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    題名: 構成類別學習中知識分化現象的極限條件：以離散向度類別結構為例
    The boundary condition of knowledge partitioning in categorization: category structure with discrete dimensions
    作者: 張軒
    Chang, Hsuan
    貢獻者: 楊立行
    Yang, Lee-Xieng
    張軒
    Chang, Hsuan
    關鍵詞: 知識分化
    歸納推理
    概念習得
    日期: 2019
    上傳時間: 2019-08-07 16:32:57 (UTC+8)
    摘要: 過去許多研究專注於了解在不同情境下人們做出的不同決定或判斷（Labov，1973，Roth 與 Shoben，1983；Bailenson 等人，2002），也有許多研究指出在包括函式學習、類別學習等認知作業中人們的學習與判斷會受到情境所影響（Lewandowsky 與 Kirsner，2000；Lewandowsky、Kalish 與 Ngang，2002；Yang 與 Lewandowsky，2003）。這種受到情境影響認知作業的現象被稱作知識分化。本研究的目的在探討使用非連續向度的實驗素材進行概念學習時是否也可以發現知識分化的現象。本研究的三個實驗皆以以離散向度作為特徵值的卡片為實驗材料，並要求實驗參與者歸納出卡片的規則。實驗一發現作為情境線索的卡片位置影響了實驗參與者的判斷，實驗二以及實驗三則發現作為情境線索的卡片圖案形狀也對判斷造成影響。結果顯示使用離散向度的實驗素材也可以觀察到知識分化。
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    描述: 碩士
    國立政治大學
    心理學系
    104752010
    資料來源: http://thesis.lib.nccu.edu.tw/record/#G0104752010
    資料類型: thesis
    DOI: 10.6814/NCCU201900646
    顯示於類別:[心理學系] 學位論文

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