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Prior research indicates that environmental and structural design choices within schools affect outcomes, yet designers face many variables and thousands of feasible plans. This paper applies tradespace exploration (TSE), using a predictive model built from historical third- and fifth-grader test data and 86 descriptive variables. Multi-way ANOVA reduces these inputs to eight composite predictors, enabling thousands of design permutations and identification of Pareto-frontier classroom plans for targeted resource investment decisions.",{"@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/making-sense-of-multiple-options-for-the-design-of-a-classroom-abstract/602794/",{"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/making-sense-of-multiple-options-for-the-design-of-a-classroom-abstract/602794.png","ImageObject",300,407,{"name":92,"@type":93},"dabgoudw","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-11-02","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 problem does the paper address in classroom design?","Question",{"text":112,"@type":113},"Classroom designers must choose among thousands of possible plans while accounting for many environmental and structural variables that influence student learning outcomes.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How is tradespace exploration (TSE) used in this study?",{"text":117,"@type":113},"TSE is applied to model how multiple classroom design parameters affect test performance and cost, enabling evaluation of many design permutations and identification of the best alternatives.",{"name":119,"@type":110,"acceptedAnswer":120},"What modeling approach reduces the number of variables for prediction?",{"text":121,"@type":113},"The study builds a predictive model from historical test data and 86 descriptive variables, then uses main effects analysis with a multi-way ANOVA to reduce them to eight composite independent variables.","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},602794,1792252045,{"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":144,"read_time":41},3985747860484,"https://ap-avatar.wpscdn.com/davatar_276721f389ce27ea32af1340a28f341c","MAKING SENSE OF MULTIPLE OPTIONS FOR THE DESIGN OF A CLASSROOM  \nEDWARD DUNCANSON  \nWestern Connecticut State University, U.S.A.  \nMICHAEL CURRY  \nDraper Laboratory in Cambridge, MA, U.S.A.  \nABSTRACT  \nThe changing nature of education has forced educators to rethink the role of classrooms in student learning. Prior research has shown that the environmental and structural design of education centers impact student learning. With a dozen variables to deal with, classroom designers are faced with the daunting task of selecting one plan from the thousands that are possible. This paper demonstrates how tradespace exploration (TSE), an analytical methodology used by NASA and the DoD to design spacecraft and other complex systems, can be applied to the design of classrooms. To demonstrate the TSE methodology, a predictive model was built based on historical data collected by prior researchers on third and fifth grader test performance and data along 86 descriptive variables that they used to characterize the school and classrooms. An analysis of main effects using a multi-way ANOVA allowed the larger data set to be reduced to 8 composite independent variables that are predictive of student tests scores. This model was then used to generate thousands of possible school and classroom design permutations and predict the resulting student test scores. This allowed the authors to identify the Pareto frontier of designs that yield the greatest benefits for a given investment. The case study described in this paper demonstrates how this approach could be applied to enable decision-makers to identify a more effective allocation of resources or determine when changes in total investment are likely to have a significant impact on desired performance.  \nINTRODUCTION  \nCan the designers of classrooms borrow a process used by satellite project managers to select a design that yields the greatest outcome for the investment? In both cases, designers have a variety of features that come in different sizes to choose from: multiple options yield thousands of variations of the final product. NASA and the Department of Defense (DoD) are currently using a process called tradespace exploration (TSE) to model the effects of multiple design parameters and aid in the selection of a plan that best addresses an immediate need. This paper represents an initial attempt to demonstrate how TSE can be utilized to inform classroom design decisions that result in the greatest student achievement for the money invested.  \nBACKGROUND  \nThe changing nature of education has forced educators to rethink the role of classrooms in student learning. School facility planners need to pay a greater amount of attention to the design of classrooms. Improvements at that level “will directly benefit the young children in schools”(Achilles, 1999, p. 2) . Students relate to the built surroundings where they spend a school day. The environmental and structural design of this learning center impacts student learning (Earthman & LeMasters, 2009; Tanner, 2009, 2014) .  \n“Structure must change before culture can change”(Ouchi, 2004, p. 18) . There are several structural and environmental factors (controlled variables) that contribute to student success. Among these are: floor space, ceiling height (relates to room volume), area of window glass (relates  \nEducational Planning 2020 51 Vol. 27, No. 2  \nto natural light), light fixtures, temperature control, air quality, cleanliness, air conditioning, safety, noise level, view of the environment, color of classroom walls, and cost (American Federation of Teachers, 2006; Duncanson, 2014; Earthman, 2004; National Summit on School Design, 2005; Tanner, 2014) . With a dozen variables to deal with, classroom designers are faced with the task of selecting one plan from the thousands that are possible.  \nTHEORY OF MAKING CHOICES  \nPeople make choices every day without a lot of thought: what to wear, what to eat. Decisions that affect a lot of people","cbCaimHHeCGwVBYp","https://ap.wps.com/l/cbCaimHHeCGwVBYp","pdf",252446,12,"English","# Abstract\n# Introduction\n# Background\n# Theory of Making Choices\n# Tradespace Exploration","[{\"question\":\"What problem does the paper address in classroom design?\",\"answer\":\"Classroom designers must choose among thousands of possible plans while accounting for many environmental and structural variables that influence student learning outcomes.\"},{\"question\":\"How is tradespace exploration (TSE) used in this study?\",\"answer\":\"TSE is applied to model how multiple classroom design parameters affect test performance and cost, enabling evaluation of many design permutations and identification of the best alternatives.\"},{\"question\":\"What modeling approach reduces the number of variables for prediction?\",\"answer\":\"The study builds a predictive model from historical test data and 86 descriptive variables, then uses main effects analysis with a multi-way ANOVA to reduce them to eight composite independent variables.\"}]","Making Sense of Multiple Options for the Design of a Classroom - Abstract | PDF",1792095242]