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- The average time of evaluation results from the experience of the teacher (the
specifics of each course, subject, tasks difficulty level, the type of students, time
assigned for a subject in a learning program)
- Student's stream flow is stochastic, Markovian
- Students are served on one server. There is also the possibility of a queue, which
is characterized by a specific time and method of service
In the case study, the motivation model is simulated using the ARENA software
(Fig.
8.4
). The simulation experiment allows us to analyze the queue's parameters
in a teacher's workstation (“tasks checking” component on Fig.
8.4
), as well as
define the students' service time by specified input parameters. For example, the
following simulation scenario can be evaluated:
Given: 55 students, time interval of 6 days, daily time for tasks' examination -
3 h, expected time for each student - 20 min, correction time - 1 day and predicted
probability of tasks evaluation: 70% - exit with promotion without repository
development, 15% - placing solution in the repository, 15% - sending back for
correction.
One has to: Define the total working time of the teacher assigned to a task
checking with specified output probability distribution, specified students' service
distribution, and estimated time for task checking.
Results: With a limited time interval of maximum 6 days, a queue on the teacher's
side will emerge. Using the same input assumptions, we can establish how many
days the teacher needs in order to evaluate the tasks. It turns out that it is almost 8.
Finally, the simulation allows evaluating parameters such as: limited access to
software and hardware resources, maximum size of social networks queue, and cost
related to the teacher's work. Using statistical data, a group management strategy
can be modified and appropriate adjustments can be made in the repository devel-
opment plan.
8.5 Conclusion
In this chapter, the community-built system has been identified as a form of
knowledge network. The knowledge is modeled using the ontological approach.
The approach allows the representation of knowledge in a formal way available for
further computer processing. Moreover, the ontological approach is compatible
with the concept of semantic web. In the future, the community-built system will be
integrated with the semantic web. Subsequently, multiple software agents can
become participants in the process of populating the knowledge repository.
Using the motivation model, the activity of the community-built system can be
analyzed equally on both technical and knowledge levels. The motivation model
covers two functions important for motivation: that of the creator and that of the
editor and describes their unique interests in supplying a knowledge repository
using the Wiki mechanism. As shown in the case study, the motivation model can
serve as a theoretical framework for different simulation models.
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