Explore the dynamic behavior, of a system dynamics model

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Reference no: EM132916184

Instructions

LEARNING OBJECTIVES

In this learning laboratory you will examine the stock, flow, feedback loop structure, and explore the dynamic behavior, of a system dynamics model of student workload management. Your learning objectives are to gain some basic familiarity with the model, and use it to develop insights into strategies for managing an academic workload during a typical college or university semester.

USER INTERACTION

The Student Workload Learning Laboratory allows the user to set-up simulation experiments from both the perspective of the faculty and the student.

From the faculty's perspective the user can specify the type of the semester the virtual student will face by determining the difficulty of the homework assignments (specifying a "1" sets-up an "easy" semester; a "2" sets-up a "moderate" semester; and a "3" sets-up a "hard" semester), and and whether or not the assignments have to be turned-in weekly or by the end of the semester. In the base run, the semester is of moderate difficulty and all assignments have to be turned-in on a weekly basis.

From the student's perspective the user can specify three characteristics for the virtual student that help to determine his/her study strategy for the semester. The user can also chose to activate two coping mechanisms that the virtual student can employ in an effort to deal with a tough semester.

The specific characteristics the user can choose to help determine the virtual student's study strategy for the semester include:

(a) A Switch for Procrastination Strategy. If this switch is activated (i.e., assigned a value of 1), the virtual student will use all available time remaining in the semester to do his/her assignments. If it is turned-off (i.e., assigned a value of 0), he/she will complete, and turn-in, each assignment in one week's time. In the former case, the faculty gives the student the entire term to do the assignments, while in the latter case the student is given one week to do each assignment. Note however that, in the case in which the faculty gives the student until the end of the semester to turn in all assignments, the user can still specify that the student will turn in assignments weekly. This reflects the notion that some students like to do their work immediately and steadily, and prefer not to wait until the last minute to get things done. In the base run simulation the assumption is that the faculty requires the virtual student to turn in assignments weekly.

(b) Initial Student's Desired Grade Point Average. In the base run this is a fixed average of 85 points out of a possible 100 on each assignment (i.e., a solid "B" average).

(c) Student's Limit on Hours Worked Per Week. The user can specify the maximum number of hours the virtual student is willing/able to devote to homework each week. This reflects both personality (some people will only do "so much" work each week as "life's too short," while others will "work until they drop"), as well as life's realities (e.g., the student may have to hold down a job while going to school, take care of children or elderly parents when not on campus, etc.). In the base run this value is set to 80 hours per week.

The two coping mechanisms that can be tested to see if/how they help the virtual student deal with a tough semester include:

(a) Adaptive Desired Grade Point Average. For a coping strategy the user can try allowing the student to modify his/her goal for a grade point average as the semester unfolds and he/she gains experience with the challenges of the workload.

(b) Student's Use of Stimulants. Another coping strategy the user can try is allowing the virtual student to use stimulants such as coffee, Red Bull, or even Ritalin to enable him/her to work longer than their normal maximum hours worked per week.

EXAMINING MODEL STRUCTURE

System dynamicists believe that a system's structure is responsible for its behavior. To begin using the learning laboratory click on either the "Examine Model Structure" button or the "Explore Model Behavior" button. Although you can easily move between the two areas, it's usually best to start by examining the system's STRUCTURE.

EXPLORING MODEL BEHAVIOR

When you are ready to begin exploring the model's BEHAVIOR go to the Simulation Set-Up dashboard by clicking on the "Explore Model Behavior" button. The base run should be set-up with all of the switches turned off, a desired GPA of 85, an 80 hour student work week, a student personality that avoids procrastination, a semester of medium difficulty, and assignments that are due on a weekly basis.

Once you have verified that the conditions are correct for the base run, click on the "Go Run the Simulation" button and examine the simulation dashboard. Be sure to clear any previous simulation runs that might be present by hitting the "Clear All Results" button.

1. To see the base run, hit the "Run the Model Once" button. What happened? Can you talk your way through the simulation run? What was the simulation score?

Copy and paste a screen shot of the six graphs from the simulation dashboard into your homework document and add the appropriate commentary.

2. In the base run the virtual student faces a semester of moderate difficulty. Try running both an easy and then a hard semester, with all the other assumptions held constant. What happens? What were the simulation scores?

Copy and paste a screen shot of the six graphs from each of the simulation runs into your homework document and add the appropriate commentary.

3. Go to the Simulation Set-Up dashboard and activate the End-of-Term Assignment Deadlines switch, but leave the Switch for Procrastination Strategy inactive. In other words, the virtual student will steadily complete his/her assignments on a weekly basis, even though the faculty gives him/her all remaining time in the semester to do the work. Run the easy, moderate, and hard semester scenarios. What happens? Why? What were the simulation scores?

Copy and paste a screen shot of the six graphs from each of the simulation runs into your homework document and add the appropriate commentary

4. Rerun the scenarios from #3 above with the Switch for Procrastination Strategy activated. In other words, the faculty again gives the virtual student all remaining time in the semester to do the work, but now he/she takes full advantage of the lenient completion schedule. What happens? Why? What were the simulation scores?

Copy and paste a screen shot of the six graphs from each of the simulation runs into your homework document and add the appropriate commentary

5. Rerun each of the three scenarios from #4 with

(a) the Switch for Student's Use of Stimulants activated.

(b) the Switch for Adaptive Desired Grade Point Average.

(c) both the Switch for Student's Use of Stimulants AND the Switch for Adaptive Desired Grade Point Average activated. Do these coping strategies solve any problems? Why? What were the simulation scores?

Copy and paste a screen shot of the six graphs from each of the simulation runs into your homework document and add the appropriate commentary

6. Run a "full court press" simulation by essentially turning everything on. Make it a hard semester, activate all the switches, boost the virtual Student's Limits on Hours Worked Per Week to the max and his/her Initial Desired Grade Point Average to the minimum. What happens? Why? What were the simulation scores?

Copy and paste a screen shot of the six graphs from each of the simulation runs into your homework document and add the appropriate commentary.

7. Try some "free style" simulations in which you set-up the simulator in an interesting way. What did you do? What happened? Why? What were the simulation scores?

Copy and paste a screen shot of the six graphs from each of the simulation runs into your homework document and add the appropriate commentary

8. Summarize the results of all your simulation experiments. What, if anything, can you say about student workload strategies?

9. With the well-known caveat from George P. Box (of Box-Jenkins Time Series Analysis fame) that "All models are wrong, but some are useful," do you notice any obvious problems with the model? How might is be fixed or further modified and extended?

Attachment:- Modeling.rar

Reference no: EM132916184

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