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Titlebook: Multidisciplinary Research on Teaching and Learning; Wolfgang Schnotz,Alexander Kauertz,Johanna Pretsch Book 2015 Palgrave Macmillan, a di

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書目名稱Multidisciplinary Research on Teaching and Learning
編輯Wolfgang Schnotz,Alexander Kauertz,Johanna Pretsch
視頻videohttp://file.papertrans.cn/641/640380/640380.mp4
圖書封面Titlebook: Multidisciplinary Research on Teaching and Learning;  Wolfgang Schnotz,Alexander Kauertz,Johanna Pretsch Book 2015 Palgrave Macmillan, a di
描述This collection indicates how research on teaching and learning from multiple scientific disciplines such as educational science and psychology can be successfully pursued by a co-operation between researchers and school teachers. The contributors adopt different methodological approaches, ranging from field research to laboratory experiments.
出版日期Book 2015
關鍵詞Interdisciplinary orientation (in educational research); Process orientation (in educational research
版次1
doihttps://doi.org/10.1057/9781137467744
isbn_softcover978-1-349-50007-9
isbn_ebook978-1-137-46774-4
copyrightPalgrave Macmillan, a division of Macmillan Publishers Limited 2015
The information of publication is updating

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Book 2015This collection indicates how research on teaching and learning from multiple scientific disciplines such as educational science and psychology can be successfully pursued by a co-operation between researchers and school teachers. The contributors adopt different methodological approaches, ranging from field research to laboratory experiments.
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ogy can be successfully pursued by a co-operation between researchers and school teachers. The contributors adopt different methodological approaches, ranging from field research to laboratory experiments.978-1-349-50007-9978-1-137-46774-4
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Multidisciplinary Research on Teaching and Learning
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Wolfgang Schnotz,Alexander Kauertz,Johanna Pretsch
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History of Neural Networks,on to artificial neural systems, 2001) [8], Nielsen (Neurocomputing, 1990 [9] in terms of the development of architectures and algorithms that are widely used today. The history of neural networks has been divided in four stages: Beginning of neural networks, First golden age, Quiet Years and Renewe
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