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Drawing on research conducted mostly in Catalonia (Spain), Moises Esteban-Guitart outlines a distinct vision of education enhanced by students' identities, which leads to a discussion of the sociocultural factors that shape the processes of learning. He brings these ideas to life by examining traits of a mobile-centric society, the present-day ecology of learning, and his three metaphors of learning (connecting knowledge, connecting minds, and connecting communities). He then suggests a number of basic principles regarding learning for the twenty-first century based on prior literature in the learning sciences. He presents the terms 'funds of identity' and 'meaningful learning experiences', and reviews the funds of knowledge approach and the Vygotskian basis for understanding identity. In the second part of the book, he illustrates a number of strategies for detecting students' funds of identity and their meaningful learning experiences, and describes some practical experiences based on the theoretical framework he adopted.

The spatial and temporal dimensions of ecological phenomena have always been inherent in the conceptual framework of ecology, but only recently have they been incorporated explicitly into ecological theory, sampling design, experimental design and models. Statistical techniques for spatial analysis of ecological data are burgeoning and many ecologists are unfamiliar with what is available and how the techniques should be used correctly. This book gives an overview of the wide range of spatial statistics available to analyse ecological data, and provides advice and guidance for graduate students and practising researchers who are either about to embark on spatial analysis in ecological studies or who have started but are unsure how to proceed. Only a basic understanding of statistics is assumed and many schematic illustrations are given to complement or replace mathematical technicalities, making the book accessible to ecologists wishing to enter this important and fast-growing field for the first time.