Elif Akçalı, Jade Williams, Rachel Burress, Albert Aguila, Mariana Buraglia
Although some studies have incorporated poetry into engineering courses, no studies exist that explore the use of writing poetry about technical topics to develop creative thinking skills in undergraduate engineering education. This study explores engineering students’ perceptions of incorporating poetry writing within an upper-level discipline-specific engineering course. Two research questions are considered: (RQ1) Do students think that the poetry assignments will be beneficial to their careers? (RQ2) What beneficial gain, if any, do students report from the poetry assignments? Sixty-one students from an industrial and systems engineering course at the University of Florida completed a four-question, open-ended survey. Data were qualitatively coded and analyzed. For RQ1, 63.3% of participants considered the assignment beneficial to their future engineering careers, 13.3% did not see it as beneficial, and 23.3% were uncertain. For RQ2, 11 code categories and four themes emerged; three themes addressed benefits related to professional skills (creative thinking, problem-solving, communication) and one theme suggested the enhancement of technical skills via deepened conceptual knowledge acquisition. Poetry writing on technical topics has the potential to cultivate creative thinking skills in upper-level discipline-specific courses in undergraduate engineering education. Additional research is warranted. Funding: This work was supported by the University of Florida Creative Campus Program as well as The Cottmeyer Family Innovative Frontiers Faculty Fellowship awarded to E. Akçalı. Supplemental Material: The e-companion is available at https://doi.org/10.1287/ited.2023.0284 .
{"title":"In Their Own Words: Student Perceptions of Technical Poetry Writing in Discipline-Specific Undergraduate Engineering Courses: Opportunities and Challenges","authors":"Elif Akçalı, Jade Williams, Rachel Burress, Albert Aguila, Mariana Buraglia","doi":"10.1287/ited.2023.0284","DOIUrl":"https://doi.org/10.1287/ited.2023.0284","url":null,"abstract":"Although some studies have incorporated poetry into engineering courses, no studies exist that explore the use of writing poetry about technical topics to develop creative thinking skills in undergraduate engineering education. This study explores engineering students’ perceptions of incorporating poetry writing within an upper-level discipline-specific engineering course. Two research questions are considered: (RQ1) Do students think that the poetry assignments will be beneficial to their careers? (RQ2) What beneficial gain, if any, do students report from the poetry assignments? Sixty-one students from an industrial and systems engineering course at the University of Florida completed a four-question, open-ended survey. Data were qualitatively coded and analyzed. For RQ1, 63.3% of participants considered the assignment beneficial to their future engineering careers, 13.3% did not see it as beneficial, and 23.3% were uncertain. For RQ2, 11 code categories and four themes emerged; three themes addressed benefits related to professional skills (creative thinking, problem-solving, communication) and one theme suggested the enhancement of technical skills via deepened conceptual knowledge acquisition. Poetry writing on technical topics has the potential to cultivate creative thinking skills in upper-level discipline-specific courses in undergraduate engineering education. Additional research is warranted. Funding: This work was supported by the University of Florida Creative Campus Program as well as The Cottmeyer Family Innovative Frontiers Faculty Fellowship awarded to E. Akçalı. Supplemental Material: The e-companion is available at https://doi.org/10.1287/ited.2023.0284 .","PeriodicalId":37137,"journal":{"name":"INFORMS Transactions on Education","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43708319","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 : 2023-02-13DOI: 10.1287/ited.2023.0282cs
Timothy C. Y. Chan, Craig Fernandes, Albert Loa, N. Sandholtz
{"title":"Case—Moneyball for Murderball: Using Analytics to Construct Lineups in Wheelchair Rugby","authors":"Timothy C. Y. Chan, Craig Fernandes, Albert Loa, N. Sandholtz","doi":"10.1287/ited.2023.0282cs","DOIUrl":"https://doi.org/10.1287/ited.2023.0282cs","url":null,"abstract":"","PeriodicalId":37137,"journal":{"name":"INFORMS Transactions on Education","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48800455","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 : 2023-02-13DOI: 10.1287/ited.2023.0282ca
Timothy C. Y. Chan, Craig Fernandes, Albert Loa, N. Sandholtz
Motivated by the problem of lineup optimization in wheelchair rugby (WCR), this case study covers descriptive, predictive, and prescriptive analytics. The case is presented from the perspective of a new assistant coach of Canada’s national WCR team, who has been tasked by the head coach to use various analytics techniques to improve their lineups. Whereas the data and actors are fictitious, they are based on real data and discussions with the national team coach and sport scientists. To solve the case, students must conduct data analysis, regression modeling, and optimization modeling. These three steps are tightly linked, as the data analysis is needed to prepare the data for regression, and the regression outputs are used as parameters in the optimization. As such, students build proficiency in developing an end-to-end solution approach for a complex real-world problem. The primary learning objectives for the students are to understand the differences between descriptive, predictive, and prescriptive analytics, to build proficiency in implementing the models using appropriate software, and to identify how these techniques can be applied to solve problems in other sports or other application areas. Supplemental Material: The Teaching Note and data files are available at https://www.informs.org/Publications/Subscribe/Access-Restricted-Materials .
{"title":"Case Article—Moneyball for Murderball: Using Analytics to Construct Lineups in Wheelchair Rugby","authors":"Timothy C. Y. Chan, Craig Fernandes, Albert Loa, N. Sandholtz","doi":"10.1287/ited.2023.0282ca","DOIUrl":"https://doi.org/10.1287/ited.2023.0282ca","url":null,"abstract":"Motivated by the problem of lineup optimization in wheelchair rugby (WCR), this case study covers descriptive, predictive, and prescriptive analytics. The case is presented from the perspective of a new assistant coach of Canada’s national WCR team, who has been tasked by the head coach to use various analytics techniques to improve their lineups. Whereas the data and actors are fictitious, they are based on real data and discussions with the national team coach and sport scientists. To solve the case, students must conduct data analysis, regression modeling, and optimization modeling. These three steps are tightly linked, as the data analysis is needed to prepare the data for regression, and the regression outputs are used as parameters in the optimization. As such, students build proficiency in developing an end-to-end solution approach for a complex real-world problem. The primary learning objectives for the students are to understand the differences between descriptive, predictive, and prescriptive analytics, to build proficiency in implementing the models using appropriate software, and to identify how these techniques can be applied to solve problems in other sports or other application areas. Supplemental Material: 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":"2023-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44571427","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}
Logic puzzles are an effective way to introduce students to advanced solution techniques in operations research, such as Lagrangian relaxation, Dantzig-Wolfe decomposition, and Benders decomposition. The Snake Egg puzzle asks the player to draw a one-cell wide path, or “snake,” in a grid. The remaining cells should form a fixed number of separate, connected, discontiguous regions called “eggs.” We propose two solution approaches: a flow-based model and lazy constraints. Instead of providing the complete model at the outset, we will step through the puzzle in a manner suitable to the classroom, emphasizing the skills that are crucial to successfully implementing advanced techniques. The puzzle functions in particular as a prelude to Benders decomposition. Funding: M. Harris is supported by an Australian Government RTP (research training program) scholarship.
{"title":"The Snake Eggs Puzzle: Preparing Students for Benders Decomposition","authors":"Mitchell K. Harris, M. Forbes","doi":"10.1287/ited.2023.0281","DOIUrl":"https://doi.org/10.1287/ited.2023.0281","url":null,"abstract":"Logic puzzles are an effective way to introduce students to advanced solution techniques in operations research, such as Lagrangian relaxation, Dantzig-Wolfe decomposition, and Benders decomposition. The Snake Egg puzzle asks the player to draw a one-cell wide path, or “snake,” in a grid. The remaining cells should form a fixed number of separate, connected, discontiguous regions called “eggs.” We propose two solution approaches: a flow-based model and lazy constraints. Instead of providing the complete model at the outset, we will step through the puzzle in a manner suitable to the classroom, emphasizing the skills that are crucial to successfully implementing advanced techniques. The puzzle functions in particular as a prelude to Benders decomposition. Funding: M. Harris is supported by an Australian Government RTP (research training program) scholarship.","PeriodicalId":37137,"journal":{"name":"INFORMS Transactions on Education","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48047538","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}
Catherine Cleophas, Christoph Hönnige, Frank Meisel, Philipp Meyer
As the COVID-19 pandemic motivated a shift to virtual teaching, exams have increasingly moved online too. Detecting cheating through collusion is not easy when tech-savvy students take online exams at home and on their own devices. Such online at-home exams may tempt students to collude and share materials and answers. However, online exams’ digital output also enables computer-aided detection of collusion patterns. This paper presents two simple data-driven techniques to analyze exam event logs and essay-form answers. Based on examples from exams in social sciences, we show that such analyses can reveal patterns of student collusion. We suggest using these patterns to quantify the degree of collusion. Finally, we summarize a set of lessons learned about designing and analyzing online exams.
{"title":"Who’s Cheating? Mining Patterns of Collusion from Text and Events in Online Exams","authors":"Catherine Cleophas, Christoph Hönnige, Frank Meisel, Philipp Meyer","doi":"10.1287/ited.2021.0260","DOIUrl":"https://doi.org/10.1287/ited.2021.0260","url":null,"abstract":"As the COVID-19 pandemic motivated a shift to virtual teaching, exams have increasingly moved online too. Detecting cheating through collusion is not easy when tech-savvy students take online exams at home and on their own devices. Such online at-home exams may tempt students to collude and share materials and answers. However, online exams’ digital output also enables computer-aided detection of collusion patterns. This paper presents two simple data-driven techniques to analyze exam event logs and essay-form answers. Based on examples from exams in social sciences, we show that such analyses can reveal patterns of student collusion. We suggest using these patterns to quantify the degree of collusion. Finally, we summarize a set of lessons learned about designing and analyzing online exams.","PeriodicalId":37137,"journal":{"name":"INFORMS Transactions on Education","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136008447","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}
Artificial intelligence (AI) and operations research (OR) have long been intertwined because of their synergistic relationship. Given the increasing popularity of AI and machine learning in particular, we face growing demand for educational offerings in this area from our students. This paper describes two courses that introduce machine learning concepts to undergraduate, predominantly industrial engineering and operations research students. Instead of taking a methods-first approach, these courses use real-world applications to motivate, introduce, and explore these machine learning techniques and highlight meaningful overlap with operations research. Significant hands-on coding experience is used to build student proficiency with the techniques. Student feedback indicates that these courses have greatly increased student interest in machine learning and appreciation of the real-world impact that analytics can have and helped students develop practical skills that they can apply. We believe that similar application-driven courses that connect machine learning and operations research would be valuable additions to undergraduate OR curricula broadly. Supplemental Material: Supplemental material is available at https://doi.org/10.1287/ited.2021.0256 .
{"title":"Introducing and Integrating Machine Learning in an Operations Research Curriculum: An Application-Driven Course","authors":"J. Boutilier, Timothy C. Y. Chan","doi":"10.1287/ited.2021.0256","DOIUrl":"https://doi.org/10.1287/ited.2021.0256","url":null,"abstract":"Artificial intelligence (AI) and operations research (OR) have long been intertwined because of their synergistic relationship. Given the increasing popularity of AI and machine learning in particular, we face growing demand for educational offerings in this area from our students. This paper describes two courses that introduce machine learning concepts to undergraduate, predominantly industrial engineering and operations research students. Instead of taking a methods-first approach, these courses use real-world applications to motivate, introduce, and explore these machine learning techniques and highlight meaningful overlap with operations research. Significant hands-on coding experience is used to build student proficiency with the techniques. Student feedback indicates that these courses have greatly increased student interest in machine learning and appreciation of the real-world impact that analytics can have and helped students develop practical skills that they can apply. We believe that similar application-driven courses that connect machine learning and operations research would be valuable additions to undergraduate OR curricula broadly. Supplemental Material: Supplemental material is available at https://doi.org/10.1287/ited.2021.0256 .","PeriodicalId":37137,"journal":{"name":"INFORMS Transactions on Education","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44350037","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 : 2022-09-19DOI: 10.1287/ited.2022.0273cs
V. Ramani, J. Dalal, Swami Dayakarananda
{"title":"Case—GAP: A Humanitarian Initiative of Ramakrishna Mission for Underprivileged Children","authors":"V. Ramani, J. Dalal, Swami Dayakarananda","doi":"10.1287/ited.2022.0273cs","DOIUrl":"https://doi.org/10.1287/ited.2022.0273cs","url":null,"abstract":"","PeriodicalId":37137,"journal":{"name":"INFORMS Transactions on Education","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48432450","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 : 2022-09-19DOI: 10.1287/ited.2022.0273ca
V. Ramani, J. Dalal, Swami Dayakarananda
Conventional textbook models of profit-maximizing firms are generally unsuitable for understanding and modeling the objectives of a nonprofit organization. Closing this gap is especially important as nonprofits, regarded as the third pillar of the society, are increasingly prevalent along with the government and the for-profit businesses. GAP, a humanitarian project undertaken by Ramakrishna Mission (RKM), a large nonprofit organization in India, has been highlighted in our case. Our case serves three pedagogical objectives: (i) understanding the cost structure that is specific to the GAP project, (ii) applying break-even analysis, and (iii) quantitative modeling of the nonprofit’s decision-making problem using a simple spreadsheet modeling approach. The case has been tested across a diverse set of courses across different MBA programs at two public business schools in India. In all those courses, students found the case challenging but were appreciative of the hands-on experience gained by working on a real-life decision-making problem.
{"title":"Case Article—GAP: A Humanitarian Initiative of Ramakrishna Mission for Underprivileged Children","authors":"V. Ramani, J. Dalal, Swami Dayakarananda","doi":"10.1287/ited.2022.0273ca","DOIUrl":"https://doi.org/10.1287/ited.2022.0273ca","url":null,"abstract":"Conventional textbook models of profit-maximizing firms are generally unsuitable for understanding and modeling the objectives of a nonprofit organization. Closing this gap is especially important as nonprofits, regarded as the third pillar of the society, are increasingly prevalent along with the government and the for-profit businesses. GAP, a humanitarian project undertaken by Ramakrishna Mission (RKM), a large nonprofit organization in India, has been highlighted in our case. Our case serves three pedagogical objectives: (i) understanding the cost structure that is specific to the GAP project, (ii) applying break-even analysis, and (iii) quantitative modeling of the nonprofit’s decision-making problem using a simple spreadsheet modeling approach. The case has been tested across a diverse set of courses across different MBA programs at two public business schools in India. In all those courses, students found the case challenging but were appreciative of the hands-on experience gained by working on a real-life decision-making problem.","PeriodicalId":37137,"journal":{"name":"INFORMS Transactions on Education","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48300062","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}
Test writing is a fundamental component of teaching. With increasing pressure to teach larger groups of students, conduct formal assessment of learning outcomes, and offer online and hybrid classes, there is a need for alternatives to constructed response problem-solving test questions. We believe that appropriate use of multiple-choice (MC) questions can alleviate some of these pressures. However, the results will only be acceptable to dedicated faculty if these questions are well written and effective in measuring student learning. In this article, we propose a structured framework consisting of six design principles that serve as a guide for writing MC items that promote higher-order thinking through the use of scenario-based and multistep problems. Then we demonstrate how to apply these principles to develop high-quality test questions in MC format for introductory analytics courses in statistics or operations research/management science.
{"title":"Practical Guidance for Writing Multiple-Choice Test Questions in Introductory Analytics Courses","authors":"S. Stevens, Susan W. Palocsay, Luis J. Novoa","doi":"10.1287/ited.2022.0274","DOIUrl":"https://doi.org/10.1287/ited.2022.0274","url":null,"abstract":"Test writing is a fundamental component of teaching. With increasing pressure to teach larger groups of students, conduct formal assessment of learning outcomes, and offer online and hybrid classes, there is a need for alternatives to constructed response problem-solving test questions. We believe that appropriate use of multiple-choice (MC) questions can alleviate some of these pressures. However, the results will only be acceptable to dedicated faculty if these questions are well written and effective in measuring student learning. In this article, we propose a structured framework consisting of six design principles that serve as a guide for writing MC items that promote higher-order thinking through the use of scenario-based and multistep problems. Then we demonstrate how to apply these principles to develop high-quality test questions in MC format for introductory analytics courses in statistics or operations research/management science.","PeriodicalId":37137,"journal":{"name":"INFORMS Transactions on Education","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48172783","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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