[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-122892-en":3,"doc-seo-122892-105":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},122892,549758252649,"Ivy","https://ap-avatar.wpscdn.com/avatar/8000253669c5317157?_k=1778319167496531819",8,"Research & Report","Applications of Machine Learning in Content Generation for Educational Video Games - An Undergraduate Research Scholars Thesis","Students often lose motivation to read assigned textbooks despite their proven benefits for comprehension and overall classroom performance. Game-Based Learning offers intrinsic motivation through interactive videogame experiences, suggesting a path to transform static textbook material into engaging learning assets. This thesis investigates whether machine learning and artificial intelligence can generate interactive educational game content that supports or supplements traditional instruction. The work lays groundwork by reformatting textbooks into interactive chatbot AIs using knowledge compilation and fact-retrieval systems.","APPLICATION OF MACHINE LEARNING IN CONTENT GENERATION  \nFOR EDUCATIONAL VIDEO GAMES  \nAn Undergraduate Research Scholars Thesis  \nby  \nLLOYD DONELAN, BRENTON LENZEN, and KISHAN PATEL  \nSubmitted to the Undergraduate Research Scholars program at Texas A&M University  \nin partial fulfillment of the requirements for the designation as an  \nUNDERGRADUATE RESEARCH SCHOLAR  \nApproved by Research Advisors: Professor Andre Thomas  \nProfessor Hadeel Ramadan Dr. Theodora Chaspari  \nMay 2020  \nMajor: Computer Science  \nTABLE OF CONTENTS  \nPage  \nABSTRACT..................................................................................................................................... 1  \nNOMENCLATURE ........................................................................................................................3  \nCHAPTER  \nI. INTRODUCTION .........................................................................................................4  \nBackground Information and Research Motivations ...............................................4  \nDifferences from Previous Studies ..........................................................................5  \nProject Expectations.................................................................................................6  \nPotential Future Tasks..............................................................................................7  \nII. METHODS ....................................................................................................................8  \nNLP Pipeline Conceptual Overview ........................................................................8  \nFirst Iteration of the Text Parser ............................................................................ 13  \nFirst Iteration of the Chatbot.................................................................................. 14  \nSecond Iteration of the Chatbot .............................................................................14  \nSecond Iteration of the Text Parser: The NLP Pipeline.........................................15  \nFirst Attempt at Generating Knowledge Bundles ..................................................16  \nSecond Attempt at Generating Knowledge Bundles .............................................18  \nIII. RESULTS ....................................................................................................................22  \nAnalysis of Question Generation Using Knowledge Bundle Attempt \\#1 .............22  \nQuestion Generation Good Examples (Knowledge Bundle Attempt \\#1) ..............22  \nQuestion Generation Mixed Examples (Knowledge Bundle Attempt \\#1) ............23  \nQuestion Generations Bad Examples (Knowledge Bundle Attempt \\#1) ...............23  \nAnalysis of Knowledge Bundle Attempt \\#2 ..........................................................24  \nIV. CONCLUSION ............................................................................................................27  \nREFERENCES ..............................................................................................................................30  \nAPPENDIX A: DICTIONARY-GEN ALGORITHM ..................................................................32  \nAPPENDIX B: QUESTION-GEN ALGORITHM .......................................................................36  \nABSTRACT  \nApplications of Machine Learning in Content Generation for Educational Video Games  \nLloyd Donelan, Brenton Lenzen, and Kishan Patel  \nDepartment of Computer Science & Engineering  \nTexas A&M University  \nResearch Advisors: Professor Andre Thomas and Professor Hadeel Ramadan  \nDepartment of Visualization  \nTexas A&M University  \nResearch Advisor: Dr. Theodora Chaspari  \nDepartment of Computer Science & Engineering  \nTexas A&M University  \nOver the past few years, students have become increasingly unmotivated to read their assigned textbooks as an accompaniment to classroom lectures and activities. Reading the textbook i","cbCaifuCslnWIdYn","https://ap.wps.com/l/cbCaifuCslnWIdYn","pdf",573615,1,42,"English","en",105,"# Abstract\n# Nomenclature\n# I. Introduction\n## Background Information and Research Motivations\n## Differences from Previous Studies\n## Project Expectations\n## Potential Future Tasks\n# II. Methods\n## NLP Pipeline Conceptual Overview\n## First Iteration of the Text Parser\n## First Iteration of the Chatbot\n## Second Iteration of the Chatbot\n## Second Iteration of the Text Parser: The NLP Pipeline\n## First Attempt at Generating Knowledge Bundles\n## Second Attempt at Generating Knowledge Bundles\n# III. Results\n## Analysis of Question Generation Using Knowledge Bundle Attempt #1\n## Question Generation Examples and Quality (Attempt #1)\n## Analysis of Knowledge Bundle Attempt #2\n# IV. Conclusion\n# References\n# Appendix A: Dictionary-Gen Algorithm\n# Appendix B: Question-Gen Algorithm","[{\"question\":\"Why focus on machine learning for educational video game content generation?\",\"answer\":\"The thesis targets low student motivation to read textbooks and explores whether game-based approaches can improve engagement and knowledge retention using ML and AI to generate interactive content.\"},{\"question\":\"What is the proposed approach for turning textbooks into interactive learning experiences?\",\"answer\":\"The team aims to reformat school textbooks into interactive chatbot AIs supported by knowledge compilation and fact-retrieval systems designed for educational video game content generation.\"},{\"question\":\"How were results evaluated in the project?\",\"answer\":\"Results analyze question generation quality using knowledge bundle attempts, including good, mixed, and bad examples for the first attempt and further analysis for the second attempt.\"}]","Applications of Machine Learning in Content Generation for Educational Video Games - An Undergraduate Research Scholars Thesis | PDF",1785813529,106,{"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},"applications-of-machine-learning-in-content-generation-for-educational-video-games-an-undergraduate-research-scholars-thesis","",{"@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/applications-of-machine-learning-in-content-generation-for-educational-video-games-an-undergraduate-research-scholars-thesis/122892/",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 focus on machine learning for educational video game content generation?","Question",{"text":75,"@type":76},"The thesis targets low student motivation to read textbooks and explores whether game-based approaches can improve engagement and knowledge retention using ML and AI to generate interactive content.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"What is the proposed approach for turning textbooks into interactive learning experiences?",{"text":80,"@type":76},"The team aims to reformat school textbooks into interactive chatbot AIs supported by knowledge compilation and fact-retrieval systems designed for educational video game content generation.",{"name":82,"@type":73,"acceptedAnswer":83},"How were results evaluated in the project?",{"text":84,"@type":76},"Results analyze question generation quality using knowledge bundle attempts, including good, mixed, and bad examples for the first attempt and further analysis for the second attempt.","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"]