G. Colajanni, A. Gobbi, Marinella Picchi, Alice Raffaele, E. Taranto
We introduce Ricerca Operativa Applicazioni Reali (ROAR; in English, Real Applications of Operations Research), a three-year project for higher secondary schools. Its main aim is to improve students’ interest, motivation, and skills related to Science, Technology, Engineering, and Mathematics disciplines by integrating mathematics and computer science through operations research. ROAR offers examples and problems closely connected with students’ everyday life or with the industrial reality, balancing mathematical modeling and algorithmics. The project is composed of three teaching units, addressed to grades 10, 11, and 12. The implementation of the first teaching unit took place in Spring 2021 at the scientific high school IIS Antonietti in Iseo (Brescia, Italy). In particular, in this paper, we provide a full description of this first teaching unit in terms of objectives, prerequisites, topics and methods, organization of the lectures, and digital technologies used. Moreover, we analyze the feedback received from students and teachers involved in the experimentation, and we discuss advantages and disadvantages related to distance learning that we had to adopt because of the COVID-19 pandemic.
{"title":"An Operations Research–Based Teaching Unit for Grade 10: The ROAR Experience, Part I","authors":"G. Colajanni, A. Gobbi, Marinella Picchi, Alice Raffaele, E. Taranto","doi":"10.1287/ited.2022.0271","DOIUrl":"https://doi.org/10.1287/ited.2022.0271","url":null,"abstract":"We introduce Ricerca Operativa Applicazioni Reali (ROAR; in English, Real Applications of Operations Research), a three-year project for higher secondary schools. Its main aim is to improve students’ interest, motivation, and skills related to Science, Technology, Engineering, and Mathematics disciplines by integrating mathematics and computer science through operations research. ROAR offers examples and problems closely connected with students’ everyday life or with the industrial reality, balancing mathematical modeling and algorithmics. The project is composed of three teaching units, addressed to grades 10, 11, and 12. The implementation of the first teaching unit took place in Spring 2021 at the scientific high school IIS Antonietti in Iseo (Brescia, Italy). In particular, in this paper, we provide a full description of this first teaching unit in terms of objectives, prerequisites, topics and methods, organization of the lectures, and digital technologies used. Moreover, we analyze the feedback received from students and teachers involved in the experimentation, and we discuss advantages and disadvantages related to distance learning that we had to adopt because of the COVID-19 pandemic.","PeriodicalId":37137,"journal":{"name":"INFORMS Transactions on Education","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46922814","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 : 2022-03-11DOI: 10.1287/ited.2021.0266ca
Steven M. Shechter
This article describes an in-class role-playing exercise, as well as a case study, on the application of mixed integer programming to help a hospital with physician scheduling. The intended audiences are graduate students or advanced undergraduate students taking a first course in optimization who have been introduced to integer programming. The role-playing exercise aims to develop students’ skills in the iterative process of listening to decision makers describe their problem, asking them questions, and developing initial formulations of the problem. The case study provides students the opportunity to spend more time developing a full mathematical formulation, solving it, and writing up their findings. The case assumes students have already been introduced to the “Big-M” method but assumes no prior introduction to the concepts of hard versus soft constraints. There is no natural objective in this problem, such as the usual “maximize profit” or “minimize cost”; instead, students are introduced to the topic of Goal Programming, which also introduces them to the concept of multiobjective optimization.
{"title":"Case Article—Pediatrician Scheduling at British Columbia Women’s Hospital","authors":"Steven M. Shechter","doi":"10.1287/ited.2021.0266ca","DOIUrl":"https://doi.org/10.1287/ited.2021.0266ca","url":null,"abstract":"This article describes an in-class role-playing exercise, as well as a case study, on the application of mixed integer programming to help a hospital with physician scheduling. The intended audiences are graduate students or advanced undergraduate students taking a first course in optimization who have been introduced to integer programming. The role-playing exercise aims to develop students’ skills in the iterative process of listening to decision makers describe their problem, asking them questions, and developing initial formulations of the problem. The case study provides students the opportunity to spend more time developing a full mathematical formulation, solving it, and writing up their findings. The case assumes students have already been introduced to the “Big-M” method but assumes no prior introduction to the concepts of hard versus soft constraints. There is no natural objective in this problem, such as the usual “maximize profit” or “minimize cost”; instead, students are introduced to the topic of Goal Programming, which also introduces them to the concept of multiobjective optimization.","PeriodicalId":37137,"journal":{"name":"INFORMS Transactions on Education","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42003368","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 : 2022-03-11DOI: 10.1287/ited.2021.0266cs
Steven M. Shechter
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Pub Date : 2022-01-13DOI: 10.1287/ited.2021.0257ca
Arnd Huchzermeier, Jannik Wolters, M. Uphues
In this case study, students combine data-based insights with strategic considerations to make fundamental business decisions at the German grocery retail chain Real. In response to dwindling numbers of customers and reduced revenues, Real developed the RealPro customer benefits program to achieve a quick turnaround. For a fixed annual fee, RealPro members receive substantial and permanent discounts of 20% on nonpromoted items from a broad range of food categories. Students employ data analytics methods to extract insights from the provided data set, which contains point-of-sale information from the actual market test of RealPro. Based on these insights, decisions concerning the rollout and design of the RealPro program must be made. We provide data analysis solutions in both Excel and R to analyze 75 thousand customer transactions. In the case extension, students can apply the difference-in-differences method and two covariate balancing algorithms for in-depth statistical analyses. For this purpose, we provide an additional unbalanced data set with 83 thousand transactions, on which the students can test and analyze propensity score matching and entropy balancing models.
{"title":"Case Article—The RealPro Customer Benefits Program: Rekindling Shopper Loyalty Through a Subscription Service","authors":"Arnd Huchzermeier, Jannik Wolters, M. Uphues","doi":"10.1287/ited.2021.0257ca","DOIUrl":"https://doi.org/10.1287/ited.2021.0257ca","url":null,"abstract":"In this case study, students combine data-based insights with strategic considerations to make fundamental business decisions at the German grocery retail chain Real. In response to dwindling numbers of customers and reduced revenues, Real developed the RealPro customer benefits program to achieve a quick turnaround. For a fixed annual fee, RealPro members receive substantial and permanent discounts of 20% on nonpromoted items from a broad range of food categories. Students employ data analytics methods to extract insights from the provided data set, which contains point-of-sale information from the actual market test of RealPro. Based on these insights, decisions concerning the rollout and design of the RealPro program must be made. We provide data analysis solutions in both Excel and R to analyze 75 thousand customer transactions. In the case extension, students can apply the difference-in-differences method and two covariate balancing algorithms for in-depth statistical analyses. For this purpose, we provide an additional unbalanced data set with 83 thousand transactions, on which the students can test and analyze propensity score matching and entropy balancing models.","PeriodicalId":37137,"journal":{"name":"INFORMS Transactions on Education","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41836678","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}
{"title":"Introduction to the Special Issue: The Education Science of Delivering Analytics Education","authors":"J. Belien","doi":"10.1287/ited.2021.0264","DOIUrl":"https://doi.org/10.1287/ited.2021.0264","url":null,"abstract":"","PeriodicalId":37137,"journal":{"name":"INFORMS Transactions on Education","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47061850","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 : 2021-12-22DOI: 10.1287/ited.2021.0258ca
M. Gorman
Louisiana Branch Lines is a struggling Southeast U.S. railroad in just four cities and 12 markets. Their marketing, operations, and finance performance is poor and their departments disjointed. In this customizable, nine-part case, instructors can choose to focus on basic problem structuring and descriptive and predictive statistics, optimization model building, simulation of solutions, or the integration of all of the above. It is based on a real-world case.
{"title":"Case Article—Louisiana Branch Lines","authors":"M. Gorman","doi":"10.1287/ited.2021.0258ca","DOIUrl":"https://doi.org/10.1287/ited.2021.0258ca","url":null,"abstract":"Louisiana Branch Lines is a struggling Southeast U.S. railroad in just four cities and 12 markets. Their marketing, operations, and finance performance is poor and their departments disjointed. In this customizable, nine-part case, instructors can choose to focus on basic problem structuring and descriptive and predictive statistics, optimization model building, simulation of solutions, or the integration of all of the above. It is based on a real-world case.","PeriodicalId":37137,"journal":{"name":"INFORMS Transactions on Education","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49205809","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 : 2021-11-03DOI: 10.1287/ited.2021.0262ca
Jeffrey S. Stonebraker
The interactive case study requires student teams to engage with the instructor using a structured decision analysis process in deciding whether to develop a new drug to treat blood clots in legs. There is role-playing in the interactive case study where student teams are decision consultants and the instructor serves as the decision maker, subject matter expert (SME), and coach. Student teams are responsible for managing the analytical process, framing the decision, collecting data from the SME (instructor), constructing the Excel model, assessing probabilities for the most-sensitive uncertainties from the SME, evaluating the Excel-based decision-tree model, and presenting evaluation results and recommendations to the decision maker (instructor). The goal of the case is to improve the analytical, modeling, and consulting skills of the students. The interactive case study is the culmination of a semester-long elective MBA course, entitled Decision Making Under Uncertainty. Since 2010, I have taught this course 31 times to 870 graduate students.
互动式案例研究要求学生团队使用结构化决策分析过程与教师互动，以决定是否开发一种治疗腿部血栓的新药。在互动式案例研究中有角色扮演，学生团队是决策顾问，导师充当决策者、主题专家(SME)和教练。学生团队负责管理分析过程，制定决策，从中小企业(指导教师)收集数据，构建Excel模型，评估中小企业最敏感的不确定性的概率，评估基于Excel的决策树模型，并向决策者(指导教师)提交评估结果和建议。本案例的目标是提高学生的分析、建模和咨询技能。这一互动案例研究是一门名为“不确定性下的决策”(Decision Making Under Uncertainty)的MBA选修课程的高潮。从2010年至今，我已经为870名研究生教授了31次这门课程。
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