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The development of European power markets is highly influenced by integrated electricity and heat systems. Therefore, decarbonization policies for the electricity and heat sectors, as well as numerical models that are used to guide such policies, should consider cross-sectoral interdependencies and need evaluation. Many model-based policy assessments evaluate potential benefits of combined heat and power. However, the extent of benefits, such as emissions reductions, found in existing studies is subject to considerable variations. While scenarios and model inputs may partly explain such variations, differences in results may also be related to the model formulation itself. Against this background, this study is the first to compare electricity market models in the context of potential benefits of integrated electricity and heat systems in decarbonization. Five large-scale market models covering electricity and heat supply were utilized to study the interactions between a rather simple coal replacement scenario and a more ambitious policy that supports decarbonization through power-to-heat. With a focus on flexibility provision, emissions reduction, and economic efficiency, although the models agree on the qualitative effects, there are considerable quantitative differences. For example, the estimated reductions in overall CO2 emissions range between 0.2 and 9.0 MtCO(2)/a for a coal replacement scenario and between 0.2 and 25.0 MtCO(2)/a for a power-to-heat scenario. Model differences can be attributed mainly to the level of detail of combined heat and power modeling and the endogeneity of generation investments. Based on a detailed comparison of the modeling results, implications for modeling choices and political decisions are discussed.

Climate target achievement has a crucial influence on the modelling and the decision processes in the energy sector. It has motivated the development of several policy instruments to mitigate greenhouse gas emissions, including administrative and market-based mechanisms for phasing out coal-fired generation technologies. In order to analyse such instruments, electricity market and energy system models are widely used. However, the results and the corresponding recommendations largely depend on the formulation of the respective model. This motivates a systematic comparison of five large-scale electricity market models which are applied to European scenarios with a focus of the analysis on Germany considering the period until 2030. A method for the identification of model differences is proposed to analyse the effects of two coal phase-out strategies. This contribution expands on earlier studies and provides some more general takeaways for both modellers and decision-makers. For instance, our analysis demonstrates the influence of the reference scenario on evaluating a policy instrument. Furthermore, the importance of technical aspects, such as the constraints for combined heat and power plants, are discussed, and implications regarding three dimensions (the generation adequacy, economic efficiency and environmental sustainability of power supply) are presented.

In situ polar Kerr effect measurements have been used to study the magnetic anisotropy of Au(111)/Co/X, Pd(111)/Co/X, Cu(111)/Co/X, and Pd(100)/Co/X sandwiches, where X is the nonmagnetic metal Ag, Au, Cu, Ir, and Pd or the insulator MgO. The films were grown by molecular beam epitaxy (MBE). For the metals, we found that the magnitude of the Co/X perpendicular interface anisotropy is strongly peaked at ∼1 atomic layer (1.5-2.5 Å) coverage. To investigate structural influences on the anisotropy, we have used reflection high energy diffraction (RHEED) and low energy electron diffraction (LEED) to measure changes resulting from overlayer coverage. Analysis of digitized RHEED images captured every ∼1 Å during metal overlayer coverage shows no abrupt change of the in-plane lattice constant. We have also investigated the out-of-plane lattice spacing as a function of nonmagnetic metal coverage by measuring LEED I-V curves along the (0,0) rod. In the case of Cu, where the LEED behavior is nearly kinematic, we see no evidence of any abrupt structural changes at ∼1 atomic layer coverage. These results suggest the observed peak in magnetic anisotropy is not structural in origin. The influence of an insulating overlayer, MgO, on the perpendicular magnetic properties was also investigated.

This paper describes the design and ecologically valid evaluation of a learner model that lies at the heart of an intelligent learning environment called iTalk2Learn. A core objective of the learner model is to adapt formative feedback based on students’ affective states. Types of adaptation include what type of formative feedback should be provided and how it should be presented. Two Bayesian networks trained with data gathered in a series of Wizard-of-Oz studies are used for the adaptation process. This paper reports results from a quasi-experimental evaluation, in authentic classroom settings, which compared a version of iTalk2Learn that adapted feedback based on students’ affective states as they were talking aloud with the system (the affect condition) with one that provided feedback based only on the students’ performance (the non-affect condition). Our results suggest that affect-aware support contributes to reducing boredom and off-task behavior, and may have an effect on learning. We discuss the internal and ecological validity of the study, in light of pedagogical considerations that informed the design of the two conditions. Overall, the results of the study have implications both for the design of educational technology and for classroom approaches to teaching, because they highlight the important role that affect-aware modelling plays in the adaptive delivery of formative feedback to support learning.

Robust domain knowledge consists of conceptual and procedural knowledge. The two types of knowledge develop together, but are fostered by different learning tasks. Exploratory tasks enable students to manipulate representations and discover the underlying concepts. Structured tasks let students practice problem-solving procedures step-by-step. Educational technology has mostly relied on providing only either task type, with a majority of learning environments focusing on structured tasks. We investigated in two quasi-experimental studies with 8-10 years old students from UK (N = 121) and 10-12 years old students from Germany (N = 151) whether a combination of both task types fosters robust knowledge more than structured tasks alone. Results confirmed this hypothesis and indicate that students learning with a combination of tasks gained more conceptual knowledge and equal procedural knowledge compared to students learning with structured tasks only. The results illustrate the efficacy of combining both task types for fostering robust fractions knowledge.

Robust domain knowledge consists of conceptual and procedural knowledge. The two types of knowledge develop together, but are fostered by different learning tasks. Exploratory tasks enable students to manipulate representations and discover the underlying concepts. Structured tasks let students practice problem-solving procedures step-by-step. Educational technology has mostly relied on providing only either task type, with a majority of learning environments focusing on structured tasks. We investigated in two quasi-experimental studies with 8-10 years old students from UK (N = 121) and 10-12 years old students from Germany (N = 151) whether a combination of both task types fosters robust knowledge more than structured tasks alone. Results confirmed this hypothesis and indicate that students learning with a combination of tasks gained more conceptual knowledge and equal procedural knowledge compared to students learning with structured tasks only. The results illustrate the efficacy of combining both task types for fostering robust fractions knowledge.

This paper describes the design and ecologically valid evaluation of a learner model that lies at the heart of an intelligent learning environment called iTalk2Learn. A core objective of the learner model is to adapt formative feedback based on students’ affective states. Types of adaptation include what type of formative feedback should be provided and how it should be presented. Two Bayesian networks trained with data gathered in a series of Wizard-of-Oz studies are used for the adaptation process. This paper reports results from a quasi-experimental evaluation, in authentic classroom settings, which compared a version of iTalk2Learn that adapted feedback based on students’ affective states as they were talking aloud with the system (the affect condition) with one that provided feedback based only on the students’ performance (the non-affect condition). Our results suggest that affect-aware support contributes to reducing boredom and off-task behavior, and may have an effect on learning. We discuss the internal and ecological validity of the study, in light of pedagogical considerations that informed the design of the two conditions. Overall, the results of the study have implications both for the design of educational technology and for classroom approaches to teaching, because they highlight the important role that affect-aware modelling plays in the adaptive delivery of formative feedback to support learning.