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The use of artificial intelligence in psychology

General data

Course ID:	WF-PS-UAIP-ER
Erasmus code / ISCED:	14.4 Kod klasyfikacyjny przedmiotu składa się z trzech do pięciu cyfr, przy czym trzy pierwsze oznaczają klasyfikację dziedziny wg. Listy kodów dziedzin obowiązującej w programie Socrates/Erasmus, czwarta (dotąd na ogół 0) – ewentualne uszczegółowienie informacji o dyscyplinie, piąta – stopień zaawansowania przedmiotu ustalony na podstawie roku studiów, dla którego przedmiot jest przeznaczony. / (0313) Psychology The ISCED (International Standard Classification of Education) code has been designed by UNESCO.
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) Basic information on ECTS credits allocation principles: the annual hourly workload of the student’s work required to achieve the expected learning outcomes for a given stage is 1500-1800h, corresponding to 60 ECTS; the student’s weekly hourly workload is 45 h; 1 ECTS point corresponds to 25-30 hours of student work needed to achieve the assumed learning outcomes; weekly student workload necessary to achieve the assumed learning outcomes allows to obtain 1.5 ECTS; work required to pass the course, which has been assigned 3 ECTS, constitutes 10% of the semester student load. view allocation of credits
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	Selected timetable range: weekly course term Navigate to timetable MO TU W WYK_MON TH FR
Type of class:	Monographic lecture, 30 hours, 20 places more information
Coordinators:	Włodzimierz Strus, 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) 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	Selected timetable range: weekly course term Navigate to timetable MO TU W TH FR WYK_MON
Type of class:	Monographic lecture, 30 hours, 15 places more information
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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