[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-118636-en":3,"doc-seo-118636-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},118636,687197207919,"Theodora","https://ap-avatar.wpscdn.com/avatar/a000253d6f5f7c60be?x-image-process=image/resize,m_fixed,w_180,h_180&k=1779446848396160552",8,"Research & Report","Towards Personalized Human Learning At Scale: A Machine Learning Approach","This thesis examines personalized learning in education and its promise to tailor instruction, learning materials, learning paths, analytics, and reporting to each learner in order to strengthen learning outcomes. It addresses limitations of current approaches that depend on expert instructors, are costly, limited in availability, and cannot scale to growing demand. Using machine-learning techniques, the work develops computational models trained on educational big data to support core personalized-learning activities, including content customization, learning analytics, and trustworthy deployment methods.","RICE UNIVERSITY  \nTowards Personalized Human Learning At Scale: A Machine Learning Approach  \nBy Zichao Wang  \nA THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE  \nDoctor of Philosophy  \nAPPROVED, THESIS COMMITTEE  \nRichard Baraniuk (Apr 12, 2023 07:02 CDT)  \nRichard G. Baraniuk  \nC. Sidney Burrus Professor of  \nElectrical and Computer Engineering  \ninagarr(Ar~~ ~~~~g~~,~~ ~~2arr023~~ ~~10:CDT)~~  ~~Santiago Segarra  \nW. M. Rice Trustee Assistant Professor of Electrical and Computer Engineering  \nAndrew Lan  \nAssistant Professor, College of Information and Computer Sciences, University of Massachusetts Amherst  \nMichael C Mozer (Apr 13, 2023 08:51 EDT)  \nMike Mozer  \nSenior Staff Research Scientist, Google Brain, and Professor, Department of Computer Science and Institute of Cognitive Science, University of Colorado, Boulder  \nAnshumali Shrivastava  \nAssociate Professor of Computer Science  \nHOUSTON, TEXAS April 2023  \nABSTRACT  \nTowards Personalized Human Learning At Scale:  \nA Machine Learning Approach  \nby  \nZichao Wang  \nThis thesis focuses on personalized learning in education, a promising and effective means of learning where the instructions, educational materials, learning paths, analytics, and reports are tailored to each learner to best support their individual learning pathsand improve learning outcomes. Current personalized learning relies heavily on expert instructors and is costly, has limited availability, and is unable to scale to meet the massive demand of learning today. This thesis takes a machine-learning approach to address the aforementioned issues by developing computational models that learn from educational big data to perform the activities central to personalized learning in education. First, I will present a series of works for learning content customization, including methods and systems to generate, evaluate, represent, and analyze different types of learning content such as math word problems, factual quizzes, and scientific formulae. Second, I will present two frameworks for learning analytics, which enable the understanding and tracking of the progress of large numbers of learners effectively and efficiently. Finally, I will present methodologies for trustworthy machine learning, a necessity for deploying machine learning systems in real-world educational scenarios. These methodologies include theoretical tools for understanding recurrent neural networks, the powerhouse underlying modern knowledge tracing models, and controllable data generation, enabling machines to behave more precisely according to human instructions.  \nAcknowledgments  \nThis journey is not possible without the support and trust of many individuals.  \nI owe deep gratitude to my thesis advisor, Rich Baraniuk, for cultivating me into an independent researcher, for making research a fun experience, and for instilling in me the confidence and passion to pursue a career in research. His vision, positivity, openness, and commitment to excellence have profoundly shaped the way I work and live.  \nI thank my long-time collaborator and mentor, Andrew Lan, for being my “go-to” person whenever I want to discuss research. Andrew taught me, patiently and hands-on, how to do research at the very beginning and is still doing so today. Most of my projects are the result of discussing and grinding with him. I hope our collaboration continues.  \nI thank the rest of my committee members, Santiago Segarra, Anshumali Shrivastava, and Mike Mozer, for their critical feedback on this thesis. I am also grateful to Mike for his insightful suggestions for my research during and beyond my time at Google Research.  \nI am fortunate to have spent productive and memorable times at three industry labs asa research intern under incredible mentorships: with Cheng Zhang at Microsoft Research Cambridge, with Anima Anandkumar and Weili Nie at NVIDIA Research, and with Caile Collins and Nathan Dass at Google Research. Their rigor, work et","cbCaieKNmLWuLodE","https://ap.wps.com/l/cbCaieKNmLWuLodE","pdf",16646079,1,303,"English","en",105,"# Abstract\n## Personalized learning and scalability problem\n## Machine-learning approach and core activities\n## Learning content customization\n## Learning analytics frameworks\n## Trustworthy machine learning methodologies","[{\"question\":\"What problem does the thesis address in personalized learning for education?\",\"answer\":\"Current personalized learning relies heavily on expert instructors, which makes it costly, limited in availability, and difficult to scale. The thesis targets these issues to meet large and growing learning demand.\"},{\"question\":\"How does the thesis use machine learning to enable personalized learning at scale?\",\"answer\":\"It develops computational models that learn from educational big data to perform key personalized-learning tasks, including content generation and evaluation, analytics for tracking progress, and trustworthy deployment methods.\"},{\"question\":\"What are the main components of the proposed work?\",\"answer\":\"The thesis covers learning content customization for multiple content types, learning analytics frameworks for understanding and tracking many learners efficiently, and methodologies for trustworthy machine learning in real-world educational scenarios.\"}]","Towards Personalized Human Learning At Scale: A Machine Learning Approach | PDF",1785684631,764,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"towards-personalized-human-learning-at-scale-a-machine-learning-approach","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/towards-personalized-human-learning-at-scale-a-machine-learning-approach/118636/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-02",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What problem does the thesis address in personalized learning for education?","Question",{"text":75,"@type":76},"Current personalized learning relies heavily on expert instructors, which makes it costly, limited in availability, and difficult to scale. The thesis targets these issues to meet large and growing learning demand.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How does the thesis use machine learning to enable personalized learning at scale?",{"text":80,"@type":76},"It develops computational models that learn from educational big data to perform key personalized-learning tasks, including content generation and evaluation, analytics for tracking progress, and trustworthy deployment methods.",{"name":82,"@type":73,"acceptedAnswer":83},"What are the main components of the proposed work?",{"text":84,"@type":76},"The thesis covers learning content customization for multiple content types, learning analytics frameworks for understanding and tracking many learners efficiently, and methodologies for trustworthy machine learning in real-world educational scenarios.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,123,128,131,135],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]