@inproceedings{KoenigWolf2016,
  author    = {K{\"o}nig, Johannes Alexander and Wolf, Martin},
  title     = {A new definition of competence developing games - and a framework to assess them},
  series = {ACHI 2016 : The Ninth International Conference on Advances in Computer-Human Interactions},
  booktitle = {ACHI 2016 : The Ninth International Conference on Advances in Computer-Human Interactions},
  isbn      = {978-1-61208-468-8},
  pages     = {95 -- 97},
  year      = {2016},
  abstract  = {There are different types of games that try to make use of the motivation of a gaming situation in learning contexts. This paper introduces the new terminology 'Competence Developing Game' (CDG) as an umbrella term for all games with this intention. Based on this new terminology, an assessment framework has been developed and validated in scope of an empirical study. Now, all different types of CDGs can be evaluated according to a defined and uniform set of assessment criteria and, thus, are comparable according to their characteristics and effectiveness.},
  language  = {en}
}
@article{KosterScheidweilerTieves2016,
  author    = {Koster, Arie and Scheidweiler, Robert and Tieves, Martin},
  title     = {A flow based pruning scheme for enumerative equitable coloring algorithms},
  series = {A flow based pruning scheme for enumerative equitable coloring algorithms},
  journal   = {A flow based pruning scheme for enumerative equitable coloring algorithms},
  doi       = {10.48550/arXiv.1607.08754},
  pages     = {1 -- 30},
  year      = {2016},
  abstract  = {An equitable graph coloring is a proper vertex coloring of a graph G where the sizes of the color classes differ by at most one. The equitable chromatic number is the smallest number k such that G admits such equitable k-coloring. We focus on enumerative algorithms for the computation of the equitable coloring number and propose a general scheme to derive pruning rules for them: We show how the extendability of a partial coloring into an equitable coloring can be modeled via network flows. Thus, we obtain pruning rules which can be checked via flow algorithms. Computational experiments show that the search tree of enumerative algorithms can be significantly reduced in size by these rules and, in most instances, such naive approach even yields a faster algorithm. Moreover, the stability, i.e., the number of solved instances within a given time limit, is greatly improved. Since the execution of flow algorithms at each node of a search tree is time consuming, we derive arithmetic pruning rules (generalized Hall-conditions) from the network model. Adding these rules to an enumerative algorithm yields an even larger runtime improvement.},
  language  = {en}
}