Azilawati Jamaludin, David Hung Wei Loong, L. Xuan
{"title":"Developments in educational neuroscience: implications for the art and science of learning","authors":"Azilawati Jamaludin, David Hung Wei Loong, L. Xuan","doi":"10.1080/23735082.2019.1684991","DOIUrl":null,"url":null,"abstract":"ABSTRACT Learning is a complex phenomenon where a learner constitutes a system operating at neural, physiological, cognitive and social levels, with interactions between and across processes and levels, effecting neural to cognitive to social levels and vice versa. In tracing historical paradigms, theories of learning have been traditionally fragmented in nature, typically focusing on sub-process or sub–levels of the system. For example, theories of cognitivism focuses on internal processes and connections that take place during learning, negating observed behaviours or outward behaviours of learning, while theories of social constructivism place strong emphasis on human development and knowledge construction that is socially situated, with less attention paid to individual differences and variations. In recognizing inherently complex interrelated learning systems, a more integrated and comprehensive understanding of learning is necessary. Such an understanding entails research endeavours that can harness multiple, complex parameters of the learner system through mapping and understanding interactions between and across learning processes and levels. Such endeavours entail the use of multiple sources of scientific evidence, across multi-modal data capture modes and multi-levels of analyses, informed by multi-disciplinary theoretical framings. In this paper, we argue that an overarching scientific ethos towards learning optimizations need artful implementations of pedagogies and interventions that close the circle—from scientific findings translated into practical applications in education and back to addressing problems in education as impetus for evidence-informed theorizations of learning.","PeriodicalId":52244,"journal":{"name":"Learning: Research and Practice","volume":"149 1","pages":"201 - 213"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Learning: Research and Practice","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/23735082.2019.1684991","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Social Sciences","Score":null,"Total":0}
引用次数: 2
Abstract
ABSTRACT Learning is a complex phenomenon where a learner constitutes a system operating at neural, physiological, cognitive and social levels, with interactions between and across processes and levels, effecting neural to cognitive to social levels and vice versa. In tracing historical paradigms, theories of learning have been traditionally fragmented in nature, typically focusing on sub-process or sub–levels of the system. For example, theories of cognitivism focuses on internal processes and connections that take place during learning, negating observed behaviours or outward behaviours of learning, while theories of social constructivism place strong emphasis on human development and knowledge construction that is socially situated, with less attention paid to individual differences and variations. In recognizing inherently complex interrelated learning systems, a more integrated and comprehensive understanding of learning is necessary. Such an understanding entails research endeavours that can harness multiple, complex parameters of the learner system through mapping and understanding interactions between and across learning processes and levels. Such endeavours entail the use of multiple sources of scientific evidence, across multi-modal data capture modes and multi-levels of analyses, informed by multi-disciplinary theoretical framings. In this paper, we argue that an overarching scientific ethos towards learning optimizations need artful implementations of pedagogies and interventions that close the circle—from scientific findings translated into practical applications in education and back to addressing problems in education as impetus for evidence-informed theorizations of learning.