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200109 SE Anwendungsseminar: Geist und Gehirn (2021S)
Programming psychological experiments in Python
Prüfungsimmanente Lehrveranstaltung
Labels
DIGITAL
Anwendungsseminare können nur für das Pflichtmodul B verwendet werden! Eine Verwendung für das Modul A4 Freie Fächer ist nicht möglich.
An/Abmeldung
Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").
- Anmeldung von Di 02.02.2021 09:00 bis Mi 24.02.2021 09:00
- Abmeldung bis Mi 03.03.2021 09:00
Details
max. 20 Teilnehmer*innen
Sprache: Englisch
Lehrende
Termine (iCal) - nächster Termin ist mit N markiert
- Dienstag 09.03. 13:15 - 14:45 Digital
- Dienstag 16.03. 13:15 - 14:45 Digital
- Dienstag 23.03. 13:15 - 14:45 Digital
- Dienstag 13.04. 13:15 - 14:45 Digital
- Dienstag 20.04. 13:15 - 14:45 Digital
- Dienstag 27.04. 13:15 - 14:45 Digital
- Dienstag 04.05. 13:15 - 14:45 Digital
- Dienstag 11.05. 13:15 - 14:45 Digital
- Dienstag 18.05. 13:15 - 14:45 Digital
- Dienstag 01.06. 13:15 - 14:45 Digital
- Dienstag 08.06. 13:15 - 14:45 Digital
- Dienstag 15.06. 13:15 - 14:45 Digital
- Dienstag 22.06. 13:15 - 14:45 Digital
- Dienstag 29.06. 13:15 - 14:45 Digital
Information
Ziele, Inhalte und Methode der Lehrveranstaltung
Art der Leistungskontrolle und erlaubte Hilfsmittel
The grading will be based on the writing of a relatively simple PsychoPy script for experimental presentation. Any sort of material or help may be used for writing your script, but it has to be written by you (and so of course you have to know what each function or line of code does). Your script will have to be presented shortly (e.g. 3-5 min) during one of the last lessons, after which you will get some feedback; the final code can be submitted anytime toward the end of the semester (deadline will be specified in due time).Syllabus (approx.):
1. General introduction to Python. Main variable types, basic commands.
2. Lists, tuples, strings, and related methods.
3. IF – ELSE – conditional statements, FOR and WHILE loops.
4. Dictionary variables. Defining functions.
5. Local and global variables.
6. Handling files and storing data.
7. Exception handling. Classes. Basic data processing and analysis.
8. Introduction to PsychoPy. Input through GUI and screen settings.
9. Presenting stimuli. Timing: the core module.
10. Monitoring and recording input: keyboard and mouse.
11. R statistics intro.
12.-15. Script presentations
1. General introduction to Python. Main variable types, basic commands.
2. Lists, tuples, strings, and related methods.
3. IF – ELSE – conditional statements, FOR and WHILE loops.
4. Dictionary variables. Defining functions.
5. Local and global variables.
6. Handling files and storing data.
7. Exception handling. Classes. Basic data processing and analysis.
8. Introduction to PsychoPy. Input through GUI and screen settings.
9. Presenting stimuli. Timing: the core module.
10. Monitoring and recording input: keyboard and mouse.
11. R statistics intro.
12.-15. Script presentations
Mindestanforderungen und Beurteilungsmaßstab
The PsychoPy script will have to be written at the end of the course, and it may present any sort of well-known or totally original psychological task (e.g. an example taken from an article or otherwise a task for your own upcoming thesis).However, it should include the following elements:
- Welcome screen and instructions (~10%)
- Presentation of stimuli according to the given task - including proper generation of possible items (or trial details) to be presented and possibly a balanced randomization of sequence order (~25%)
- Recording of responses (~20%)
- Feedback about the performance (extra)
- End screen (~5%)
- Output properly saved in a file, with all relevant data per each trial (~20%)
- Automatic preprocessing and/or brief pre-analysis of results (extra)Grades approx.:
>=50%: 4, >=63%: 3, >=75%: 2, >=87%: 1The percentages are just illustrative of the importance, there will be no detailed evaluation of each part.Alternative tasks may be possible (e.g. if you want to do some elaborate data analysis instead), but in that case first discuss it with me.After most lessons, there will be some small script to write as homework.
- Welcome screen and instructions (~10%)
- Presentation of stimuli according to the given task - including proper generation of possible items (or trial details) to be presented and possibly a balanced randomization of sequence order (~25%)
- Recording of responses (~20%)
- Feedback about the performance (extra)
- End screen (~5%)
- Output properly saved in a file, with all relevant data per each trial (~20%)
- Automatic preprocessing and/or brief pre-analysis of results (extra)Grades approx.:
>=50%: 4, >=63%: 3, >=75%: 2, >=87%: 1The percentages are just illustrative of the importance, there will be no detailed evaluation of each part.Alternative tasks may be possible (e.g. if you want to do some elaborate data analysis instead), but in that case first discuss it with me.After most lessons, there will be some small script to write as homework.
Prüfungsstoff
Literatur
Material will be uploaded to Moodle. There is no obligatory literature.Recommended:
Dawson, Michael. Python programming for the absolute beginner. Cengage Learning, 2010.
http://www.psychopy.org/documentation.html
https://discourse.psychopy.org/
https://stackoverflow.com/
https://repl.it/languages/Python3
Dawson, Michael. Python programming for the absolute beginner. Cengage Learning, 2010.
http://www.psychopy.org/documentation.html
https://discourse.psychopy.org/
https://stackoverflow.com/
https://repl.it/languages/Python3
Zuordnung im Vorlesungsverzeichnis
Letzte Änderung: Fr 12.05.2023 00:19
All lessons will be held in "webinar" (online meetings) format via BigBlueButton. If the situation allows, the script presentations in June may optionally be given in person.