This study investigates the effectiveness of using a learning module that combines interactive nonlinear storytelling games with three-dimensional (3D) simulation models. The story narrative is used to mimic real-world scenarios to train students to apply their knowledge. Using simulation software and games can facilitate practical understanding of complex systems and enhance students’ learning outcomes via situated learning. Situated learning is a pedagogical approach that places learners in real-life problem-solving situations to foster meaningful STEM learning. In this work, students use a nonlinear story to represent and express what they know about inventory and queueing models. Students use the simulation models to examine, analyze, and access virtual worlds that mimic real-world systems, interpret the information, organize their knowledge, and represent what they have learned.
To investigate the effectiveness of combining nonlinear storytelling & simulation-based learning on students’ learning and motivation, two groups are compared: control (simulation-based only) (1), and intervention (nonlinear story and simulation learning game) (2). The control group is composed of students who used simulation models with a traditional case study format. In comparison, the nonlinear story and simulation learning game group is represented by the students who are taught with the aid of the game learning module. The results of this study compared the groups in terms of students’ motivation, engineering identity, and learning outcomes. The data of the control and intervention groups were collected in Fall 2020, and Fall 2021, respectively. The intervention group showed higher overall motivation and learning outcomes compared to the control group.
We propose and assess the effectiveness of novel immersive simulation-based learning (ISBL) modules for teaching and learning engineering economy concepts. The proposed intervention involves technology-enhanced problem-based learning where the problem context is represented via a three-dimensional (3D), animated discrete-event simulation model that resembles a real-world system or situation that students may encounter in future professional settings. Students can navigate the simulated environment in both low- and high-immersion modes (i.e., on a typical personal computer or via a virtual reality headset). The simulation helps contextualize and visualize the problem setting, allowing students to observe and understand the underlying dynamics, collect relevant data/information, evaluate the effect of changes on the system, and learn by doing. The proposed ISBL approach is supported by multiple pedagogical and psychological theories, namely the information processing approach to learning theory, constructivism theory, self-determination theory, and adult learning theory. We design and implement a set of ISBL modules in an introductory undergraduate engineering economy class. The research experiments involve two groups of students: a control group and an intervention group. Students in the control group complete a set of traditional assignments, while the intervention group uses ISBL modules. We use well-established survey instruments to collect data on demographics, prior preparation, motivation, experiential learning, engineering identity, and self-assessment of learning objectives based on Bloom’s taxonomy. Statistical analysis of the results suggests that ISBL enhances certain dimensions related to motivation and experiential learning, namely relevance, confidence, and utility. We also provide a qualitative assessment of the proposed intervention based on detailed, one-on-one user testing and evaluation interviews.
There is a cohesive body of research on the effectiveness of problem-based learning (PBL) for a wide range of learner groups across different disciplines in engineering education. On the other hand, there is a growing interest in using immersive technologies such as virtual reality (VR) in engineering education. While there are many literature review articles on each of these subjects separately, there is a lack of review articles on the application of combined PBL-VR learning environments in engineering education. This paper provides an assessment of the applications and potential of implementing immersive technologies in a PBL setting to utilize the advantages of both paradigms. More specifically, this paper aims to provide insights related to two main questions: (1) where (in what disciplines/subjects) PBL and VR have been used together in engineering education? And, (2) how are VR and PBL integrated and used in engineering education? The first question is investigated by performing a bibliometric analysis of relevant papers published in the proceedings of previous ASEE annual conferences. The second question is explored by performing a literature review and classification of ASEE papers that discuss the use of VR in conjunction with PBL. Our findings reveal a gap between the application of integrated PBL and VR across different disciplines in engineering education. We also analyze the trends related to PBL and VR application in engineering education over time. Finally, we identify and propose future opportunities related to the combination of PBL and immersive technologies, including but not limited to immersive simulation-based learning (ISBL) and incorporating artificial intelligence (AI) into immersive virtual/simulated learning environments used in engineering education.
Even though order picking is the most costly operation in a warehouse, current design practices have used the same principles (straight rows with parallel pick aisles and perpendicular cross aisles) to reduce travel distances between pick locations for more than sixty years. We present an open-source computational software system for facilitating the design of warehouse layouts to near-optimality considering average walking distance of the picker as the objective function. This software is particularly novel because a wide variety of traditional and innovative designs are automatically generated and evaluated. For the warehouse design parameters we consider the rectangular aspect ratio of the floor plan, the number and location of cross aisles, the number and location of pick aisles, and the location of a single input/output location. The main components of the design system are importing pick list profile data, creating the warehouse layout design as a network, product allocation (slotting) of SKUs through the warehouse, routing of pickers on a sample of orders using an exact routing algorithm, and design optimization using a meta-heuristic. We provide both mathematical and computational descriptions of the algorithms used by the software system, describe the types of problems that can be solved, and summarize our computational experience. This software is open source available on a GitHub website under an MIT license.
We introduce the visibility graph as an alternative way to estimate the length of a route traveled by order pickers in a warehouse. Heretofore it has been assumed that
workers travel along a network of travel paths corresponding to centers of aisles, including along the right angles formed where picking aisles join cross aisles. A
visibility graph forms travel paths that correspond to more direct and, we believe, more appropriate “travel by sight.”We compare distance estimations of the visibility
graph and the aisle-centers method analytically for a common traditional warehouse design. We conduct a range of computational experiments for both traditional and
fishbone warehouse layouts to assess the impact of this change in distance metric. Distance estimations using aisle-centers calculates a length of a picking tour on average
10–20% longer compared to distance estimations based on the visibility graph. The visibility graph metric also has implications for warehouse design: when comparing
three traditional layouts, the distance model using a visibility graph resulted in choosing a different best layout in 13.3% of the cases.
This paper presents novel immersive simulation-based learning (I-SBL) modules as an alternative active-learning method for teaching and learning fundamental concepts related to database de-sign. I-SBL involves a 3-dimensional simulated environment that resembles a real-world system.Students can navigate through the simulated environment (in low- and high-immersion modes),observe and understand the underlying dynamics, evaluate the effect of the changes on the system,and learn by doing. The use of such modules is especially important when access to the real system is limited or impossible due to geographical barriers and/or regulations and safety considerations.We assess the impact of the proposed approach by implementing a sample I-SBL module in an undergraduate database class. The study involves two groups of students: control and test groups.Students in the control group complete a traditional problem-based learning (PBL) assignment,while the test group uses the I-SBL version of the same assignment. The assessment data collected include demographics, prior preparation, motivation, usability tests, and pre/post quizzes to mea-sure knowledge gain. Statistical analysis of the results suggests that I-SBL performs at least as wellas PBL. The results also provide important insights into the effective design and implementation of I-SBL.
The problem of improving the environmental performance of a supply chain without entailing excessive cost is becoming a frequent problem as
companies face an increasing pressure from governments and customers for reducing the environmental impact of their activities. As the environmental improvement of an operating supply chain implies not only technology upgrading decisions, but also decisions regarding the structure of the supply chain itself; deciding on what strategy to follow is a complex task. The aim of this work is to provide a bi- objective solution approach for finding such strategy so that both the environmental and financial goals are best met.
In this paper, we describe and compare serial, parallel, and distributed solver implementations for large batches of Traveling Salesman Problems using the Lin-Kernighan Heuristic (LKH) and the Concorde exact TSP Solver. Parallel and distributed solver implementations are useful when many medium to large size TSP instances must be solved simultaneously. These implementations are found to be straightforward and highly efficient compared to serial implementations. Our results indicate that parallel computing using hyper-threading for solving 150- and 200-city TSPs can increase the overall utilization of computer resources up to 25 percent compared to single thread computing. The resulting speed-up/physical core ratios are as much as ten times better than a parallel and concurrent version of the LKH heuristic using SPC3 in the literature. We illustrate our approach with an application in the design of order picking warehouses.