Inspired by Isaac Asimov’s "Foundation", Professor Ernesto Pacheco developed LOST (Logistics Simulator) with the aim of understanding how people make decisions in the area of logistics. The game fosters the integration of different elements to enhance the learning experience and make it possible to detect areas of opportunity.
By Ernesto Pacheco Velázquez
Being a math student and, along the way, reading the author Isaac Asimov, is not at all unusual. Within Asimov's collection of books, I found "Foundation" and, since then, psychohistory and the character of Hari Seldon have come to form part of my vocabulary. "Foundation" is a science-fiction series about the conduct of a society of the future and the possibility of modeling its behavior by creating a mathematical science that can explain and predict its changes. The search for the creation of this science (which Asimov calls psychohistory) is conducted by a group of scientists led by a mathematician: Hari Seldon.
Mathematicians cannot possibly read these books without dreaming of founding psychohistory. Even though it is a science fiction novel located in the future, psychohistory appears to have originated from the answer to the question: How do people make decisions? Even at the individual level, there is no easy answer to this question. Understanding how people make decisions gave my doctoral thesis meaning, and led to a research project in the area of logistics: LOST (Logistics Simulator), which is basically a simulator for making logistics decisions.
Although officially the aim was to create a tool with which students could compete and have fun demonstrating their knowledge in logistics, while being motivated and driven to study, research and experiment. Basically, the main reason for creating this game was to understand how people make decisions in the area of logistics.
Initially, LOST presented a scenario for decision-making in the field of logistics, which contemplates random demands, production restrictions, occasional machine failures, supplier offers, variable percentages of defective items, and so on. The scenario grew so much and the number of variables was so great that it was impossible to understand how my students made decisions. In the end, I could only see their decisions, but not understand why they had made them, which variables they had considered, or which factors had gone unnoticed.
In addition, the simulator contemplated knowledge in subjects such as forecasting, inventories, production, optimization and other related topics: covering this content in a single course was not feasible. Nevertheless, the game was transferred to the classroom and I decided to spend a few class hours discussing and debating topics that were not contemplated in the program. The response was unexpected. The students were extremely motivated to achieve better results in the game and although it included subjects they had not yet studied, they eagerly investigated and found out how to make decisions in those areas.
Posting rankings that allowed students to compare their results with those of their teammates in the group was a wise move. Their motivation to reach the top sports in the ranking led them to repeat and understand the game, and made them think of the interrelationships generated between different departments. In the feedback questionnaires answered at the end of the game, students felt that LOST helped them to make decisions and understand the consequences of their decision.
Based on the results, I presented the game at educational innovation congresses and projects. In this way, LOST won three major awards:
● Second place in the Regional Award Latin America (Reimagine Education, 2015)
● Third place in the category Presence Learning (Reimagine Education, 2015)
● Novus Award as one of the best projects (ITESM, 2016)
In order to generate gradual learning, the game was divided into scenarios that included variables with increasing degrees of difficulty. When students achieve satisfactory results, they can move on to a new, more complex scenario where they have to take a greater number of decisions and incorporate new variables, thus increasing their knowledge and his expertise.
The acceptance of the game has been excellent, fostering the integration of different elements to enhance the learning experience and make it possible to detect areas of opportunity. For example: the incorporation of logistics indicators; the use of instructional videos; the use of questionnaires to measure knowledge; and the creation of an online game. This improvement project has come to be known as the "Asimov Project".
Despite all this effort, the answer to the initial question remains a mystery to me: How do people make decisions? The development of a science that can predict the behavior of a society or an individual is still a long way off, so I have come to the conclusion that Hari Seldon has not yet been born. However, I also accept that the progress made so far is highly valuable. I would like to invite you to learn more about this tool and hope you not only have fun with it, but also gain new knowledge. If you are a teacher, I urge you to explore this platform and, if possible, implement it within your courses. The results will surprise you.
About the author
Ernesto Pacheco is a Doctor of Operations Management and a full-time professor in the Department of Industrial Engineering at Tecnológico de Monterrey, Campus Ciudad de México. He teaches the courses Operations Research, Inventory Theory, Production Management, Statistics, and Decision-Making. He participates actively in research projects and is a member of diverse interdisciplinary research groups, working on educational innovation initiatives.