@article{MileoSchaubMericoetal.2011,
  author    = {Mileo, Alessandra and Schaub, Torsten H. and Merico, Davide and Bisiani, Roberto},
  title     = {Knowledge-based multi-criteria optimization to support indoor positioning},
  series = {Annals of mathematics and artificial intelligence},
  volume    = {62},
  journal   = {Annals of mathematics and artificial intelligence},
  number    = {3-4},
  publisher = {Springer},
  address   = {Dordrecht},
  issn      = {1012-2443},
  doi       = {10.1007/s10472-011-9241-2},
  pages     = {345 -- 370},
  year      = {2011},
  abstract  = {Indoor position estimation constitutes a central task in home-based assisted living environments. Such environments often rely on a heterogeneous collection of low-cost sensors whose diversity and lack of precision has to be compensated by advanced techniques for localization and tracking. Although there are well established quantitative methods in robotics and neighboring fields for addressing these problems, they lack advanced knowledge representation and reasoning capacities. Such capabilities are not only useful in dealing with heterogeneous and incomplete information but moreover they allow for a better inclusion of semantic information and more general homecare and patient-related knowledge. We address this problem and investigate how state-of-the-art localization and tracking methods can be combined with Answer Set Programming, as a popular knowledge representation and reasoning formalism. We report upon a case-study and provide a first experimental evaluation of knowledge-based position estimation both in a simulated as well as in a real setting.},
  language  = {en}
}
@article{TrainiKleinertBittmann2021,
  author    = {Traini, Claudia and Kleinert, Corinna and Bittmann, Felix},
  title     = {How does exposure to a different school track influence learning progress?},
  series = {Research in social stratification and mobility},
  volume    = {76},
  journal   = {Research in social stratification and mobility},
  publisher = {Elsevier},
  address   = {Amsterdam [u.a.]},
  issn      = {0276-5624},
  doi       = {10.1016/j.rssm.2021.100625},
  pages     = {285 -- 298},
  year      = {2021},
  abstract  = {German secondary education is known for its early, strict selection of students into different schooling tracks based on prior academic performance, based on the assumption that students learn more efficiently when the learning environment is tailored to their individual abilities and needs. While much previous research has shown that entry into tracks is socially selective, less is known whether there are effects of being exposed to a particular school track on educational success and which mechanisms are contributing to these effects. We investigate this question by comparing the learning progress in reading and mathematics of students in the upper and intermediate schooling track over five years of secondary schooling, based on large-scale German-wide longitudinal data (NEPS-SC3). Even when restricting our sample to a group of students with similar preconditions and controlling for skills at the beginning of secondary schooling, we find that the learning progress in the upper track is higher for both domains, suggesting scissor effects of track exposure. It is mainly the average performance level of the class, and to a lesser degree its social background composition, which mediates these effects. In contrast, migration background composition of the class and instructional quality perceived by students hardly contribute to explaining increasing learning gains in the upper track.},
  language  = {en}
}