實驗心理學的整合科學史與科學哲學

Integrated History and Philosophy of Experimental Psychology

學期

114-2

學分

3 學分

當期課號

133104

永久課號

HSPH30014

開課單位

心智哲學研究所

授課教師

嚴如玉

校區

陽明

類別

必修

上課時間表

節	週三
6 14:20–15:10	實驗心理學的整合科學史與科學哲學 YX321 3 節連堂
7 15:30–16:20
8 16:30–17:20

* 根據陽明交大上課時間表所列

概述

Course descriptions: This graduate seminar offers a rigorous examination of experimental psychology through the dual lenses of history and philosophy of science. We will trace the evolution of experimental psychology from its late-19th century foundations to contemporary computational and neuroscientific approaches, situating methodological developments within broader philosophical debates about scientific explanation, scientific realism, operational definitions, mental representation, and mechanistic modeling. Students will learn to analyze the epistemic aims, conceptual frameworks, and methodological commitments of experimental psychology using tools from both the history of science and the philosophy of science and mind. Through engagement with scientometric datasets (1979–2025) and co-citation analysis, participants will investigate how experimental psychology’s research programs have evolved, interacted, and diversified over time. The course emphasizes critical reflection on the normative and epistemological dimensions of psychological research, including the role of theory-ladenness, interdisciplinarity, and ethical considerations in shaping experimental practice. By the end of the seminar, students will be equipped to articulate philosophically informed assessments of experimental psychology’s conceptual foundations, empirical methods, and trajectory as a scientific discipline. Course objectives: Understand the historical development of experimental psychology. Examine major experimental methodologies and their philosophical underpinnings. Explore the interaction between psychological theory, experimental methods, philosophy of science, and philosophy of mind Critically analyze the ethical, social, and epistemological challenges in experimental psychology

先修科目

本課程預設同學需對實驗心理學實作細節有相當程度的理解與掌握，若不足，將無法滿足本課程的課程學習目標與報告要求。因此，欲修習此課程同學，須經授課教師評估是否具備相關實驗心理學背景，經授課教師確認後具備相關背景，方可修此課程。未經教師評估是否具備相關背景或者經評估後相關背景不足者，請退選此課程。請於選課前寄信至karenyan@nycu.edu.tw與老師約評估時間。

評分方式

1.Homework and Assignments, Exams and Quizzes, Evaluation and Grading Policy: AI Deep Research Reports 10%*3=30% Reconstructing Argument Exercise 10%*3=30% Data-Analysis Reports 10%*3 =30% Class Participation 10% Please arrive on time for each class and submit any time-off requests in advance through the 請假系統. Failure to do so may result in a grade penalty.

週次計畫

週次	主題
第 1 週	Introduction to a novel approach to the integrated history and philosophy of science 參考資料： 1. Yan, K., Tsai, M, and Huang, T. (2023). A Scientometric Approach to the Integrated History and Philosophy of Science: Entrenched Biomedical Standardization and Citation-Exemplar. International Studies in the Philosophy of Science (History and Philosophy of Science field, 39/106, Q2, 2022) (Free eprints) (Preprint) 2. Yan, K. and Liao, C. (2023). A Co-Citation Analysis of Cross-Disciplinarity in the Empirically-Informed Philosophy of Mind. Synthese 201, 159. (History and Philosophy of Science field, 5/106, Q1, 2022). https://doi.org/10.1007/s11229-023-04146-x (Preprint). 3. Yan, K., Tsai, M, and Huang, T. (2021). Improving the Quality of Case-Based Research in the Philosophy of Contemporary Sciences. Synthese, 198, 9591–9610 (History and Philosophy of Science field, 2/106, Q1, 2020). https://doi.org/10.1007/s11229-020-02657-5 (pdf). 4. Yan, K., Tsai, M., and Huang, T. (2022). Integrating Scientonomy with Scientometrics. In Hakob, B. Patton, P. Rupik, G. and Shaw, J. (Eds.) Scientonomy: The Challenges of Constructing a Theory of Scientific Change (pp. 67-82). Vernon Press. https://vernonpress.com/book/1366 (pdf). 5. 嚴如玉 (2022)。〈跨領域哲學〉，《華文哲學百科》（2022 版本），王一奇（編）。URL=http://mephilosophy.ccu.edu.tw/entry.php?entry_name=跨領域哲學。
第 2 週	Co-Citation Analysis Introduction to co-citation analysis How to retrieve bibliographical data from Web of Science database Introducing the literature dataset of experimental psychology from 1979 to 2025
第 3 週	Operationalism https://plato.stanford.edu/entries/operationalism/ AI Deep Research Report 1
第 4 週	Progress in Psychology https://drive.google.com/drive/folders/1bl7mXRwTnSkDxlBrEWaao3S17ptYg_wc?usp=sharing Reconstructing Argument Exercise 1 Uljana Feest’s Work https://philpapers.org/s/Uljana%20Feest Feest, U. (2020). Construct Validity in Psychological Tests ? The Case of Implicit Social Cognition. European Journal for Philosophy of Science, 10 (1), 1–24. https://doi.org/10.1007/s13194-019-0270-8
第 5 週	Mental Representation & The Computational Theory of Mind https://plato.stanford.edu/entries/mental-representation/ https://plato.stanford.edu/entries/computational-mind/ https://plato.stanford.edu/archives/win2023/entries/cognitive-science/ AI Deep Research Report 2
第 6 週	Mechanisms in Science https://plato.stanford.edu/entries/science-mechanisms/ Wessinger, C. M., & Clapham, E. (2009). Cognitive Neuroscience: An Overview. In L. R. Squire (Ed.), Encyclopedia of Neuroscience (pp. 1117–1122). Academic Press. https://doi.org/10.1016/B978-008045046-9.00299-0 McClelland, J. L. (2001). Cognitive Neuroscience. In N. J. Smelser & P. B. Baltes (Eds.), International Encyclopedia of the Social & Behavioral Sciences (pp. 2133–2140). Pergamon. https://doi.org/10.1016/B0-08-043076-7/03406-9 Kriegeskorte, N., & Douglas, P. K. (2018). Cognitive computational neuroscience. Nature Neuroscience, 21(9), 1148. https://doi.org/10.1038/s41593-018-0210-5 Subramanian, A., Chitlangia, S., & Baths, V. (2022). Reinforcement learning and its connections with neuroscience and psychology. Neural Networks, 145, 271–287. https://doi.org/10.1016/j.neunet.2021.10.003 AI Deep Research Report 3
第 7 週	Chen, R.-L. (2018). Experimental Individuation: Creation and Presentation. In O. Bueno, R.-L. Chen, & M. B. Fagan (Eds.), Individuation, Process, and Scientific Practices (p. 0). Oxford University Press. https://doi.org/10.1093/oso/9780190636814.003.0009 Chen, RL., Hricko, J. Experimental individuation and philosophical retail arguments. Synthese 198, 2313–2332 (2021). https://doi.org/10.1007/s11229-019-02207-8 Reconstructing Argument Exercise 2
第 8 週	How to apply quantitative tools and philosophical conceptual tools to the literature of large-scale brain network Yan, K., & Hricko, J. (2017). Brain networks, structural realism, and local approaches to the scientific realism debate. Studies in History and Philosophy of Biological and Biomedical Sciences, 64, 1–10. https://doi.org/10.1016/j.shpsc.2017.05.001 Reconstructing Argument Exercise 3
第 9 週	How to apply quantitative tools and philosophical conceptual tools to the literature of large-scale brain network
第 10 週	How to apply quantitative tools and philosophical conceptual tools to the literature of large-scale brain network
第 11 週	Integrated History and Philosophy of Science Analysis Part I (1979-1990)
第 12 週	Integrated History and Philosophy of Science Analysis Part II (1991-2000)
第 13 週	Integrated History and Philosophy of Science Analysis Part III (2001-2010) Data-Analysis Report Draft workshop 1
第 14 週	Integrated History and Philosophy of Science Analysis Part IV (2011-2020) Data-Analysis Report Draft workshop 2
第 15 週	Integrated History and Philosophy of Science Analysis Part V (2021-2025) Data-Analysis Report Draft workshop 3
第 16 週	Submission Deadline Data-Analysis Reports 1-3

Office Hours

地點: By Appointment
時間: By Appointment
聯絡方式: karenyan@nycu.edu.tw