初探影響科學學習的先天因子(III)
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Date
2013-09-30
Authors
張俊彥
葉庭光
張月霞
李柏磊
胡忠怡
李銘仁
Journal Title
Journal ISSN
Volume Title
Publisher
行政院國家科學委員會
Abstract
近年來，基因體學與神經科學研究的突破，提供認知科學與教育學者有更佳的機會探 索學習的內在機制。若我們能充分了解學習行為的內在機制，我們將可以提供學習者最 佳的學習方式與策略。為了充分瞭解與掌控學習和行為背後的相關機制，本研究將結合 科學教育、認知心理學、神經科學、基因體學、以及資訊科學/系統生物學不同領域的研 究者共同合作。研究重心著重於兩部分：一為探索變項，透過跨領域整合與技術，廣泛 探索影響學習的變項，包括基因資訊、大腦各腦區結構、大腦灰質與白質密度/厚度、各 種影響學習的認知能力、以及學習成效等；接著，我們將透過資訊科學/系統生物學的演 算與統計，試著從複雜的資訊中，找到影響學習的路徑/機制。我們亦考慮依據找到的學 習機制，嘗試設計適性化的課程或教學模組，初步探討這樣的課程內容設計及教學策略 是否對於學習者能有所助益。我們希望透過本跨領域的研究計畫，初步瞭解先天因子在 學習上的相關性及其可能的相互影響，以幫助科學家共同探索心智的「黑盒子」。
In the past decade, genetic and neuroscience research has provided some of the most exciting breakthroughs for cognitive science and education. In our opinion, integration of multiple disciplines (education, cognitive psychology, neuroscience, and molecular biology; ECNG) can serve to inform researchers in different areas in terms of furthering their own research and deriving meaningful thoughts/implications and practice for learning sciences, rather than merely provide a powerful means for exploring the mechanism of human behavior. This interdisciplinary research project aims to integrate researchers in different area to explore mechanisms of learning. With the aim to establish the possible pathway/mechanism of learning, we will try to collect diverse information related to ECNG network systems, such as types of genomes, functions of proteins, brain structure, cognitive abilities, and academic performance. Furthermore, we will endeavor to design different algorithms leveraging on systems biology methodology for predicting learning mechanisms/pathways. According to the learning mechanism, we will also try to develop adaptive instructing models or strategies for better assisting/matching students’ learning potentials. Our profound hope is to integrate researchers in different fields in order to explore the mechanism of learning and provide concrete evidence of ways in which students＇ learning can be improved.
In the past decade, genetic and neuroscience research has provided some of the most exciting breakthroughs for cognitive science and education. In our opinion, integration of multiple disciplines (education, cognitive psychology, neuroscience, and molecular biology; ECNG) can serve to inform researchers in different areas in terms of furthering their own research and deriving meaningful thoughts/implications and practice for learning sciences, rather than merely provide a powerful means for exploring the mechanism of human behavior. This interdisciplinary research project aims to integrate researchers in different area to explore mechanisms of learning. With the aim to establish the possible pathway/mechanism of learning, we will try to collect diverse information related to ECNG network systems, such as types of genomes, functions of proteins, brain structure, cognitive abilities, and academic performance. Furthermore, we will endeavor to design different algorithms leveraging on systems biology methodology for predicting learning mechanisms/pathways. According to the learning mechanism, we will also try to develop adaptive instructing models or strategies for better assisting/matching students’ learning potentials. Our profound hope is to integrate researchers in different fields in order to explore the mechanism of learning and provide concrete evidence of ways in which students＇ learning can be improved.