臺灣博碩士論文加值系統

本研究基於Flavell（1979）、Nelson 與Narens（1990, 1994）的後設認知理論，應用Winne與Hadwin（1998）的自我調整學習模式（model of self-regulation）中的「評估標準」和「認知評價」以及Schraw（2009）提出的絕對準確指標（Absolute accuracy index）計算自我評估的準確度。延伸Dunlosky, Hartwig , Rawson 與 Lipko（2011）的實驗設計，以53位大學理工科，但非物理、化學本科系、非電子類科的學生為研究對象。其中，控制組有26位受試者，不介入任何教學；另外27位為實驗組，介入拆解概念單元方法的教學，請受試者自己拆解概念單元作為閱讀標準（即確認重要概念的依據），研究大學生以「拆解概念單元為閱讀標準」學習科學文本時的閱讀理解程度與自評準確度是否提升。分析實驗組，其閱讀理解後測（包含定義題和簡答題）的成績和自我評估準確度是否優於控制組？實驗組概念單元拆解技巧的學習和應用狀況是否會影響各項成績表現？結果顯示：在定義題方面，實驗組閱讀理解後測的成績以及自我評估準確度都顯著優於控制組。簡答題方面，實驗組成績略優於控制組，但是未達顯著；實驗組在簡答題的自我評估準確度與控制組也沒有顯著差異。另外，相關分析顯示：概念單元的拆解技巧學得越好，越能在作答或自我評估的時候應用概念單元的理念，閱讀理解後測的成績（包含：定義題和簡答題）也越好，定義題的自我評估準確度也越高；有應用概念單元作答，則定義題的總成績和自我評估準確度都比較高；有應用概念單元進行自我評分，則自我評估準確度都較高（包含定義題和簡答題）。

Based on the metacognition theories of Flavell (1979), Nelson and Narens (1990, 1994), this study adopted the “evaluation standards” and “cognitive evaluation” in the “model of self-regulation” developed by Winne and Hadwin (1998) and ”Absolute Accuracy Index“ developed by Schraw (2009). Extending the experimental design of Dunlosky, Hartwig, Rawson, and Lipko (2011), fifty-three college students were recruited from Science and Engineering Departments, excluding those who major in Physics, Chemistry, and Electronic Engineering. The experimental group (n = 27) was instructed to learn from a scientific text with “self-generated idea unit standards”. The procedure of the experimental group started with an instruction of dividing each concept into several idea units, then the students themselves generated the idea units as a reading standard (i.e., the basis for ensuring conceptual understanding). The control group (n = 26) read the scientific text without any instruction. This study investigated whether reading comprehension (assessed by definition and short-answer questions) and calibration accuracy would be improved by generating idea units as a reading standard for the scientific text. The results showed that for definition questions, reading comprehension and calibration accuracy of the experimental group were significantly better than that of the control group. Concerning the short-answer questions, the experimental group performed slightly better than the control group, but the difference was not statistically significant. There was no significant difference in calibration accuracy between the experimental and the control groups. In addition, correlational analyses showed that with better skill to generate idea units during the instruction, these participants were more likely to apply the skill in the post-test and self-judgment, had better post-test scores and more accurate judgment.

摘要--i
ABSTRACT--ii
目錄--iii
圖次--v
表次--vi

第一章　緒論--1
第一節　研究背景與研究動機--1
第二節　研究目的與研究問題--2
第三節　名詞解釋--2
第四節　研究限制--3

第二章　文獻探討--4
第一節　後設認知的理論架構--4
第二節　後設認知判斷和校準準確度--9
第三節　Dunlosky 與 Rawson 等學者對自我評估準確度及概念單元評估標準（idea unit standards）的研究--13

第三章　研究方法--17
第一節　研究對象--17
第二節　研究設計--17
第三節　研究流程--18
第四節　研究工具--21

第四章　研究結果與討論--37
第一節　組別和學習效果的關係--37
第二節　組別和不同題型成績的關係--38
第三節　組別和不同題型自我評估準確度的關係--39
第四節　拆解概念單元技巧的學習及其應用（在作答或自我評估）狀況--40
第五節　拆解概念單元技巧的學習及其應用狀況與測驗成績、自我評估準確度以及科學閱讀自我調整學習策略的相關性--43
第六節　以「概念單元為閱讀標準」的閱讀方式對受試者的幫助 及使用上的困難--45
第七節　分析實驗組和控制組在閱讀理解測驗後測中 各小題的答題表現--47
第八節　討論--51

第五章　結論與建議--53
第一節　結論--53
第二節　建議--53

參考文獻--55
附錄--57

中文文獻

高琦玲、黃明月與陳學志（2007）。後設認知的監測判斷。德霖學報，21，425-434。

英文文獻
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Dunlosky, J., Rawson, K. A., & Middleton, E. L. (2005). What constrains the accuracy of metacomprehension judgments? Testing the transfer-appropriate-monitoring and accessibility hypotheses. Journal of Memory and Language, 52, 551-565.

Dunlosky, J., Hartwig, M.K., Rawson, K.A., & Lipko, A.R. (2011). Improving college students’ evaluation of text learning using idea-unit standards. The Quarterly Journal of Experimental Psychology, 64(3), 467-484.

Flavell, J. H. (1963). The developmental psychology of Jean Piaget. Princeton, NJ, US: D Van Nostrand.

Flavell, J. H. (1976). Metacognitive aspects of problem solving. In L. B. Resnick, (Ed.), The nature of intelligence (pp. 231-235). Hillsdale, NJ: Lawrence Erlbaum.

Lipko, A.R., Dunlosky, J., Hartwig, M.K., Rawson,K.A., Swan,K., & Dale,C. (2009). Using standards to improve middle school students’ accuracy at evaluating the quality of their recall. Journal of Experimental Psychology: Applied, 15(4), 307-318.

Metcalfe, J., & Kornell, N. (2005). A Region of Proximal Learning model of study time allocation. Journal of Memory and Language ,52, 463-477.

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Nelson, T. O., & Narens, L. (1990). Metamemory: A theoretical framework and new finding. In G.H. Bower (Ed.), The psychology of learning and motivation, 26, (pp.125-141). New York: Academic Press.

Nelson, T. O. (1992). Metacognition: Core readings. Needham Heights, MA, US: Allyn & Bacon.

Nelson, T. O., & Narens, L. (1994). Why investigate metacognition? In J. Metcalfe & A. P. Shimamura (Eds.), Metacognition: Knowing about knowing (pp. 1-25). Cambridge, MA: MIT Press.

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Nordén, B., & Krutmeijer, E. (2000). The Nobel Prize in Chemistry, 2000: Conductive Polymers, Kungl. Vetenskapsakademien (The Royal Swedish Academy of Sciences), 1, p.9-10.

Rawson, K.A., & Dunlosky, J. (2007). Improving students’ self-evaluation of learning for key concepts in textbook materials. European journal of cognitive psychology, 19(4/5), 559-579.

Schraw, G. (2009). Measuring metacognitive judgments. In D. J. Hacker, J. Dunlosky, & A. C. Graesser (Eds.). Handbook of metacognition in education (pp. 415-429).NY: Routledge.

Winne, P. H. (1995a). Inherent details in self-regulated learning. Educational Psychologist, 30, 173-187.

Winne, P. H. (1995b). Self-regulation is ubiquitous but its forms vary with knowledge. EducationalPsychologist, 30, 223-228.

Winne, P. H. (1996). A metacognitive view of individual differences in self-regulated learning. Learning and Individual Differences, 8, 327-353.

Winne, P. H., & Hadwin, A. F. (1998). Studying as self-regulated learning. In D. J. Hacker, J. Dunlosky,& A. C. Graesser (Eds.), Metacognition in educational theory and practice (pp. 277-304). Mahwah, NJ: Erlbaum.

Winne, P. H. (2004). Students’ calibration of knowledge and learning processes: Implications for designing powerful software learning environments. International Journal of Educational Research, 41, 466-88.