Lectures and Grading

It is recommended that very little lecture time be spent specifically on Littlefield Technologies. In Stanford's Operations course, there was a 10-minute demonstration of the software on the first or second day of the course just to show the students what they should expect if they are using the software correctly. After each assignment completed, there were also 20-minute class discussions where the most successful teams described what they did and their rationale. Other than these times, Littlefield Technologies was only occasionally mentioned, for example, to set up the context for some concept being taught in class. References to Littlefield Technologies were limited in class to support the idea that students were "on their own" in managing the factory, as they might be in a real-life setting, and that it was up to them to figure out how to apply and extend concepts from the course to the more complex (and thus more realistic) Littlefield Technologies setting.

Although students have access to team standings from their online factories, many professors print out that table before each class and post it somewhere in the classroom.  This re-inforces the competitive nature of the game and keeps it at the forefront of students' minds.

After each of two assignments, each student team typically turn in a "memo" describing their actions during the game and presenting an analysis either justifying their actions or arguing that some other set of actions would have done even better. The analysis should use the analytical tools presented in lectures. The assignments are mainly graded on the analysis, although a small portion of the grade may also depend on the team's final score in the simulation. Instructors can request a packet of electronic documents that include sample assignments and teaching notes.

Finally, after each assignment is graded, a one or two-page handout is distributed to students that describes more details of the scenario they just experienced (i.e., the values of demand and the resulting minimum required number of machines) The handouts do not generally present any claims to "optimal" behavior. Instead, the handout describes how the most successful teams approached the problem of managing the factory, including the analytical tools they used and their resulting decisions.