Mathematics learning support centres (MLSC) are widely established and evaluated in English-speaking countries (such as the UK, Ireland and Australia). In most of these countries, several national surveys on MLSCs exist. They give an overview of the number of MLSCs as well as their characteristics in these countries. In Germany, there is a lack of studies on MLSCs and the landscape of MLSCs has not been described yet. This article presents basic information concerning counts of MLSCs and their characteristics at universities. Based on a three-step approach of analysing university homepages and additional personal contact via email or phone calls, we gathered typical MLSC features (e.g. staff quantities and qualification, opening and support hours, supported study programmes). We analysed 190 universities from a web-based register on study programmes. In total, we found 61 MLSCs located at 51 German universities. Another 16 support centres were specialized on mathematics didactics, which means they focussed on didactical and methodological support for preservice teacher students and often provided different teaching materials. Thirty-eight centres were located at universities (62.3%) and 23 MLSCs at universities of applied sciences and comparable universities (37.7%). The MLSCs were different in their sizes of staff and opening hours, and both the numbers of staff and the service hours differed greatly. The student groups MLSCs at German universities focus on differ concerning characteristics like study programme or semester. We will provide the main categories describing these groups. We seek to answer research questions concerning the characteristics of MLSCs in Germany and discuss the results compared to international findings. This information is useful for further international collaborative research, for example a standardized international survey. From a national perspective, these findings support networking and collaborations between the MLSCs as well. As some German MLSCs are facing financial cuts, these results might help in gaining additional funding.
We analyse the impact of learning strategies on engineering students' performance in mathematics. Learning strategies play an important role in self-regulated learning and are a possible predictor of student performance. Especially for mathematics-related learning strategies, the question arises how such strategies can be measured and how they relate to mathematics performance. Therefore, we present a new learning strategy questionnaire that takes into account the specifics of mathematical learning at universities. We then present correlational data of a longitudinal study with n = 403 engineering students. We further regress their performance on students' use of their learning strategies as well as their prior performance. The results indicate which learning strategies help students succeed.
The disciplinary identity as a computer science student has recently received increasing attention as a well-developed subject identity can help with increasing retention, interest and motivation. Besides, identity theory can serve as an analytical lens for issues around diversity. However, identity is also often perceived as a vague, overused concept with a variety of theories to build upon. In addition, connections to other topics, such as computer science conceptions, remain unclear and there seems to be little intra-disciplinary exchange about the concept. This article therefore attempts to provide a starting point by presenting a so far missing systematic literature review of identity in Computing Education Research (CER). We analyzed a corpus of 41 papers published since 2005 with a focus on the variety of identity theories that are used, the reasons for using them and the overall theoretical framing of the concept in the CER literature up to this point. We use content analysis with both inductive and deductive coding to derive categories from the corpus to answer our research questions. The results show that there is less variety in the theories than originally expected, most publications refer to the theory of “Communities of Practice”. The reasons for employing identity theory are also rather canonical, in particular, there is only little theoretical development of the theories within CER and also only little empirical work. Finally, we also present an extended version of a computing identity that can be theoretically derived from the work in our corpus.
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