article draws on interviews with 92 students in massive open online courses (MOOCs) to examine the strategies they use to overcome the challenges they face. Our findings  \nindicate that some of their strategies, such as rewatching videos, returning to a course after a break, and rereading content, could appear in data automatically collected by learning platforms. Other strategies, such as asking family members for assistance or searching the web for supplementary study materials, are invisible to tracking logs. We present three important domains ofthe experience of MOOC students that are absent from the tracking logs: the practices at learners’workstations, learners’ activities online but off platform, and the wider social context of their lives beyond the MOOC. With the rise of sophisticated new methods of learning analytics (Siemens & Baker, 2012), researchers, faculty, and course developers have a growing and diverse body of quantitative data and computational research methods to guide improvements in MOOC design; our findings highlight the importance of drawing on other forms of research to design courses that support learners’needs and practices.  \nBackground and Context  \nThe term massive open online course descr","cbCaid07xzqn8lbx","https://ap.wps.com/l/cbCaid07xzqn8lbx","pdf",414218,"English","# Background and Context\n## What MOOCs track and what they miss\n## Attrition and persistence patterns\n## Limits of clickstream prediction","[{\"question\":\"Why is big data in MOOCs considered incomplete for studying learning?\",\"answer\":\"Because clickstream and log data cannot capture every important element of learning and participation in digital environments, so key strategies and contexts may be absent.\"},{\"question\":\"What three domains are absent from MOOCs tracking logs, according to the findings?\",\"answer\":\"Practices at learners’ workstations, online activities that occur off-platform, and the wider social context beyond the MOOC.\"},{\"question\":\"How does the study use interviews to investigate learners’ strategies?\",\"answer\":\"It interviews 92 MOOC learners to understand what challenges they face and which strategies help them overcome those challenges, including both trackable and invisible actions.\"}]","The Life Between Big Data Log Events: Learners’ Strategies to Overcome Challenges in MOOCs - read online free | PDF",1792068233,25]