The use of artificial intelligence in psychology
General data
Course ID: | WF-PS-UAIP-ER |
Erasmus code / ISCED: |
14.4
|
Course title: | The use of artificial intelligence in psychology |
Name in Polish: | The use of artificial intelligence in psychology |
Organizational unit: | Institute of Psychology |
Course groups: | |
ECTS credit allocation (and other scores): |
6.00 (differs over time)
|
Language: | English |
Subject level: | intermediate |
Learning outcome code/codes: | PS_W02 PS_W03 PS_K03 |
Short description: |
(in Polish) The course is devoted to the application of artificial intelligence algorithms in psychology. During the course, students learn basic information about artificial intelligence algorithms and get to know with examples of their applications based on documented psychological research in which these algorithms have been used. |
Full description: |
(in Polish) 1. Basic information about artificial intelligence algorithms 2. Decision tree algorithms 3. Quinlan's algorithm and its use in psychology - research examples 4. The regression tree algorithm and its use in psychology - research examples 5. classification trees algorithm and its use in psychology - research examples 6. Artificial neural networks 7. Artificial neural networks and their use in psychology - research examples part. 1 8. Artificial neural networks and their use in psychology - research examples part. 2 9. Other methods of machine learning - support vector machine - research example 10. The apriori algorithm, Market Basket Analysis - an example of use in psychology 11. Text mining algorithms and their use for text analysis 13. Text mining algorithms and their use in psychology - research example of personality traits parents shape in their children 14. Social Network Analysis - application, implementation and use in psychology. Combining SNA with text mining algorithms (on the example of personality traits shaped by parents). 15. colloquium |
Bibliography: |
(in Polish) Basic literature: Elder, J., Hill, T., Miner, G., Nisbet, B., Delen, D., & Fast, A. (2012). Practical Text Mining and Statistical Analysis for Nono-structured Text Data Application. Oxford: Elsevier. Nisbet, R., Elder, J., & Miner, G. (2009). Handbook of statistical analysis and data mining applications. Burlington, MA: Academic Press (Elsevier). |
Efekty kształcenia i opis ECTS: |
(in Polish) KNOWLEDGE: - have knowledge of some research in psychology that was carried out with the use of algorithms, e.g. regarding personality profiles drawn on the basis of activity in post-social networks such as facebook, etc. SKILLS: - students correctly use the terminology of data mining methods, COMPETENCES: understand the principle of their use to analyze data in science Description of ECTS credits Participation in classes: 30 hours Preparation for classes and a test, reading the literature: 30 hours |
Assessment methods and assessment criteria: |
(in Polish) The basis for completing the course is a test of the knowledge acquired during the lecture |
Classes in period "Winter semester 2021/22" (past)
Time span: | 2021-10-01 - 2022-01-31 |
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MO TU W WYK_MON
TH FR |
Type of class: |
Monographic lecture, 30 hours, 20 places
|
|
Coordinators: | Włodzimierz Strus, Agnieszka Szymańska | |
Group instructors: | Agnieszka Szymańska | |
Students list: | (inaccessible to you) | |
Examination: |
Course -
examination
Monographic lecture - examination |
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(in Polish) E-Learning: | (in Polish) E-Learning (pełny kurs) z podziałem na grupy |
|
Type of subject: | optional with unlimited choices |
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(in Polish) Grupa przedmiotów ogólnouczenianych: | (in Polish) nie dotyczy |
|
Short description: |
(in Polish) The course is devoted to the application of artificial intelligence algorithms in psychology. During the course, students learn basic information about artificial intelligence algorithms and get to know with examples of their applications based on documented psychological research in which these algorithms have been used. |
Classes in period "Winter semester 2022/23" (past)
Time span: | 2022-10-01 - 2023-01-31 |
Navigate to timetable
MO TU W TH FR WYK_MON
|
Type of class: |
Monographic lecture, 30 hours, 15 places
|
|
Coordinators: | Jarosław Jastrzębski, Agnieszka Szymańska | |
Group instructors: | Agnieszka Szymańska | |
Students list: | (inaccessible to you) | |
Examination: |
Course -
examination
Monographic lecture - examination |
|
(in Polish) E-Learning: | (in Polish) E-Learning (pełny kurs) z podziałem na grupy |
|
Type of subject: | optional with unlimited choices |
|
(in Polish) Grupa przedmiotów ogólnouczenianych: | (in Polish) PO - przedmioty ogólnouczelniane (bez obszaru) |
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