Pattern Classification May Be Key to Learning

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Pattern Classification May Be Key to Learning

机译：模式分类可能是学习的关键

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It is both the bane of many parents and what has been called a major national vulnerability: the inability of many children to understand mathematics. Developing strategies to overcome that problem is the research focus of Nicole McNeil, associate professor of psychology at the University of Notre Dame, South Bend, Ind. Members of the CLAD (Cognition, Learning and Development) Lab that McNeil directs recently collaborated with colleagues at Vanderbilt University, Nashville, Tenn., to examine how the labels educators use to identify patterns affects preschoolers' understanding of these patterns. They compared concrete labels, which refer to the changing physical features of the pattern (e.g., "red, white, red, white"), to abstract labels, which describe the pattern using an arbitrary system that mimics the pattern (e.g., "A, B, A, B").

机译：这既是许多父母的祸根，又是所谓的主要国家脆弱性：许多孩子无法理解数学。开发克服该问题的策略是印第安那州南本德市圣母大学心理学副教授妮可·麦克尼尔（Nicole McNeil）的研究重点。麦克尼尔领导的CLAD（认知，学习与发展）实验室成员最近与田纳西州纳什维尔的范德比尔特大学（Vanderbilt University）研究了教育者用来识别模式的标签如何影响学龄前儿童对这些模式的理解。他们比较了具体的标签（该标签指的是图案的不断变化的物理特征（例如，“红色，白色，红色，白色”））与抽象的标签（这些标签使用模拟该图案的任意系统来描述该图案）（例如“ A ，B，A，B“）。

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《USA today》 |2015年第2843期|5-6|共2页
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1. A Truly Online Learning Algorithm using Hybrid Fuzzy ARTMAP and Online Extreme Learning Machine for Pattern Classification [J] . Wong Shen Yuong, Yap Keem Siah, Yap Hwa Jen, Neural processing letters . 2015,第3期

机译：结合模糊ARTMAP和在线极限学习机的模式分类真正在线学习算法
2. A Truly Online Learning Algorithm using Hybrid Fuzzy ARTMAP and Online Extreme Learning Machine for Pattern Classification [J] . Shen Yuong Wong, Keem Siah Yap, Hwa Jen Yap, Neural Processing Letters . 2015,第3期

机译：结合模糊ARTMAP和在线极限学习机的模式分类真正在线学习算法
3. Reinforcement learning combined with a fuzzy adaptive learning control network (FALCON-R) for pattern classification [J] . Quah KH, Quek C, Leedham G Pattern Recognition: The Journal of the Pattern Recognition Society . 2005,第4期

机译：强化学习结合模糊自适应学习控制网络（FALCON-R）进行模式分类
4. Patterns for Learning, and Metadesign: Key Challenge for Learning Environment Designers [C] . Tom Boyle ED-MEDIA 2000 . 2000

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5. Semi-Supervised Machine Learning Techniques for Classification of Evolving Data in Pattern Recognition =TECHNIQUES SEMI-SUPERVISéES D'APPRENTISSAGE MACHINE POUR LA CLASSIFICATION DES DONNéES EN éVOLUTION EN RECONNAISSANCE DE FORMES [D] . Tencer, Lukas. 2017

机译：半监督机器学习技术，用于模式识别中不断发展的数据分类=在表单识别中对数据进行分类的半监督机器学习技术
6. Classification of Watermelon Seeds Using Morphological Patterns of X-ray Imaging: A Comparison of Conventional Machine Learning and Deep Learning [O] . Mohammed Raju Ahmed, Jannat Yasmin, Eunsung Park, 2020

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Pattern Classification May Be Key to Learning

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