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This study evaluates a context-specific decision-based tutoring approach that assesses understanding, prescribes feedback, and supports correct decision-making. Using a refrigeration problem, 373 students used a single 40-minute tutor activity and demonstrated significant improvement in understanding (p\u003C0.0001, Cohen’s d>0.8).",{"@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/intelligent-tutoring-system-using-decision-based-learning-for-thermodynamic-phase-diagrams/588704/",{"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/intelligent-tutoring-system-using-decision-based-learning-for-thermodynamic-phase-diagrams/588704.png","ImageObject",300,407,{"name":92,"@type":93},"Rizky","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-11-10","2026-10-15",true,{"@type":102,"interactionType":103,"userInteractionCount":14},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What learning mechanism does the study emphasize for thermodynamics?","Question",{"text":112,"@type":113},"The study emphasizes connecting new information to existing understanding or modifying understanding to accept new information.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How does the proposed tutor system support student problem solving?",{"text":117,"@type":113},"It assesses understanding through context-specific problem-solving decisions, prescribes feedback based on that assessment, and helps students reach correct decision-making.",{"name":119,"@type":110,"acceptedAnswer":120},"What were the study’s results after using the tutor activity?",{"text":121,"@type":113},"All groups (373 students) showed significant improvement in understanding after a single 40-minute tutor activity (p\u003C0.0001, Cohen’s d>0.8).","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},588704,1792065776,{"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":14,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":139,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":129,"read_time":144,"preview_page_count":4},962085564807,"https://ap-avatar.wpscdn.com/davatar_6f874abed73319feea01a86fa6f0fab8","| | Ad | vances in Engineering Edu | cation |  |  |\n| --- | --- | --- | --- | --- | --- |\n|  |  |  |  | |  |\n|  |  |  |  |  |  |\n\nSPRING 2017  \nIntelligent Tutoring System Using Decision Based Learning for Thermodynamic Phase Diagrams  \nMATHEW HAGGE MOSTAFA AMIN-NASERI JOHN JACKMAN ENRUO GUO  \nSTEPHEN B. GILBERT AND  \nGLORIA STARNS Iowa State University Ames, IA  \nAND  \nLEANN FAIDLEY Wartburg College Waverly, IA  \nABSTRACT  \nStudents learn when they connect new information to existing understanding or when they modify existing understanding to accept new information. Most current teaching methods focus on trying to get students to solve problems in a manner identical to that of an expert. This study investigates the effectiveness of assessing student understanding related to context specific problem solving decisions, prescribing feedback based on the assessment, and improving student understanding to the point where they can make correct decisions. Students were given a refrigeration problem unlike their prior problems and were asked to draw the cycle on a T-v diagram using a tutor system. Every group tested (a total of 373 students) showed a significant improvement in their understanding (p\u003C0 . 0001, Cohen’s d>0 . 8) using a single 40 minute tutor activity.  \nKey words: Thermodynamics, intelligent tutoring, misunderstanding  \nADVANCES IN ENGINEERING EDUCATION  \nIntelligent Tutoring System Using Decision Based Learning for Thermodynamic Phase Diagrams  \nINTRODUCTION  \nIt is well established that thermodynamics is a major challenge for undergraduate engineering students in terms of their ability to understand and properly use the concepts and principles at a level that is necessary to solve engineering problems (Miller, 2006; Streveler et al. , 2008, Prevost et al. , 2012) . In addition, students develop misconceptions about thermodynamics that lead them to incorrect solutions. Chi (2008) and Reiner, et al. (2000) address the question of why some misconceptions are particularly prevalent and difficult to correct. Their results suggest that particularly problematic misconceptions may be based on metaphors to physical phenomena that are similar but not quite right, e.g. thinking of electrical current as a fluid. Or, difficult misconceptions are based on phenomena with unobservable components or relationships.  \nOne approach to improving student understanding of thermodynamics was to create more interactive instructional materials using computer-based instruction to supplement traditional textbooks (Anderson et al. , 2005; Taraban, 2003) . Interactions included answering multiple choice and short answer questions as well as controlling simulations of device and system behaviors. However, their results did not indicate significant improvement in student understanding.  \nResearchers have attempted to define and test student understanding of the set of concepts needed to solve problems in thermal-fluids courses (Streveler 2003; Prince 2012) . Turns & Van Meter (2011) argued that how students structure their declarative knowledge is strongly linked to their problem framing ability. They recommended explicit explanations of the essential concepts and the problem solving process along with mechanisms for engaging students in problem solving. To identify students’ misconceptions about thermodynamics, Beall (1994) posed conceptual questions to the students and asked them to write a response. This assessment of student understanding was used to clear up misconceptions in subsequent lectures.  \nBuilding on this work, Prevost et al. (2012) scaled the approach to large classes using automated text analysis to provide instructors with an analysis of students’ constructed responses. The goal was to automatically generate a report for instructors so that they could address any problems by the next class meeting by providing feedback to students or modifying instructional materials.  \nAlthough there is wide variation in student understanding, ty","cbCairdmfshNlC0P","https://ap.wps.com/l/cbCairdmfshNlC0P","pdf",2563215,22,"English","# Abstract\n# Introduction\n# Related Literature on Learning","[{\"question\":\"What learning mechanism does the study emphasize for thermodynamics?\",\"answer\":\"The study emphasizes connecting new information to existing understanding or modifying understanding to accept new information.\"},{\"question\":\"How does the proposed tutor system support student problem solving?\",\"answer\":\"It assesses understanding through context-specific problem-solving decisions, prescribes feedback based on that assessment, and helps students reach correct decision-making.\"},{\"question\":\"What were the study’s results after using the tutor activity?\",\"answer\":\"All groups (373 students) showed significant improvement in understanding after a single 40-minute tutor activity (p\\u003c0.0001, Cohen’s d\\u003e0.8).\"}]","Intelligent Tutoring System Using Decision Based Learning for Thermodynamic Phase Diagrams | PDF",55]