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Learning from worked-out examples has been shown to be very effective in initial cognitive skill acquisition. In order to fully exploit the potential of example-based learning, teachers should, however, know how to effectively employ such examples in classroom instruction. Therefore, we have designed a computer-based learning environment in which mathematics and science teachers learn how to effectively employ worked-out examples. The learning environment was developed according to approved design criteria. The topics that are addressed in the learning environment were chosen in response to the results of a needs assessment that analysed schoolbooks and classroom videos, and took interviews with teachers into account. In experiments as well as in several teacher trainings on example-based learning, the computerbased learning environment was evaluated and improved accordingly. On a more general level, our research and development project showed that a computer-based learning programme could be a sensible tool that supports follow-up work in teacher training contexts.

Many renewable sources for electricity generation are distributed and volatile by nature, and become inefficient and difficult to coordinate with traditional power transmission paths. As a part of the transition from fossil fuel to renewable sources, local energy markets allow an efficient allocation and distribution of energy from local sources to nearby households. When using a discrete time double auction model, bids in such markets reflect the supply and demand of energy. However, since the energy demand of a household contains personal information, such markets are not in line with privacy legislation.In this paper, we investigate the influence of anonymization methods on local energy markets. In particular, we anonymize the bids of the order book, and we compare the CO2 emissions and the expenses of market participants of this allocation with a non-anonymous one. We have modeled the flows of personal data for a local energy auction platform, and we have developed a model for the supply and demand of electricity of a small town in the near future. Our experiments show that with elementary anonymization methods, the impact of anonymization on the costs and on the CO2 emissions is small.

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Neuartige Produktionskonzepte für chemische und verfahrenstechnische Herstellungsprozesse rücken verstärkt in den Fokus der Industrie. Hier werden die wichtigsten Anforderungen an logistische Assets, Steuerungs‐ und Planungsprozesse sowie Mitarbeiter dargestellt, die zu bearbeiten sind, um die Vorteile der Modularisierung in der Prozessindustrie nutzbar zu machen. Dabei ist zu berücksichtigen, dass das dargestellte Forschungsprogramm keinen Anspruch auf Vollständigkeit erhebt. Gespräche mit Verantwortlichen in der Supply Chain und Logistik der Prozessindustrie haben die Bedeutung der dargestellten Forschungsaufgaben jedoch bestätigt. Weitere Themen (z. B. in Bezug auf Geschäftsmodelle und IT‐Integration) können bei Bedarf ergänzt werden.