The current study examines the personal epistemology of fourth-grade elementary school teachers from Germany (n = 10) and the United States (n = 10) to gain a more nuanced understanding of teachers’ beliefs about knowledge and knowing through a cross-cultural lens. Analyses of semi-structured interviews reveal similarities and differences in the statements of teachers. Four themes are identified: The majority of teachers believed that (a) knowing is uncertain and (b) knowledge has domain-specific qualities; (c) U.S. teachers seemed to view knowledge more as being embedded within their community, while (d) German teachers discussed more internal knowledge sources. The general discussion includes possible cross-cultural explanations for these four emerging themes and points tentatively to developmental issues stemming from uncertainty beliefs. Conceptual and educational implications are discussed and suggestions for future research are given.
This paper examines the conceptualization and measurement of epistemological and ontological phenomena and makes recommendations for improving the conceptual framework and methodological assessment of these phenomena. I discuss the ways educational researchers have studied beliefs and how this research can be improved through a comprehensive conceptual framework and better measurement. This paper provides definitions of epistemological and ontological beliefs and world views, discusses six complementary strategies for assessing these beliefs, compares the strengths of these strategies, and provides examples of how they have been used in the research literature. This paper discusses challenges related to the development of a comprehensive theoretical framework for beliefs, as well as ways to improve measurement of these beliefs and summarizes six emergent themes.
It is shown that the understanding of documents in general and of line drawings in particular can be seen as a first step towards the the understanding of arbitrary scenes by making effective use of methods from artificial intelligence. The starting point is a set of domain-independent linear image primitives which define a line graph. After the removal of artifacts the recognition of meaningful complex structures is accomplished in several steps with the aid of a growing amount of domain-specific knowledge. Further scene knowledge controls the deployment of the various operators to arrive at a consistent interpretation throughout the scene. The selection of the object-oriented programming paradigm proved to be very effective. >