Pub Date : 2023-06-13DOI: 10.1287/ited.2023.0288ca
M. Drake
This case study provides a comprehensive decision-making scenario that takes students through all three types of analytics—descriptive, predictive, and prescriptive—to provide recommendations to a decision maker. The scenario focuses on an individual investor who is purchasing LEGO sets from retailers with the goal of selling them for a higher price on the aftermarket in a few years once they retire from shelves. Students must create visualizations to generate insights from the data and develop a regression model to identify sets that represent value investment opportunities. In the extension case they must take their estimated values and optimize the decisions of which sets to purchase to meet the decision maker’s investment goals using an integer program. Students also have the opportunity to develop soft skills in problem solving and communicating results and dealing with missing data points in a data set that is larger than standard textbook data sets but is still a manageable size for introductory students. The open-ended instructions make the case appropriate for a wide range of students from the introductory undergraduate level to the advanced graduate level. Supplemental Material: Supplemental materials are available at https://doi.org/10.1287/ited.2023.0288ca . The Teaching Note and data files are available at https://www.informs.org/Publications/Subscribe/Access-Restricted-Materials .
{"title":"Case Article—Creating a Brick Empire Through Data Visualization and Analytics","authors":"M. Drake","doi":"10.1287/ited.2023.0288ca","DOIUrl":"https://doi.org/10.1287/ited.2023.0288ca","url":null,"abstract":"This case study provides a comprehensive decision-making scenario that takes students through all three types of analytics—descriptive, predictive, and prescriptive—to provide recommendations to a decision maker. The scenario focuses on an individual investor who is purchasing LEGO sets from retailers with the goal of selling them for a higher price on the aftermarket in a few years once they retire from shelves. Students must create visualizations to generate insights from the data and develop a regression model to identify sets that represent value investment opportunities. In the extension case they must take their estimated values and optimize the decisions of which sets to purchase to meet the decision maker’s investment goals using an integer program. Students also have the opportunity to develop soft skills in problem solving and communicating results and dealing with missing data points in a data set that is larger than standard textbook data sets but is still a manageable size for introductory students. The open-ended instructions make the case appropriate for a wide range of students from the introductory undergraduate level to the advanced graduate level. Supplemental Material: Supplemental materials are available at https://doi.org/10.1287/ited.2023.0288ca . The Teaching Note and data files are available at https://www.informs.org/Publications/Subscribe/Access-Restricted-Materials .","PeriodicalId":37137,"journal":{"name":"INFORMS Transactions on Education","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43752764","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-13DOI: 10.1287/ited.2023.0288csa
M. Drake
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Pub Date : 2023-06-13DOI: 10.1287/ited.2023.0288csb
Matthew J. Drake
Open AccessOpen Access licenseAboutSectionsView PDF ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinked InEmail Go to SectionOpen AccessOpen Access license HomeINFORMS Transactions on EducationAhead of Print Case—Creating a Brick Empire Through Data Visualization and Analytics (B)Matthew J. Drake Matthew J. Drake Published Online:13 Jun 2023https://doi.org/10.1287/ited.2023.0288csbGreg McCullough has conducted a thorough analysis of the more than 600 LEGO sets released in 2018 and 2019 to gain a better understanding of the characteristics of the different themes and subthemes. His overall goal is to identify the sets in which he should invest. After the sets retire, he expects to use the proceeds from selling the sets to supplement his family’s collecting passion.Although the future value of a retired LEGO set is partially dependent on the desirability of the set itself and the theme (such as Harry Potter, Minecraft, Star Wars, etc.), another major determinant of the desirability of a set as an investment is the value potential, which is defined as the difference between the price that LEGO “should” be charging for the set based on its characteristics and the actual retail price. Sets with large value potential represent outsized investment opportunities in much the same way that a value mutual fund invests in securities that are potentially undervalued based on their fundamentals.In his prior analysis, Greg developed a model that determines the price that LEGO should be charging for sets and has used it to determine the value potential for all of the sets that were released in 2019. Some sets ending up having positive value potentials, whereas others had negative value potentials. He eliminated all the sets with negative value potential from further investment consideration. He also researched the resale prices for retired LEGO sets on the secondary market and narrowed his potential investment options to sets in the following themes: City, Creator, DC Super Heroes, Friends, Harry Potter, Hidden Side, Ideas, Marvel Super Heroes, Minecraft, Ninjago, Overwatch, Speed Champions, and Star Wars. This left him with the 109 sets listed in the data file provided.Greg’s task now is to determine which specific sets he should purchase as an investment. He has initially allocated $4,000 to his investment budget, although he is open to adjusting that amount up or down within the range from $2,000 to $6,000 based on the relationship between value potential and total investment.Like any well-constructed investment portfolio, Greg also wants to ensure that he is properly diversified to limit his exposure to adverse market conditions affecting one particular set or theme in the future. As a result, he had decided not to purchase more than 10 copies of any one set, and he seeks to avoid any one theme representing more than 20% of the total number of LEGO sets that he has purchased.Based on his analysis of sets selling on the s
{"title":"Case—Creating a Brick Empire Through Data Visualization and Analytics (B)","authors":"Matthew J. Drake","doi":"10.1287/ited.2023.0288csb","DOIUrl":"https://doi.org/10.1287/ited.2023.0288csb","url":null,"abstract":"Open AccessOpen Access licenseAboutSectionsView PDF ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinked InEmail Go to SectionOpen AccessOpen Access license HomeINFORMS Transactions on EducationAhead of Print Case—Creating a Brick Empire Through Data Visualization and Analytics (B)Matthew J. Drake Matthew J. Drake Published Online:13 Jun 2023https://doi.org/10.1287/ited.2023.0288csbGreg McCullough has conducted a thorough analysis of the more than 600 LEGO sets released in 2018 and 2019 to gain a better understanding of the characteristics of the different themes and subthemes. His overall goal is to identify the sets in which he should invest. After the sets retire, he expects to use the proceeds from selling the sets to supplement his family’s collecting passion.Although the future value of a retired LEGO set is partially dependent on the desirability of the set itself and the theme (such as Harry Potter, Minecraft, Star Wars, etc.), another major determinant of the desirability of a set as an investment is the value potential, which is defined as the difference between the price that LEGO “should” be charging for the set based on its characteristics and the actual retail price. Sets with large value potential represent outsized investment opportunities in much the same way that a value mutual fund invests in securities that are potentially undervalued based on their fundamentals.In his prior analysis, Greg developed a model that determines the price that LEGO should be charging for sets and has used it to determine the value potential for all of the sets that were released in 2019. Some sets ending up having positive value potentials, whereas others had negative value potentials. He eliminated all the sets with negative value potential from further investment consideration. He also researched the resale prices for retired LEGO sets on the secondary market and narrowed his potential investment options to sets in the following themes: City, Creator, DC Super Heroes, Friends, Harry Potter, Hidden Side, Ideas, Marvel Super Heroes, Minecraft, Ninjago, Overwatch, Speed Champions, and Star Wars. This left him with the 109 sets listed in the data file provided.Greg’s task now is to determine which specific sets he should purchase as an investment. He has initially allocated $4,000 to his investment budget, although he is open to adjusting that amount up or down within the range from $2,000 to $6,000 based on the relationship between value potential and total investment.Like any well-constructed investment portfolio, Greg also wants to ensure that he is properly diversified to limit his exposure to adverse market conditions affecting one particular set or theme in the future. As a result, he had decided not to purchase more than 10 copies of any one set, and he seeks to avoid any one theme representing more than 20% of the total number of LEGO sets that he has purchased.Based on his analysis of sets selling on the s","PeriodicalId":37137,"journal":{"name":"INFORMS Transactions on Education","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136106154","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Intensive competition among supply chains often forces trading partners to collaborate despite their conflict of interests. Supply chain contracts and collaboration theory is well established in the academic literature to align the interests but much less conveyed to students and industry professionals for a practical impact. Although the Beer Game captures the bullwhip effect and the value of information sharing, it ignores the conflict of interests, that is, price and quantity bargaining, among the trading partners. We describe a new online teaching game, the FloraPark simulation (“the flower game” at https://flower.gamespots.net/ ), based on real-life events in the international fresh-cut flower supply chains, for students to learn supply chain collaboration via contracts in a setting of multiple supply chains competing in the same market. Students play trading partners in the flower supply chains and experiment with the push, pull, and advanced purchasing discount contracts by negotiating wholesale prices and quantities to achieve the conflicting objectives of (1) collaboration to beat other supply chains, and (2) bargaining to protect their own interests from their trading partners. Supplemental Material: The e-companion is available at https://doi.org/10.1287/ited.2022.0035 .
{"title":"FloraPark (the Flower Game): A Supply Chain Contract and Collaboration Simulation","authors":"Yao Zhao, Arim Park, Olena Rudna, J. Song","doi":"10.1287/ited.2022.0035","DOIUrl":"https://doi.org/10.1287/ited.2022.0035","url":null,"abstract":"Intensive competition among supply chains often forces trading partners to collaborate despite their conflict of interests. Supply chain contracts and collaboration theory is well established in the academic literature to align the interests but much less conveyed to students and industry professionals for a practical impact. Although the Beer Game captures the bullwhip effect and the value of information sharing, it ignores the conflict of interests, that is, price and quantity bargaining, among the trading partners. We describe a new online teaching game, the FloraPark simulation (“the flower game” at https://flower.gamespots.net/ ), based on real-life events in the international fresh-cut flower supply chains, for students to learn supply chain collaboration via contracts in a setting of multiple supply chains competing in the same market. Students play trading partners in the flower supply chains and experiment with the push, pull, and advanced purchasing discount contracts by negotiating wholesale prices and quantities to achieve the conflicting objectives of (1) collaboration to beat other supply chains, and (2) bargaining to protect their own interests from their trading partners. Supplemental Material: The e-companion is available at https://doi.org/10.1287/ited.2022.0035 .","PeriodicalId":37137,"journal":{"name":"INFORMS Transactions on Education","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49251915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Scholarly interests in developing personalized learning analytics dashboards (LADs) in universities have been increasing. LADs are data visualization tools for both teachers and learners that allow them to support student success and improve teaching and learning. In most LADs, however, a teacher-centric, institutional view drives their designs, treating students only as passive end-users, which results in LADs being less useful to students. To address this limitation, we used a card-sorting technique and asked 42 students at a university in Northern Ireland to construct dashboards that reflect their priorities. Using a situated theory of learning as a lens and with the help of multiple qualitative methods, we collected data on what constitutes useful dashboards. Findings suggest that situated learning data sets, such as information on how students learn by talking and listening to others in their communities, need to be integrated into LADs. Students preferred to see the inclusion of qualitative narratives, self-directed learning data and financial information (money spent versus resources utilized) in LADs. As well as raising new questions on how such LADs could be designed, this study challenges institutional overreliance on measurable digital footprints as proxies for academic success. We call for recognizing the wider social learning that happens in landscapes of practice so that LADs become more useful to students.
{"title":"Which Data Sets Are Preferred by University Students in Learning Analytics Dashboards? A Situated Learning Theory Perspective","authors":"Paul Joseph-Richard, J. Uhomoibhi","doi":"10.1287/ited.2023.0289","DOIUrl":"https://doi.org/10.1287/ited.2023.0289","url":null,"abstract":"Scholarly interests in developing personalized learning analytics dashboards (LADs) in universities have been increasing. LADs are data visualization tools for both teachers and learners that allow them to support student success and improve teaching and learning. In most LADs, however, a teacher-centric, institutional view drives their designs, treating students only as passive end-users, which results in LADs being less useful to students. To address this limitation, we used a card-sorting technique and asked 42 students at a university in Northern Ireland to construct dashboards that reflect their priorities. Using a situated theory of learning as a lens and with the help of multiple qualitative methods, we collected data on what constitutes useful dashboards. Findings suggest that situated learning data sets, such as information on how students learn by talking and listening to others in their communities, need to be integrated into LADs. Students preferred to see the inclusion of qualitative narratives, self-directed learning data and financial information (money spent versus resources utilized) in LADs. As well as raising new questions on how such LADs could be designed, this study challenges institutional overreliance on measurable digital footprints as proxies for academic success. We call for recognizing the wider social learning that happens in landscapes of practice so that LADs become more useful to students.","PeriodicalId":37137,"journal":{"name":"INFORMS Transactions on Education","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44593550","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Managers are increasingly being tasked with overseeing data-driven projects that incorporate prescriptive and predictive models. Furthermore, basic knowledge of the data analytics pipeline is a fundamental requirement in many modern organizations. Given the central importance of analytics in today’s business environment, there is a growing demand for educational pedagogies that give students the opportunity to learn the fundamentals while also familiarizing them with how such tools are applied. However, a tension exists between the introduction of real-world problems that students can analyze and extract insight from and the need for prerequisite knowledge of mathematical concepts and programming languages such as Python/R. As a consequence, this paper describes an application-focused course that uses Microsoft Excel and mathematical programming to introduce MBA students with nontechnical backgrounds to tools from both prescriptive and predictive analytics. While students’ gain proficiency in managing data and creating optimization and machine learning models, they are also exposed to broader business concepts. Teaching evaluations indicate that the course has helped students further develop their practical skills in Microsoft Excel, gain an appreciation of the real-world impact of data analytics, and has introduced them to a discipline they originally believed was best suited for more technically focused professionals.
{"title":"Introducing Prescriptive and Predictive Analytics to MBA Students with Microsoft Excel","authors":"Adam Diamant","doi":"10.1287/ited.2023.0286","DOIUrl":"https://doi.org/10.1287/ited.2023.0286","url":null,"abstract":"Managers are increasingly being tasked with overseeing data-driven projects that incorporate prescriptive and predictive models. Furthermore, basic knowledge of the data analytics pipeline is a fundamental requirement in many modern organizations. Given the central importance of analytics in today’s business environment, there is a growing demand for educational pedagogies that give students the opportunity to learn the fundamentals while also familiarizing them with how such tools are applied. However, a tension exists between the introduction of real-world problems that students can analyze and extract insight from and the need for prerequisite knowledge of mathematical concepts and programming languages such as Python/R. As a consequence, this paper describes an application-focused course that uses Microsoft Excel and mathematical programming to introduce MBA students with nontechnical backgrounds to tools from both prescriptive and predictive analytics. While students’ gain proficiency in managing data and creating optimization and machine learning models, they are also exposed to broader business concepts. Teaching evaluations indicate that the course has helped students further develop their practical skills in Microsoft Excel, gain an appreciation of the real-world impact of data analytics, and has introduced them to a discipline they originally believed was best suited for more technically focused professionals.","PeriodicalId":37137,"journal":{"name":"INFORMS Transactions on Education","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46036007","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-01DOI: 10.1287/ited.2023.intro.v23.n3
Michael F. Gorman, Jeroen Beliën
History: This paper has been accepted for the INFORMS Transactions on Education Special Section on Cases Based on Real-World Projects from the INFORMS Journal on Applied Analytics.
历史:这篇论文已经被INFORMS应用分析期刊上基于现实世界项目的案例的教育专题部分所接受。
{"title":"Introduction to the ITED Special Section <i>Cases Based on Real-World Projects from the INFORMS Journal on Applied Analytics</i>","authors":"Michael F. Gorman, Jeroen Beliën","doi":"10.1287/ited.2023.intro.v23.n3","DOIUrl":"https://doi.org/10.1287/ited.2023.intro.v23.n3","url":null,"abstract":"History: This paper has been accepted for the INFORMS Transactions on Education Special Section on Cases Based on Real-World Projects from the INFORMS Journal on Applied Analytics.","PeriodicalId":37137,"journal":{"name":"INFORMS Transactions on Education","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135345151","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Industrial-scale models require considerable setup time; hence, once built, they are used in myriad ways to consider closely related cases. In practice, the code for these models frequently evolves without appropriate notational choices, largely as a result of the lengthy development time of, and the number of individuals contributing to, their formulation. This leads to inefficiencies and obfuscates model structures that might be leveraged to expedite solutions. In this paper, we advocate for an emerging literature on model formulation “best practices” and present the reformulation of a widely used industrial-scale linear program. The efficient mathematical expression of this linear program, used to plan capacity expansion in the energy sector, allows for greater transparency of model structures and enhanced ability to identify computational performance improvements, as well as a lucid interpretation of its solutions. This type of formulation is employed in several mathematical programming courses at our university as an example of the advantages of best practices; the model more broadly is used widely to inform policy in the U.S. energy sector. Funding: This work was supported by the National Renewable Energy Laboratory (Laboratory Directed Research and Development program).
{"title":"Improving Mathematical Exposition of an Industrial-Scale Linear Program","authors":"Gus Greivel, A. Newman, Maxwell Brown, K. Eurek","doi":"10.1287/ited.2023.0283","DOIUrl":"https://doi.org/10.1287/ited.2023.0283","url":null,"abstract":"Industrial-scale models require considerable setup time; hence, once built, they are used in myriad ways to consider closely related cases. In practice, the code for these models frequently evolves without appropriate notational choices, largely as a result of the lengthy development time of, and the number of individuals contributing to, their formulation. This leads to inefficiencies and obfuscates model structures that might be leveraged to expedite solutions. In this paper, we advocate for an emerging literature on model formulation “best practices” and present the reformulation of a widely used industrial-scale linear program. The efficient mathematical expression of this linear program, used to plan capacity expansion in the energy sector, allows for greater transparency of model structures and enhanced ability to identify computational performance improvements, as well as a lucid interpretation of its solutions. This type of formulation is employed in several mathematical programming courses at our university as an example of the advantages of best practices; the model more broadly is used widely to inform policy in the U.S. energy sector. Funding: This work was supported by the National Renewable Energy Laboratory (Laboratory Directed Research and Development program).","PeriodicalId":37137,"journal":{"name":"INFORMS Transactions on Education","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43223363","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
L. LeBlanc, Thomas A. Grossman, Michael R. Bartolacci
The COVID-19 pandemic has forced the rapid adoption of remote teaching modalities including “hyflex” where students attend some class sessions in person and some online. Managing the hyflex course requires faculty to quickly generate several reports and to update these reports rapidly when the authorities adjust the rules, students add/drop, or the number of course sessions is changed. The creation of these reports is tedious and error-prone, so they need to be automated. However, the nature of the task precludes traditional Excel programming approaches. We use Excel’s new “dynamic array” capabilities (which are available only in Excel 365) to automate the creation and updating of the reports needed to manage the hyflex course. We show how to program the reports, and we discuss the importance of taking an iterative approach to creating effective, error-free cell formulas. To help the reader acquire genuine access to the dynamic array functions, we provide a practical tutorial on the principles and new concepts of dynamic arrays, explain how they relate to legacy array functions, and present selected dynamic array functions including SEQUENCE, FILTER, and XLOOKUP.
{"title":"Managing the Hyflex Scheduling Activity Using Excel Dynamic Arrays","authors":"L. LeBlanc, Thomas A. Grossman, Michael R. Bartolacci","doi":"10.1287/ited.2023.0287","DOIUrl":"https://doi.org/10.1287/ited.2023.0287","url":null,"abstract":"The COVID-19 pandemic has forced the rapid adoption of remote teaching modalities including “hyflex” where students attend some class sessions in person and some online. Managing the hyflex course requires faculty to quickly generate several reports and to update these reports rapidly when the authorities adjust the rules, students add/drop, or the number of course sessions is changed. The creation of these reports is tedious and error-prone, so they need to be automated. However, the nature of the task precludes traditional Excel programming approaches. We use Excel’s new “dynamic array” capabilities (which are available only in Excel 365) to automate the creation and updating of the reports needed to manage the hyflex course. We show how to program the reports, and we discuss the importance of taking an iterative approach to creating effective, error-free cell formulas. To help the reader acquire genuine access to the dynamic array functions, we provide a practical tutorial on the principles and new concepts of dynamic arrays, explain how they relate to legacy array functions, and present selected dynamic array functions including SEQUENCE, FILTER, and XLOOKUP.","PeriodicalId":37137,"journal":{"name":"INFORMS Transactions on Education","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44720635","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Modeling exercises are designed around the popular game Wordle. These exercises can possibly be used in a computational or modeling laboratory course or in a course on modeling operations research (OR) problems. They assume some familiarity with modeling integer programs, a programming language like Python for basic text processing, and optimization software like AMPL or PYOMO. These exercises were tried in a master’s-level course on modeling OR problems. Two sessions of three hours each are ideal for the whole exercise.
{"title":"An OR Approach for WORdle","authors":"Simran Lakhani, Mustafa Vora, Ashutosh Mahajan","doi":"10.1287/ited.2023.0285","DOIUrl":"https://doi.org/10.1287/ited.2023.0285","url":null,"abstract":"Modeling exercises are designed around the popular game Wordle. These exercises can possibly be used in a computational or modeling laboratory course or in a course on modeling operations research (OR) problems. They assume some familiarity with modeling integer programs, a programming language like Python for basic text processing, and optimization software like AMPL or PYOMO. These exercises were tried in a master’s-level course on modeling OR problems. Two sessions of three hours each are ideal for the whole exercise.","PeriodicalId":37137,"journal":{"name":"INFORMS Transactions on Education","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41601927","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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