Decision Sciences-Journal of Innovative Education最新文献

Facility placement is of strategic importance to most organizations as a well-placed distribution center minimizes delivery costs and reduces fulfillment lead times, thus improving customer service levels. Because organizations value the location planning process, this teaching brief offers an exercise that analyzes the planning process using the center-of-gravity algorithm, a service area map, and real-world constraints. The objective of the exercise is to identify two locations within a service area that minimize total network distribution costs. Our exercise is intended to complement standard course content and support instructors developing curricula for undergraduate operations management and supply chain management courses. Student-based survey results indicate that the assignment enhanced classroom engagement and helped students better understand the complexities of location planning.

This article details an art assignment given to undergraduate management students in an introductory supply chain management course. Students were asked to choose a supply chain ethics issue, create a work of art that responded to the issue, then write an artist's statement that discussed the thought process and choices made in creating their artwork. The majority of students submitted art that was creative, relevant to supply chain ethics, and well executed. Survey results reveal that students were in agreement that the assignment was more enjoyable than a comparable written assignment. In addition, students’ understanding of ethical issues in supply chain management increased through both the creation of their own art and interactions with the art of their peers. This novel approach to teaching ethics in supply chain management addresses shortcomings in current approaches to business education and helps student build a strong foundation for ethical decision-making in their future careers.

The advent of the COVID-19 pandemic accelerated the need to conduct synchronous online instruction in which students and faculty were distributed geographically but aggregated digitally onto a single screen on a computer. This approach will likely persist into the future. Thus, a better understanding of how engagement approaches can be adapted to the synchronous online teaching environment is critical for future success. This research presents an experiment-based investigation into the effectiveness of two often-debated engagement approaches, namely, the camera-on and the vote/chat approaches in a synchronous online learning environment. We found that using individual engagement methods, such as requiring cameras to be on or using the vote and chat functions to elicit student responses, improves learning outcomes. Surprisingly, the combined use of these methods hinders student learning, and they perform no better than the control group where no specific engagement methods were required. We posit that the reason for this result is that too much engagement increases total cognitive load to a point where it is detrimental to learning.

Large Language Model (LLM) artificial intelligence tools present a unique challenge for educators who teach programming languages. While LLMs like ChatGPT have been well documented for their ability to complete exams and create prose, there is a noticeable lack of research into their ability to solve problems using high-level programming languages. Like many other university educators, those teaching programming courses would like to detect if students submit assignments generated by an LLM. To investigate grade performance and the likelihood of instructors identifying code generated by artificial intelligence (AI) tools, we compare code generated by students and ChatGPT for introductory Python homework assignments. Our research reveals mixed results on both counts, with ChatGPT performing like a mid-range student on assignments and seasoned instructors struggling to detect AI-generated code. This indicates that although AI-generated results may not always be identifiable, they do not currently yield results approaching those of diligent students. We describe our methodology for selecting and evaluating the code examples, the results of our comparison, and the implications for future classes. We conclude with recommendations for how instructors of programming courses can mitigate student use of LLM tools as well as articulate the inherent value of preserving students’ individual creativity in producing programming languages.

This study draws from feedback intervention theory and professional communications theory to present a versatile, experiential class project to develop and improve students’ virtual communications and presentation skills by combining hard and soft-skill development, multisource feedback, and self-reflection. After successfully using this class project for four semesters, data were collected from six graduate classes (N = 145) to assess the project's effectiveness and students’ perceptions. Positive student feedback, control group–trained group comparisons, and the trained group's Time 1–Time 2 performance comparisons provide supportive evidence for the effectiveness of the project as a valuable learning tool in helping students develop virtual communication and presentation skills. As companies and institutions across industries continue to utilize virtual work arrangements, this project will be a useful tool for preparing students for the postpandemic digital business world.

The purpose of this study is to understand how instructor clarity and computer-mediated behaviors influence students’ affective learning and technology self-efficacy in online supply chain management (SCM) courses, which show how the instructor–student relationship affects online learning experiences. Data were collected through an online questionnaire using the Prolific human subject's pool. The data supported a model in which instructors’ clarity and computer-mediated immediate behaviors indirectly influenced students’ technology self-efficacy and affect for the course through the mediation of perceived immediacy. Affect for the instructor did not fit into the final model. The findings in this study help SCM instructors navigate the pedagogical pivot that may be required for the next unexpected event (pandemic, etc.) without compromising student learning goals.

This article argues that current Supply Chain Management (SCM) education and training is inadequate to meet the human capital needs of industry. To bridge this gap, we propose the development and deployment of SCM educational programs that provide learning opportunities earlier in students’ educational journeys. We argue that such programs should be based on self-directed learning of SCM knowledge, business concepts/skills, and their real-life application with help from industry partners. We present a case study of a four-way partnership SCM educational program for high schoolers, which utilizes a project-based learning method. Survey data and focus group discussion revealed positive developmental learning outcomes, the program's uniqueness, and challenges such as lack of awareness, expertise, and industry partners. We evaluate the efficacy of this four-way partnership among industry, government agencies, universities, and high schools and discuss the importance of “champions” for each partner. Our findings offer a scalable educational model that leverages multi-stakeholder engagement to address the SCM talent and educational conceptual gap.

Smart supply chain management (SSCM) has recently attracted significant attention from both industry and academia, particularly in light of the COVID pandemic. This article reviews current literature on information and integration, process automation, advanced analytics, and related business curriculum in SSCM. Our survey results demonstrate a concerning lack of adoption of SSCM in business curriculum and reveal several major challenges faced by educators when teaching SSCM, including a scarcity of available teaching resources, a need for cross-disciplinary knowledge, and a lack of industry experience among students. These findings lead to our exploration of SSCM application in various supply chain and operations functions (e.g., product design, sourcing and procurement, production, quality management, warehouse management and distribution, delivery, and supply chain risk management) during the COVID-19 pandemic. Drawing on our analysis, we conclude by offering several recommendations for promoting SSCM in business education.

The use of gamification to enhance learning in education has been well documented. However, little is known about whether gamification can impact supply chain management knowledge and behaviors among healthcare professionals. In this study, we tested the effectiveness of a simulation app (ShipShape) designed and developed to gamify the fundamental concepts of supply chain management. We field tested the effectiveness of the app to impact knowledge gain and supply chain practice by asking healthcare professionals to use the app in their day-to-day operations. We collected longitudinal data spanning the period before and after the introduction of the app. The analysis and results of different types of data collected provide support for the positive impact of the app on both supply chain knowledge and practice among healthcare professionals.

Business schools play an important role in making positive contributions to society. Thus, the Association to Advance Collegiate Schools of Business (AACSB) has placed societal impact as an expectation of all accredited schools. This article proposes an integrated multisource and multimethod approach to measure the societal impact of a business school. Using data from various sources (primary data collection via faculty survey and secondary data via faculty annual review documents) we were able to identify societal impact themes that aligned with college activities in teaching, research, and community engagement. AACSB's outlook on societal impact and the United Nations’ sustainable development goals (SDGs) provided the guiding framework. We performed content analyses using DICTION software on the data to algorithmically discover the themes characterizing societal impact. To further support our data collection efforts, faculty listening sessions and discussions with unit heads were also conducted. Decent Work and Economic Growth; and Industry, Innovation, and Infrastructure emerged as the top two themes. Using word clouds, multiple subthemes emerged from these two overarching themes. To conclude, we discuss an approach to operationalizing these themes by quantifying societal impact in a business school.