Decision Sciences-Journal of Innovative Education最新文献

COVID-19 pandemic policies requiring disease testing provide a rich context to build insights on true positives versus false positives. Our main contribution to the pedagogy of data analytics and statistics is to propose a method for teaching updating of probabilities using Bayes’ rule reasoning to build understanding that true positives and false positives depend on the prior probability. Our instructional approach has three parts. First, we show how to construct and interpret raw frequency data tables, instead of using probabilities. Second, we use dynamic visual displays to develop insights and help overcome calculation avoidance or errors. Third, we look at graphs of positive predictive values and negative predictive values for different priors. The learning activities we use include lectures, in-class discussions and exercises, breakout group problem solving sessions, and homework. Our research offers teaching methods to help students understand that the veracity of test results depends on the prior probability as well as helps students develop fundamental skills in understanding probabilistic uncertainty alongside higher-level analytical and evaluative skills. Beyond learning to update the probability of having the disease given a positive test result, our material covers naïve estimates of the positive predictive value, the common mistake of ignoring the disease's base rate, debating the relative harm from a false positive versus a false negative, and creating a new disease test.

This article examines how students learn about data-driven decision-making by creating and using a dashboard to play an online version of the familiar Beer Game. The objective is to apply data visualization skills to a business system in a way that leads to effective decisions. The students not only build a dashboard in Tableau, they also use it as they make ordering decisions while playing a round of the Beer Game that has a seasonal ramp up/ramp down demand pattern. Our assessment indicates that the exercise provides an effective application of Tableau skills and raises awareness of important aspects of dashboard design. We continue to improve the exercise to emphasize that analytics solutions can only be developed with a solid understanding of the business system.

Purpose: With the advancement of abdominal wall reconstruction, more complex hernia patients are undergoing repairs that may require a postoperative surgical intensive care unit (SICU) admission. The volume ratio (VR) of the hernia sac to the abdominal cavity is an easily applied method to quantify disease severity and the ensuing physiologic insult. This study aimed to predict postoperative SICU admission using VR and other preoperative variables.

Methods: A single-center retrospective review was conducted for patients undergoing large abdominal hernias (width ≥ 18 cm) repaired from September 2014 to October 2019. Patient demographics, comorbidities, abdominal surgical history, and VR were analyzed through univariate and multivariable methods to identify predictors of SICU admission within the first two postoperative days. A predictive model was generated and validated.

Results: Of 434 patients meeting inclusion criteria, 127(29%) required a SICU admission within the first two postoperative days. VR was significantly higher in SICU patients (Median 30.6% [IQR 14.4-59.0] vs. 10.6% [IQR 4.35-23.6], P < 0.001). Male sex, history of chronic obstructive pulmonary disease, prior component separation, recurrent incisional hernia, hernia grade 3, and VR showed higher odds of SICU admission. When validated on a testing dataset, these variables showed strong SICU admission predictions, with an area under the curve, sensitivity, and specificity of 0.82, 81.7% and 68.5%, respectively.

Conclusions: The volume ratio in combination with preoperatively available variables can reliably predict postoperative SICU admission following abdominal wall reconstruction. Anticipating such events preoperatively allows for bed space allocation as well as optimizing postoperative care.

Practitioner surveys suggest that despite well-intentioned efforts, undergraduate business programs could better equip students with “soft skills.” This research study focuses on the soft skills associated with cross-functional integration (CFI), where skill gaps are believed to exist but have not been confirmed. As the first study to specifically characterize and measure CFI skills, we argue that even in the best-case scenario, a small CFI-skills gap could persist, and that the primary goal of business programs is to minimize, not eliminate, the gap. We assert that an instrument that measures CFI skills on three dimensions (cross-functional collaboration, cross-functional coordination, and cross-functional communication) provides a critical starting point in the identification and management of the CFI skills gap. We adapt and validate such an instrument, test it with a sample of 160 business students and 160 hiring managers, and find statistically significant gaps at the construct and dimensional level. However, the magnitude of the gaps is not large, suggesting that business schools may be doing a good job of managing the CFI skills gap. Our assessment instrument is a valuable tool for companies that wish to diagnose and address CFI skills challenges.

Effective disaster response requires time-critical decisions to get personnel and supplies to the right places as quickly as possible. Such operations are complicated by the need for coordination among multiple stakeholders. In this teaching brief, we describe a serious online game for humanitarian logistics courses called the “Disaster Response Game.” The game provides students with context, challenges, and command seat experience with simulated life-and-death consequences. Our development effort includes the creation of a flexible digital platform for delivering game-style simulations for undergraduate and graduate education as well as response training within large enterprises. The system has instructional design interfaces for creating a wide range of disaster scenarios including, but not limited to, earthquakes, floods, pandemics, storms, and wildfires. As proof of concept, we built a tropical cyclone scenario and tested the corresponding multiplayer Disaster Response Game with students and subject matter experts. Students found it valuable to be assigned different roles that required collaboration, found the experience to be realistic, and were motivated to minimize casualties as best as they could with available resources. Subject matter experts also found the game to be sound in its instructional design. We seek a community of interested instructors to help develop more scenarios.

Multirole online games offer advantages for learning in business schools, as students process information and coordinate with others while pursuing measurable goals. Gaming environments can be complex, and the choices and timing of players’ actions may have long-term effects on the state of the game. Team members practice communication skills as they exchange information and coordinate actions, and games provide objective feedback about their performance. Despite these advantages, integration of multiplayer online games into business courses can present technical and instructional challenges. This article introduces an online game, CyberStrike, in which student teams play roles of state or nonstate actors attempting to protect their own information systems while selectively attacking competitors’ information systems. The game can be useful in organizational behavior courses because it engages students in decision-making processes and inter-group dynamics that highlight relevant principles in action. As student teams try to foster cooperation within a competitive environment, consequences of their decision-making, strategy development, and boundary-spanning activities become apparent. Guidelines for teaching with CyberStrike are provided, along with suggestions for incorporating multirole online games into business school classes.

Studies show that learning is situated—or that learning in one context does not easily transfer to a new context. Because business simulations are often used to provide a learning context, we wondered if this context-specific learning would transfer. To explore this issue, we used situated learning theory to ask undergraduate students in an operations management class to apply their learning in both familiar, simulation contexts, and unfamiliar, nonsimulation contexts. Using contextually based exam questions, we empirically measured learner performance on low and high cognitive effort questions. We were able to provide some support for the constructivist learning theory's hypothesis that learners can take the principles constructed in a business simulation and apply them in other contexts. Additionally, we explored the implications of confidence/self-efficacy theory and demonstrated that transfer may differ based on cognitive effort.