[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-125130-en":3,"doc-seo-125130-105":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},125130,7971461740909,"Levi","https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d",8,"Research & Report","Machine learning based education data mining through student session streams - Research","Machine learning based education data mining analyzes student session streams from e-learning platforms to forecast academic performance, especially under the increased adoption of online learning during COVID-19. The work targets shortcomings of ensemble methods when datasets are imbalanced and feature effects are not properly emphasized. An improved modified XGBoost approach (MXGB) is proposed, incorporating an effective cross-validation scheme to capture feature correlations. Experimental results show higher prediction accuracy than state-of-the-art ensemble models, with better effectiveness for student performance prediction.","Machine learning based education data mining through student  \nsession streams  \nShashirekha Hanumanthappa1, Chetana Prakash2  \n1Department of Computer Science and Engineering, Visvesvaraya Technological University, Mysore, India 2Department of Computer Science and Engineering, Bapuji Institute of Engineering and Technology, Davanagere, India  \n\n| Article history:\u003Cbr>Received Oct 16, 2023 Revised Dec 18, 2023 Accepted Dec 30, 2023 | Recently, significant growth in using online-based learning stream (i.e., elearning systems) have been seen due to pandemic such as COVID-19. Forecasting student performance has become a major task as an institution is focusing on improving the quality of education and students' performance. Data mining (DM) employing machine learning (ML) techniques have been employed in the e-learning platform for analyzing student session streamsand predicting academic performance with good effects. A recent, study shows ML-based methodologies exhibit when data is imbalanced. In addressing ensemble learning by combining multiple ML algorithms for choosing the best model according to data. However, the existing ensemblebased model does not incorporate feature importance into the student performance prediction model. Thus, exhibits poor performance, especially for multi-label classification. In addressing this, this paper presents an improved ensemble learning mechanism by modifying the XGBoost algorithm, namely modified XGBoost (MXGB) . The MXGB incorporates an effective cross-validation scheme that learns correlation among features more efficiently. The experiment outcome shows the proposed MXGBabased student performance prediction model achieves much better prediction accuracy contrary to the state-of-art ensemble-based student performance prediction model.\u003Cbr>This is an open access article under the CC BY-SA license.\u003Cbr> |\n| --- | --- |\n| Keywords:\u003Cbr>Data imbalance E-learning Ensemble algorithm Feature importance Machine learning |  |\n\nCorresponding Author:  \nShashirekha Hanumanthappa  \nDepartment of Computer Science and Engineering, Visvesvaraya Technological University Ring Road, Hanchya Sathagally Layout, Mysore, Karnataka 570019 , India  \nEmail: [shashirekha_h2k22@rediffmail.com](shashirekha_h2k22@rediffmail.com)  \nArticle Info ABSTRACT  \n1. INTRODUCTION  \nWith the wide usage of the internet and the growth of information technology have affected the way academics and industries learn i.e., it is moved from the conventional offline mode to online mode namely the e-learning platform [1] . Especially during the COVID-19 pandemic period, all classes have moved to an online model, highlighting the significance of the e-learning platform. However, significant challenges exist in providing a reliable and accurate model to predict student performance [2] . Designing an effective assessment model for understanding student behavior using session streams of the e-learning platform will aid in improving students’ academic performance by providing personalized content.  \nPersonalized content delivery for improving student performance according to individual behavior in the e-learning platform is the major challenge of the current century [3] . Adaptive personalizing techniques for understanding learner profiles have been emphasized [4], [5] . Recently, data mining (DM) and machine learning (ML) have been used for building student performanceprediction models. The DM has been used for establishing useful insight from student session stream data of the e-learning platform as shown in Figure 1;  \nalongside, improves decision-making performance by establishing behavior patter from data [6]–[9] . Both MLand DM methodologies are very promising in different fields such as business, and network security including education. Recently, a new field has emerged namely education data mining (EDM) for enhancing learning style, understanding behavior, and improving student performance [10]–[13] . The EDM data is composed of differen","cbCaisN0TpdE8lVW","https://ap.wps.com/l/cbCaisN0TpdE8lVW","pdf",544307,1,12,"English","en",105,"# Introduction\n## Education data mining and student performance prediction\n## Data imbalance and ensemble learning limitations\n# Proposed method: MXGB","[{\"question\":\"Why is student performance forecasting important in e-learning?\",\"answer\":\"Educational institutions use online learning to improve learning quality, and reliable prediction models help assess student performance more accurately and support personalized assessment.\"},{\"question\":\"What problem does the paper address in existing ensemble-based models?\",\"answer\":\"Existing ensembles perform poorly when data is imbalanced, and they do not incorporate feature importance effectively, leading to weak multi-label classification accuracy.\"},{\"question\":\"How does the proposed MXGB improve prediction accuracy?\",\"answer\":\"MXGB modifies XGBoost by introducing an improved cross-validation mechanism that learns correlations among features more efficiently, strengthening the performance prediction model.\"}]","Machine learning based education data mining through student session streams - Research | PDF",1785896826,30,{"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},"machine-learning-based-education-data-mining-through-student-session-streams-research","",{"@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/machine-learning-based-education-data-mining-through-student-session-streams-research/125130/",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","2026-08-05",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},"Why is student performance forecasting important in e-learning?","Question",{"text":75,"@type":76},"Educational institutions use online learning to improve learning quality, and reliable prediction models help assess student performance more accurately and support personalized assessment.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"What problem does the paper address in existing ensemble-based models?",{"text":80,"@type":76},"Existing ensembles perform poorly when data is imbalanced, and they do not incorporate feature importance effectively, leading to weak multi-label classification accuracy.",{"name":82,"@type":73,"acceptedAnswer":83},"How does the proposed MXGB improve prediction accuracy?",{"text":84,"@type":76},"MXGB modifies XGBoost by introducing an improved cross-validation mechanism that learns correlations among features more efficiently, strengthening the performance prediction model.","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},[93,97,101,105,110,115,120,122,127,130,134],{"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":29,"slug":121},"research-report",{"id":123,"doc_module":4,"doc_module_name":46,"category_name":124,"show_sort_weight":125,"slug":126},9,"Religion & Spirituality",20,"religion-spirituality",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":128,"show_sort_weight":125,"slug":129},"World Cup","world-cup",{"id":131,"doc_module":4,"doc_module_name":46,"category_name":132,"show_sort_weight":131,"slug":133},10,"Lifestyle","lifestyle",{"id":135,"doc_module":4,"doc_module_name":46,"category_name":136,"show_sort_weight":106,"slug":137},19,"General","general"]