[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-123014-en":3,"doc-seo-123014-105":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},123014,8796095462418,"Noah","https://ap-avatar.wpscdn.com/avatar/80000253c1241d02b47?x-image-process=image/resize,m_fixed,w_180,h_180&k=1778826106357471780",8,"Research & Report","An Exploration of Online Instructor Performance Prediction Model Using LMS Data with Machine Learning Techniques","Predicting online instructors’ performance supports higher-education institutions in identifying learning and teaching issues early and enabling timely interventions to maintain educational service quality. A central challenge is selecting key indicators from large-scale learning management system (LMS) data. With recent advances in machine learning, instructor-performance prediction has gained new momentum in online education. This study uses a design science methodology to collect LMS data, select influential variables via wrapper-based feature selection, train and compare multiple models, and identify a best-performing Random Forest approach using eight variables with SMOTE.","Association for Information Systems  \nAIS Electronic Library (AISeL)  \n\n| CONF-IRM 2024 Proceedings | International Conference on Information Resources Management (CONF-IRM) |\n| --- | --- |\n| 2024\u003Cbr>An Exploration of Online Instructor Performance Prediction Model Using LMS Data with Machine Learning Techniques\u003Cbr>Gary Yu Zhao\u003Cbr>Northwest Missouri State University, [zhao@nwmissouri.edu](zhao@nwmissouri.edu)\u003Cbr>Cindy Zhiling Tu\u003Cbr>Northwest Missouri State University, [cindytu@nwmissouri.edu](cindytu@nwmissouri.edu)\u003Cbr>Yufei Yuan\u003Cbr>McMaster University, [yuanyuf@mcmaster.ca](yuanyuf@mcmaster.ca)\u003Cbr>Follow this and additional works at: [https://aisel.aisnet.org/confirm2024](https://aisel.aisnet.org/confirm2024) |  |\n\nRecommended Citation  \nZhao, Gary Yu; Tu, Cindy Zhiling; and Yuan, Yufei, \"An Exploration of Online Instructor Performance Prediction Model Using LMS Data with Machine Learning Techniques\" (2024) . CONF-IRM 2024 Proceedings. 17.  \n[https://aisel.aisnet.org/confirm2024/17](https://aisel.aisnet.org/confirm2024/17)  \nThis material is brought to you by the International Conference on Information Resources Management (CONFIRM) at AIS Electronic Library (AISeL) . It has been accepted for inclusion in CONF-IRM 2024 Proceedings by an authorized administrator of AIS Electronic Library (AISeL) . For more information, please contact [elibrary@aisnet.org](elibrary@aisnet.org).  \n5. An Exploration of Online Instructor Performance Prediction Model Using LMS Data with Machine Learning Techniques  \nGary Yu Zhao Northwest Missouri State University  \n[zhao@nwmissouri.edu](zhao@nwmissouri.edu)  \nCindy Zhiling Tu Northwest Missouri State University  \n[cindytu@nwmissouri.edu](cindytu@nwmissouri.edu)  \nYufei Yuan  \nMcMaster University  \n[yuanyuf@mcmaster.ca](yuanyuf@mcmaster.ca)  \nAbstract  \nPredicting online instructors’performance can help higher education institutions find issues and problems in the learning and teaching process as early as possible, giving them timely interventions to help ensure the quality of educational services. One of the significant challenges of evaluating and predicting online instructors’performance is to determine the key indicators from a large amount of data generated from the learning management system (LMS). The recent advancements in the continuous development of machine learning technology have led to a new momentum of teaching performance prediction in online education. In this paper, we follow the design science research methodology. Firstly, a dataset is collected from a Midwest university LMS platform, and we use a wrapper-based method to explore a simple and effective prediction model to select four sets of key influence variables. Then, we fit, tune, and compare various machine learning prediction models on different selected variable sets. Finally, we suggest that the Random Forest (RF) on eight selected variables with the Synthetic Minority Over-sampling Technique (SMOTE) is the best prediction model based on our work.  \nKeywords: Online instructor performance, Prediction model, LMS data, Machine learning, Design science.  \n1. Introduction  \nOnline programs and students have increased dramatically in higher education. Higher educational institutions have large volumes of data from ERP (Enterprise Resource Planning) and LMS (Learning Management System) platforms which can be used to improve the quality of academic programs, services, and managerial decisions (Anwar et al., 2014) . Researchers have done much research on predicting students’ academic performance in the online education context based on different modeling methods (Ahajjam et al., 2022; Chandna et al., 2021; Karimi et al., 2020; Khan et al., 2021; Yang, 2021; Yu, 2021) . Most existing studies use student demographic information, student socioeconomic data, students’ perception of the academic learning processes, and students’ key behavioral characteristic data to train and evaluate the prediction models (Costa et al., 2020). Howeve","cbCailm1praetURC","https://ap.wps.com/l/cbCailm1praetURC","pdf",403116,1,13,"English","en",105,"# Abstract\n# 1. Introduction\n# 2. Related Work","[{\"question\":\"Why is online instructor performance prediction important?\",\"answer\":\"It helps higher-education institutions detect problems in learning and teaching processes early, enabling timely interventions to improve educational service quality.\"},{\"question\":\"What key challenge does the paper address?\",\"answer\":\"Selecting the most important indicators from the large amount of data generated by the learning management system (LMS) for performance evaluation and prediction.\"},{\"question\":\"Which machine learning model and data strategy performed best?\",\"answer\":\"The study concludes that Random Forest using eight selected variables with SMOTE provides the best prediction performance based on their experiments.\"}]","An Exploration of Online Instructor Performance Prediction Model Using LMS Data with Machine Learning Techniques | PDF",1785814183,33,{"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},"an-exploration-of-online-instructor-performance-prediction-model-using-lms-data-with-machine-learning-techniques","",{"@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/an-exploration-of-online-instructor-performance-prediction-model-using-lms-data-with-machine-learning-techniques/123014/",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","2026-08-04",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 online instructor performance prediction important?","Question",{"text":75,"@type":76},"It helps higher-education institutions detect problems in learning and teaching processes early, enabling timely interventions to improve educational service quality.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"What key challenge does the paper address?",{"text":80,"@type":76},"Selecting the most important indicators from the large amount of data generated by the learning management system (LMS) for performance evaluation and prediction.",{"name":82,"@type":73,"acceptedAnswer":83},"Which machine learning model and data strategy performed best?",{"text":84,"@type":76},"The study concludes that Random Forest using eight selected variables with SMOTE provides the best prediction performance based on their experiments.","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"]