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Titlebook: Knowledge Communities in Teacher Education; Sustaining Collabora Cheryl J. Craig,Gayle A. Curtis,M. Michael Pérez Book 2020 The Editor(s) (

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發(fā)表于 2025-3-23 11:04:04 | 只看該作者
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發(fā)表于 2025-3-23 14:42:32 | 只看該作者
,Traveling Journals as Inquiry and Professional Development (2004–2006),r continued professional development. Grounded in the literature on reflective practice (Sch?n in .. Basic Books, New York, NY, 1983; .. Teachers College Press, New York, NY, 1991; . 27(6): 26–34, 1995), this chapter describes how the Traveling Journals came about and evolved, emphasizing their refl
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發(fā)表于 2025-3-23 20:37:16 | 只看該作者
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發(fā)表于 2025-3-24 00:52:13 | 只看該作者
,Negotiating Career Pathway Challenges (1998–Present),egar in .. Falmer Press, London, UK, pp. 235–246, 1998; Munby and Russell in .. Falmer Press, London, UK, pp. 172–184, 1995) to narratively examining challenges encountered in the long careers of the Portfolio Group. From a teacher educator perspective, the chapter brings forth common situations tha
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發(fā)表于 2025-3-24 04:53:04 | 只看該作者
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發(fā)表于 2025-3-24 10:02:17 | 只看該作者
,The Portfolio Group’s Legacy,ons include exemplars of the group’s internal sharing of ideas and member testimonials as to why they have stayed in the Portfolio Group. This chapter also highlights the group’s extensive productivity over time through publications and local, national, and international presentations and spotlights
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發(fā)表于 2025-3-24 12:16:08 | 只看該作者
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發(fā)表于 2025-3-24 17:21:44 | 只看該作者
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發(fā)表于 2025-3-24 22:44:16 | 只看該作者
arises in the linearization of the boundary rigidity problem which is discussed in Section 1. In Section 2 we introduce a class of Riemannian manifolds, convex non-trapping manifolds (CNTM), for which the ray transform can be defined in a very natural way. In the case of positive rank tensor fields,
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發(fā)表于 2025-3-25 02:40:55 | 只看該作者
Cheryl J. Craig,Gayle A. Curtis,Michaelann Kelley,P. Tim Martindell,M. Michael Pérezstances between points on the sphere are as close as possible to the geodesic distances measured between the corresponding points on the cortex. Thereby, our approach maximizes the goodness of fit of distances on the cortex surface to distances on the sphere. We apply our algorithm to sections of th
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