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Mathematical Psychology

This project investigates mathematical psychology's historical and philosophical foundations to clarify its distinguishing characteristics and relationships to adjacent fields. Through gathering primary sources, histories, and interviews with researchers, author Prof. Colin Allen - University of Pittsburgh [1, 2, 3] and his students  Osman Attah, Brendan Fleig-Goldstein, Mara McGuire, and Dzintra Ullis have identified three central questions: 

  1. What makes the use of mathematics in mathematical psychology reasonably effective, in contrast to other sciences like physics-inspired mathematical biology or symbolic cognitive science? 
  2. How does the mathematical approach in mathematical psychology differ from other branches of psychology, like psychophysics and psychometrics? 
  3. What is the appropriate relationship of mathematical psychology to cognitive science, given diverging perspectives on aligning with this field? 

Preliminary findings emphasize data-driven modeling, skepticism of cognitive science alignments, and early reliance on computation. They will further probe the interplay with cognitive neuroscience and contrast rational-analysis approaches. By elucidating the motivating perspectives and objectives of different eras in mathematical psychology's development, they aim to understand its past and inform constructive dialogue on its philosophical foundations and future directions. This project intends to provide a conceptual roadmap for the field through integrated history and philosophy of science.



The Project: Integrating History and Philosophy of Mathematical Psychology



This project aims to integrate historical and philosophical perspectives to elucidate the foundations of mathematical psychology. As Norwood Hanson stated, history without philosophy is blind, while philosophy without history is empty. The goal is to find a middle ground between the contextual focus of history and the conceptual focus of philosophy.


The team acknowledges that all historical accounts are imperfect, but some can provide valuable insights. The history of mathematical psychology is difficult to tell without centering on the influential Stanford group. Tracing academic lineages and key events includes part of the picture, but more context is needed to fully understand the field's development.


The project draws on diverse sources, including research interviews, retrospective articles, formal histories, and online materials. More interviews and research will further flesh out the historical and philosophical foundations. While incomplete, the current analysis aims to identify important themes, contrasts, and questions that shaped mathematical psychology's evolution. Ultimately, the goal is an integrated historical and conceptual roadmap to inform contemporary perspectives on the field's identity and future directions.



The Rise of Mathematical Psychology



The history of efforts to mathematize psychology traces back to the quantitative imperative stemming from the Galilean scientific revolution. This imprinted the notion that proper science requires mathematics, leading to "physics envy" in other disciplines like psychology.


Many early psychologists argued psychology needed to become mathematical to be scientific. However, mathematizing psychology faced complications absent in the physical sciences. Objects in psychology were not readily present as quantifiable, provoking heated debates on whether psychometric and psychophysical measurements were meaningful.


Nonetheless, the desire to develop mathematical psychology persisted. Different approaches grappled with determining the appropriate role of mathematics in relation to psychological experiments and data. For example, Herbart favored starting with mathematics to ensure accuracy, while Fechner insisted experiments must come first to ground mathematics.


Tensions remain between data-driven versus theory-driven mathematization of psychology. Contemporary perspectives range from psychometric and psychophysical stances that foreground data to measurement-theoretical and computational approaches that emphasize formal models.


Elucidating how psychologists negotiated to apply mathematical methods to an apparently resistant subject matter helps reveal the evolving role and place of mathematics in psychology. This historical interplay shaped the emergence of mathematical psychology as a field.



The Distinctive Mathematical Approach of Mathematical Psychology



What sets mathematical psychology apart from other branches of psychology in its use of mathematics?


Several key aspects stand out:

  1. Advocating quantitative methods broadly. Mathematical psychology emerged partly to push psychology to embrace quantitative modeling and mathematics beyond basic statistics.
  2. Drawing from diverse mathematical tools. With greater training in mathematics, mathematical psychologists utilize more advanced and varied mathematical techniques like topology and differential geometry.
  3. Linking models and experiments. Mathematical psychologists emphasize tightly connecting experimental design and statistical analysis, with experiments created to test specific models.
  4. Favoring theoretical models. Mathematical psychology incorporates "pure" mathematical results and prefers analytic, hand-fitted models over data-driven computer models.
  5. Seeking general, cumulative theory. Unlike just describing data, mathematical psychology aspires to abstract, general theory supported across experiments, cumulative progress in models, and mathematical insight into psychological mechanisms.


So while not unique to mathematical psychology, these key elements help characterize how its use of mathematics diverges from adjacent fields like psychophysics and psychometrics. Mathematical psychology carved out an identity embracing quantitative methods but also theoretical depth and broad generalization.



Situating Mathematical Psychology Relative to Cognitive Science



What is the appropriate perspective on mathematical psychology's relationship to cognitive psychology and cognitive science? While connected historically and conceptually, essential distinctions exist.


Mathematical psychology draws from diverse disciplines that are also influential in cognitive science, like computer science, psychology, linguistics, and neuroscience. However, mathematical psychology appears more skeptical of alignments with cognitive science.


For example, cognitive science prominently adopted the computer as a model of the human mind, while mathematical psychology focused more narrowly on computers as modeling tools.


Additionally, mathematical psychology seems to take a more critical stance towards purely simulation-based modeling in cognitive science, instead emphasizing iterative modeling tightly linked to experimentation.


Overall, mathematical psychology exhibits significant overlap with cognitive science but strongly asserts its distinct mathematical orientation and modeling perspectives. Elucidating this complex relationship remains an ongoing project, but preliminary analysis suggests mathematical psychology intentionally diverged from cognitive science in its formative development.


This establishes mathematical psychology's separate identity while retaining connections to adjacent disciplines at the intersection of mathematics, psychology, and computation.



Looking Ahead: Open Questions and Future Research



This historical and conceptual analysis of mathematical psychology's foundations has illuminated key themes, contrasts, and questions that shaped the field's development. Further research can build on these preliminary findings.

Additional work is needed to flesh out the fuller intellectual, social, and political context driving the evolution of mathematical psychology. Examining the influences and reactions of key figures will provide a richer picture.

Ongoing investigation can probe whether the identified tensions and contrasts represent historical artifacts or still animate contemporary debates. Do mathematical psychologists today grapple with similar questions on the role of mathematics and modeling?

Further analysis should also elucidate the nature of the purported bidirectional relationship between modeling and experimentation in mathematical psychology. As well, clarifying the diversity of perspectives on goals like generality, abstraction, and cumulative theory-building would be valuable.

Finally, this research aims to spur discussion on philosophical issues such as realism, pluralism, and progress in mathematical psychology models. Is the accuracy and truth value of models an important consideration or mainly beside the point? And where is the field headed - towards greater verisimilitude or an indefinite balancing of complexity and abstraction?

By spurring reflection on this conceptual foundation, this historical and integrative analysis hopes to provide a roadmap to inform constructive dialogue on mathematical psychology's identity and future trajectory.


The SDTEST® 



The SDTEST® is a simple and fun tool to uncover our unique motivational values that use mathematical psychology of varying complexity.



The SDTEST® helps us better understand ourselves and others on this lifelong path of self-discovery.


Here are reports of polls which SDTEST® makes:


1) गेल्या महिन्यात कर्मचार्‍यांच्या संबंधात कंपन्यांच्या कृती (होय / नाही)

2) गेल्या महिन्यात कर्मचार्यांच्या संबंधात कंपन्यांच्या कारवाई (% मध्ये तथ्य)

3) भय

4) माझ्या देशासमोरील सर्वात मोठ्या समस्या

5) यशस्वी संघ तयार करताना चांगले नेते कोणते गुण आणि क्षमता वापरतात?

6) गूगल. कार्यसंघाच्या कार्यक्षमतेवर परिणाम करणारे घटक

7) नोकरी शोधणा of ्यांची मुख्य प्राथमिकता

8) बॉसला एक महान नेता काय बनवते?

9) लोकांना कामावर यशस्वी काय करते?

10) आपण दूरस्थपणे काम करण्यासाठी कमी वेतन मिळण्यास तयार आहात?

11) एजिझम अस्तित्वात आहे का?

12) करिअरमधील वयवाद

13) जीवनात वयवाद

14) वयवादाची कारणे

15) लोक का सोडून देतात याची कारणे (अण्णा व्हिटल द्वारे)

16) विश्वास (#WVS)

17) ऑक्सफोर्ड आनंद सर्वेक्षण

18) मानसशास्त्रीय कल्याण

19) आपली पुढील सर्वात रोमांचक संधी कोठे असेल?

20) आपल्या मानसिक आरोग्याची काळजी घेण्यासाठी आपण या आठवड्यात काय कराल?

21) मी माझ्या भूतकाळाबद्दल, वर्तमान किंवा भविष्याबद्दल विचार करतो

22) गुणवत्ता

23) कृत्रिम बुद्धिमत्ता आणि सभ्यतेचा शेवट

24) लोक विलंब का करतात?

25) आत्मविश्वास वाढविण्यात लिंग फरक (आयएफडी le लेन्सबॅच)

26) Xing.com संस्कृती मूल्यांकन

27) पॅट्रिक लेन्सिओनीचे "संघाचे पाच बिघडलेले कार्य"

28) सहानुभूती आहे ...

29) नोकरीची ऑफर निवडण्यात आयटी तज्ञांसाठी काय आवश्यक आहे?

30) लोक बदलांचा प्रतिकार का करतात (सिओबॉन मॅकहेल यांनी)

31) आपण आपल्या भावनांचे नियमन कसे करता? (नवल मुस्तफा एम.ए. द्वारा)

32) 21 आपल्याला कायमचे देय देणारी कौशल्ये (यिर्मया टीओ / 赵汉昇)

33) वास्तविक स्वातंत्र्य आहे ...

34) इतरांवर विश्वास वाढवण्याचे 12 मार्ग (जस्टिन राइटद्वारे)

35) प्रतिभावान कर्मचार्‍यांची वैशिष्ट्ये (प्रतिभा व्यवस्थापन संस्थेद्वारे)

36) आपल्या कार्यसंघास प्रवृत्त करण्यासाठी 10 की

37) विवेकाचे बीजगणित (व्लादिमीर लेफेब्रे द्वारे)

38) भविष्यातील तीन भिन्न शक्यता (डॉ. क्लेअर डब्ल्यू. ग्रेव्हज द्वारे)

39) अतुलनीय आत्म-विश्वास निर्माण करण्यासाठी कृती (सुरेन समर्चायन द्वारे)

40)


Below you can read an abridged version of the results of our VUCA poll “Fears“. The full version of the results is available for free in the FAQ section after login or registration.

भय

देश
इंग्रजी
-
Mail
पुन्हा गणना
सहसंबंध गुणाकाचा गंभीर मूल्य
विल्यम सीली गॉसेट (विद्यार्थी) द्वारे सामान्य वितरण r = 0.0317
विल्यम सीली गॉसेट (विद्यार्थी) द्वारे सामान्य वितरण r = 0.0317
स्पीयरमॅनद्वारे सामान्य वितरण r = 0.0013
वितरणसामान्य
नाही
सामान्य
नाही
सामान्य
नाही
सामान्यसामान्यसामान्यसामान्यसामान्य
सर्व प्रश्न
सर्व प्रश्न
माझे सर्वात मोठे भय आहे
माझे सर्वात मोठे भय आहे
Answer 1-
कमकुवत सकारात्मक
0.0537
कमकुवत सकारात्मक
0.0288
कमकुवत नकारात्मक
-0.0175
कमकुवत सकारात्मक
0.0948
कमकुवत सकारात्मक
0.0381
कमकुवत नकारात्मक
-0.0178
कमकुवत नकारात्मक
-0.1563
Answer 2-
कमकुवत सकारात्मक
0.0194
कमकुवत नकारात्मक
-0.0048
कमकुवत नकारात्मक
-0.0385
कमकुवत सकारात्मक
0.0655
कमकुवत सकारात्मक
0.0495
कमकुवत सकारात्मक
0.0106
कमकुवत नकारात्मक
-0.0982
Answer 3-
कमकुवत नकारात्मक
-0.0001
कमकुवत नकारात्मक
-0.0084
कमकुवत नकारात्मक
-0.0449
कमकुवत नकारात्मक
-0.0445
कमकुवत सकारात्मक
0.0485
कमकुवत सकारात्मक
0.0742
कमकुवत नकारात्मक
-0.0207
Answer 4-
कमकुवत सकारात्मक
0.0433
कमकुवत सकारात्मक
0.0291
कमकुवत नकारात्मक
-0.0232
कमकुवत सकारात्मक
0.0163
कमकुवत सकारात्मक
0.0367
कमकुवत सकारात्मक
0.0226
कमकुवत नकारात्मक
-0.0996
Answer 5-
कमकुवत सकारात्मक
0.0277
कमकुवत सकारात्मक
0.1291
कमकुवत सकारात्मक
0.0108
कमकुवत सकारात्मक
0.0745
कमकुवत सकारात्मक
0.0012
कमकुवत नकारात्मक
-0.0177
कमकुवत नकारात्मक
-0.1783
Answer 6-
कमकुवत नकारात्मक
-0.0015
कमकुवत सकारात्मक
0.0058
कमकुवत नकारात्मक
-0.0607
कमकुवत नकारात्मक
-0.0094
कमकुवत सकारात्मक
0.0255
कमकुवत सकारात्मक
0.0844
कमकुवत नकारात्मक
-0.0363
Answer 7-
कमकुवत सकारात्मक
0.0113
कमकुवत सकारात्मक
0.0348
कमकुवत नकारात्मक
-0.0657
कमकुवत नकारात्मक
-0.0305
कमकुवत सकारात्मक
0.0521
कमकुवत सकारात्मक
0.0686
कमकुवत नकारात्मक
-0.0532
Answer 8-
कमकुवत सकारात्मक
0.0657
कमकुवत सकारात्मक
0.0728
कमकुवत नकारात्मक
-0.0255
कमकुवत सकारात्मक
0.0124
कमकुवत सकारात्मक
0.0386
कमकुवत सकारात्मक
0.0153
कमकुवत नकारात्मक
-0.1345
Answer 9-
कमकुवत सकारात्मक
0.0757
कमकुवत सकारात्मक
0.1605
कमकुवत सकारात्मक
0.0066
कमकुवत सकारात्मक
0.0612
कमकुवत नकारात्मक
-0.0063
कमकुवत नकारात्मक
-0.0492
कमकुवत नकारात्मक
-0.1822
Answer 10-
कमकुवत सकारात्मक
0.0764
कमकुवत सकारात्मक
0.0669
कमकुवत नकारात्मक
-0.0124
कमकुवत सकारात्मक
0.0271
कमकुवत सकारात्मक
0.0365
कमकुवत नकारात्मक
-0.0130
कमकुवत नकारात्मक
-0.1348
Answer 11-
कमकुवत सकारात्मक
0.0634
कमकुवत सकारात्मक
0.0526
कमकुवत नकारात्मक
-0.0075
कमकुवत सकारात्मक
0.0096
कमकुवत सकारात्मक
0.0264
कमकुवत सकारात्मक
0.0242
कमकुवत नकारात्मक
-0.1270
Answer 12-
कमकुवत सकारात्मक
0.0450
कमकुवत सकारात्मक
0.0944
कमकुवत नकारात्मक
-0.0323
कमकुवत सकारात्मक
0.0307
कमकुवत सकारात्मक
0.0343
कमकुवत सकारात्मक
0.0260
कमकुवत नकारात्मक
-0.1530
Answer 13-
कमकुवत सकारात्मक
0.0725
कमकुवत सकारात्मक
0.0947
कमकुवत नकारात्मक
-0.0389
कमकुवत सकारात्मक
0.0265
कमकुवत सकारात्मक
0.0443
कमकुवत सकारात्मक
0.0144
कमकुवत नकारात्मक
-0.1631
Answer 14-
कमकुवत सकारात्मक
0.0820
कमकुवत सकारात्मक
0.0897
कमकुवत नकारात्मक
-0.0030
कमकुवत नकारात्मक
-0.0122
कमकुवत सकारात्मक
0.0060
कमकुवत सकारात्मक
0.0135
कमकुवत नकारात्मक
-0.1213
Answer 15-
कमकुवत सकारात्मक
0.0549
कमकुवत सकारात्मक
0.1265
कमकुवत नकारात्मक
-0.0334
कमकुवत सकारात्मक
0.0119
कमकुवत नकारात्मक
-0.0153
कमकुवत सकारात्मक
0.0242
कमकुवत नकारात्मक
-0.1157
Answer 16-
कमकुवत सकारात्मक
0.0732
कमकुवत सकारात्मक
0.0242
कमकुवत नकारात्मक
-0.0373
कमकुवत नकारात्मक
-0.0398
कमकुवत सकारात्मक
0.0729
कमकुवत सकारात्मक
0.0169
कमकुवत नकारात्मक
-0.0774


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[1] https://twitter.com/wileyprof
[2] https://colinallen.dnsalias.org
[3] https://philpeople.org/profiles/colin-allen

2023.10.13
वलेरी कोसेन्को
उत्पादन मालक SaaS SDTEST®

व्हॅलेरी 1993 मध्ये सामाजिक अध्यापनशास्त्र-मानसशास्त्रज्ञ म्हणून पात्र होते आणि तेव्हापासून त्यांनी प्रकल्प व्यवस्थापनात त्यांचे ज्ञान लागू केले.
व्हॅलेरीने 2013 मध्ये पदव्युत्तर पदवी आणि प्रकल्प आणि कार्यक्रम व्यवस्थापक पात्रता प्राप्त केली. त्याच्या पदव्युत्तर कार्यक्रमादरम्यान, तो प्रोजेक्ट रोडमॅप (GPM Deutsche Gesellschaft für Projektmanagement e. V.) आणि स्पायरल डायनॅमिक्सशी परिचित झाला.
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नमस्कार! मला विचारू द्या, आपण आधीपासूनच आवर्त गतिशीलतेशी परिचित आहात?