@incollection{MishraVladova2021,
  author    = {Mishra, Vidisha and Vladova, Gergana},
  title     = {It's personal},
  series = {The fourth industrial revolution and its impact on ethics},
  booktitle = {The fourth industrial revolution and its impact on ethics},
  editor    = {Miller, Katharina and Wendt, Karen},
  publisher = {Springer},
  address   = {Cham},
  isbn      = {978-3-030-57019-4},
  doi       = {10.1007/978-3-030-57020-0_12},
  pages     = {151 -- 158},
  year      = {2021},
  abstract  = {The new technologies of the Fourth Industrial Revolution (4IR) are disrupting traditional models of work and learning. While the impact of digitalization on education was already a point of serious deliberation, the COVID-19 pandemic has expedited ongoing transitions. With 90\% of the world's student population having been impacted by national lockdowns—online learning has gone from being a luxury to a necessity, in a context where around 3.6 billion people are offline. As the impacts of the 4IR unfold alongside the current crisis, it is not enough for future policy pathways to prioritize educational attainment in the traditional sense; it is essential to reimagine education itself as well as its delivery entirely. Future policy narratives will need to evaluate the very process of learning and identify the ways in which technology can help reduce existing disparities and enhance digital access, literacy and fluency in a scalable manner. In this context, this chapter analyses the status quo of online learning in India and Germany. Drawing on the experiences of these two economies with distinct trajectories of digitalization, the chapter explores how new technologies intersect with traditional education and local sociocultural conditions. Further, the limitations and opportunities presented by dominant ed-tech models is critically analyzed against the ongoing COVID-19 pandemic.},
  language  = {en}
}
@article{WilhelmsBoersigYangetal.2022,
  author    = {Wilhelms, Andre and B{\"o}rsig, Nicolas and Yang, Jingwei and Holbach, Andreas and Norra, Stefan},
  title     = {Insights into phytoplankton dynamics and water quality monitoring with the BIOFISH at the Elbe River, Germany},
  series = {Water},
  volume    = {14},
  journal   = {Water},
  number    = {13},
  publisher = {MDPI},
  address   = {Basel},
  issn      = {2073-4441},
  doi       = {10.3390/w14132078},
  pages     = {20},
  year      = {2022},
  abstract  = {Understanding the key factors influencing the water quality of large river systems forms an important basis for the assessment and protection of cross-regional ecosystems and the implementation of adapted water management concepts. However, identifying these factors requires in-depth comprehension of the unique environmental systems, which can only be achieved by detailed water quality monitoring. Within the scope of the joint science and sports event "Elbschwimmstaffel" (swimming relay on the river Elbe) in June/July 2017 organized by the German Ministry of Education and Research, water quality data were acquired along a 550 km long stretch of the Elbe River in Germany. During the survey, eight physiochemical water quality parameters were recorded in high spatial and temporal resolution with the BIOFISH multisensor system. Multivariate statistical methods were applied to identify and delineate processes influencing the water quality. The BIOFISH dataset revealed that phytoplankton activity has a major impact on the water quality of the Elbe River in the summer months. The results suggest that phytoplankton biomass constitutes a substantial proportion of the suspended particles and that photosynthetic activity of phytoplankton is closely related to significant temporal changes in pH and oxygen saturation. An evaluation of the BIOFISH data based on the combination of statistical analysis with weather and discharge data shows that the hydrological and meteorological history of the sampled water body was the main driver of phytoplankton dynamics. This study demonstrates the capacity of longitudinal river surveys with the BIOFISH or similar systems for water quality assessment, the identification of pollution sources and their utilization for online in situ monitoring of rivers.},
  language  = {en}
}