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During the development of a Competence Developing Game’s (CDG) story it is indispensable to understand the target audience. Thereby, CDGs stories represent more than just the plot. The Story is about the
Setting, the Characters and the Plot. As a toolkit to support the
development of such a story, this paper introduces the UserFocused Storybuilding (short UFoS) Framework for CDGs. The Framework and its utilization will be explained, followed by a description of its development and derivation, including an empirical study. In addition, to simplify the Framework use regarding the CDG’s target audience, a new concept of Nine Psychographic Player Types will be explained. This concept of Player Types provides an approach to handle the differences in between players during the UFoS Framework use. Thereby,
this article presents a unique approach to the development of
target group-differentiated CDGs stories.
The Scarab Project
(2015)
Urban Search and Rescue (USAR) is an active research
field in the robotics community. Despite recent advances
for many open research questions, these kind of systems are
not widely used in real rescue missions. One reason is that such
systems are complex and not (yet) very reliable; another is that
one has to be an robotic expert to run such a system. Moreover,
available rescue robots are very expensive and the benefits of
using them are still limited.
In this paper, we present the Scarab robot, an alternative
design for a USAR robot. The robot is light weight, humanpackable
and its primary purpose is that of extending the
rescuer’s capability to sense the disaster site. The idea is that a
responder throws the robot to a certain spot. The robot survives
the impact with the ground and relays sensor data such as
camera images or thermal images to the responder’s hand-held
control unit from which the robot can be remotely controlled.
With autonomous mobile robots receiving increased
attention in industrial contexts, the need for benchmarks
becomes more and more an urgent matter. The RoboCup
Logistics League (RCLL) is one specific industry-inspired scenario
focusing on production logistics within a Smart Factory.
In this paper, we describe how the RCLL allows to assess the
performance of a group of robots within the scenario as a
whole, focusing specifically on the coordination and cooperation
strategies and the methods and components to achieve them.
We report on recent efforts to analyze performance of teams in
2014 to understand the implications of the current grading
scheme, and derived criteria and metrics for performance
assessment based on Key Performance Indicators (KPI) adapted
from classic factory evaluation. We reflect on differences and
compatibility towards RoCKIn, a recent major benchmarking
European project.
Competence Developing Games (CDGs) are a new concept of how to think about games with serious intentions. In order to emphasize on this topic, a new framework has been developed. It basically relies on learning and motivation theories. This ‘motivational Competence Developing Game Framework’ demonstrates how it is possible to use these theories in a CDG development process. The theoretical derivation and use of the framework is explained in this paper.