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Collaboration is used in Software Engineering (SE) to develop software. Industry seeks SE graduates with collaboration skills to contribute to productive software development. SE educators can use Collaborative Learning (CL) to help students develop collaboration skills. This paper uses a Systematic Mapping Study (SMS) to examine the application of the CL educational theory in SE Education. The SMS identified 14 papers published between 2011 and 2022. We used qualitative analysis to classify the papers into four CL paradigms: Conditions, Effect, Interactions, and Computer-Supported Collaborative Learning (CSCL). We found a high interest in CSCL, with a shift in student interaction research to computer-mediated technologies. We discussed the 14 papers in depth, describing their goals and further analysing the CSCL research. Almost half the papers did not achieve the appropriate level of supporting evidence; however, calibrating the instruments presented could strengthen findings and support multiple CL paradigms, especially opportunities to learn at the social and community levels, where research was lacking. Though our results demonstrate limited CL educational theory applied in SE Education, we discuss future work to layer the theory on existing study designs for more effective teaching strategies., Comment: 7 pages

We propose a new approach to measuring the agreement between two oscillatory time series, such as seismic waveforms, and demonstrate that it can be employed effectively in inverse problems. Our approach is based on Optimal Transport theory and the Wasserstein distance, with a novel transformation of the time series to ensure that necessary normalisation and positivity conditions are met. Our measure is differentiable, and can readily be employed within an optimization framework. We demonstrate performance with a variety of synthetic examples, including seismic source inversion, and observe substantially better convergence properties than achieved with conventional $L_2$ misfits. We also briefly discuss the relationship between Optimal Transport and Bayesian inference., Comment: This is a pre-copyedited, author-produced version of an article accepted for publication in Geophysical Journal International following peer review. The version of record is available at https://doi.org/10.1093/gji/ggac151

In this chapter, we survey some recent developments in the field of geophysical inversion. We aim to provide an accessible general introduction to the breadth of current research, rather than focussing in depth on particular topics. In particular, we hope to give the reader an appreciation for the similarities and connections between different approaches, and their relative strengths and weaknesses., Comment: 32 pages, 2 figures. Original manuscript submitted for review as a chapter of "Data Assimilation and Inverse Problems in Geophysical Sciences", eds. Alik Ismail-Zadeh, Fabio Castelli, Dylan Jones and Sabrina Sanchez