Results 221 to 230 of about 135,562 (267)
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Learning to think historically
Educational Psychologist, 1994Good historical thinking requires more than mastery of facts, it demands a detailed, densely textured analysis of the relations among those facts. Historical analysis demands the ability to apply abstract concepts to develop hypotheses about cause and effect; the hypotheses must be rigorously supported by evidence and withstand the weight of counter ...
Kathryn T. Spoehr, Luther W. Spoehr
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Deep Learning for Historical Data Analysis
Proceedings of the 3rd Workshop on Structuring and Understanding of Multimedia heritAge Contents, 2021This presentation will give an overview of projects on leveraging deep learning for historical data analysis my group did in the last 3 years, partly in the context of the ANR EnHerit project. I will first discuss how deep learning can be used to retrieve and analyze repeated details in artworks in artwork collections [5, 6].
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Development of ubiquitous historical learning system
Proceedings of the 2005 International Conference on Active Media Technology, 2005. (AMT 2005)., 2005We rarely see the system which supports historical learning according to each situation - before the tour, during the tour, after the tour. We developed the system of historical learning which offers the information according to the situation. It is made from HORIKAWA sightseeing - the tourist industry that gives travelers a sightseeing tour around the
Yusuke Takahashi +2 more
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The Professionalization of Historical Learning
Reviews in American History, 1986The transformation of the study of history from an avocation into a profession was part of a general process of institutionalization which scholarship underwent in the nineteenth century. Until then historians had been amateurs in the strict sense of the word, men who wrote about the past out of sheer love of the subject.
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Learning of SAINNs from Covariance Function: Historical Learning
2003In this paper the learning capabilities of a class of neural networks named Stochastic Approximate Identity Neural Networks (SAINNs) have been analyzed. In particular these networks are able to approximate a large class of stochastic processes from the knowledge of their covariance function.
Paolo Crippa, Claudio Turchetti
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Learning to Understand Historical Context
2022The development of historical thinking in students using active methodologies is an unavoidable opportunity to approach key events in the history of humanity, such as the Nuremberg trials. This chapter presents a proposal for gamification in the classroom through role-playing using a card game designed ad hoc in order to develop historical empathy in ...
Pilar Rivero +3 more
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2004
Alaistair Hannay has presented us a penetrating chapter on “Faith, History, and Approximation,” one that opens up a number of different issues on the topic. He centers his chapter on Soren Kierkegaard’s Concluding Unscientific Postscript and what Hannay finds there about faith in regard to reasoning about the matter of approximation in knowledge.
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Alaistair Hannay has presented us a penetrating chapter on “Faith, History, and Approximation,” one that opens up a number of different issues on the topic. He centers his chapter on Soren Kierkegaard’s Concluding Unscientific Postscript and what Hannay finds there about faith in regard to reasoning about the matter of approximation in knowledge.
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An Historical Perspective of Learning Spaces
2021This chapter offers some reflections on both historical and contemporary effects of specific influences on conceptions of schools and classrooms, particularly as they influence Aotearoa New Zealand education. Ideas about classrooms and schools are illustrated through images from a variety of contexts and times.
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Learning from historical precedent
[1989] Proceedings. The Annual AI Systems in Government Conference, 2003Explanation-based learning, a method of abstracting general principles from a small number of prior cases, is discussed. The author demonstrates the feasibility of applying this method to economic sanction incidents. This approach is contrasted with regression analysis, a traditional quantitative method. A method for integrating these two approaches is
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The Historical Foundation of Learning Disabilities
Remedial and Special Education, 1985This paper reviews the research of Alfred Strauss and Heinz Werner on the behavioral differences between exogenous (brain injured) and endogenous (familial-cultural) mental retardation using quantitative methods of research synthesis. The concept of exogenous mental retardation evolved into present-day conceptions of learning disabilities. The findings,
Kenneth A. Kavale, Steven R. Forness
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