200077 SE Vertiefungsseminar: Entwicklung und Bildung (2023S)
Latent Modelling using Education Data
Prüfungsimmanente Lehrveranstaltung
Labels
DIGITAL
Dieses Vertiefungsseminar kann für alle Schwerpunkte absolviert werden.Vertiefungsseminare 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 Do 02.02.2023 09:00 bis Do 23.02.2023 09:00
- Abmeldung bis Fr 03.03.2023 09:00
Details
max. 20 Teilnehmer*innen
Sprache: Englisch
Lehrende
Termine (iCal) - nächster Termin ist mit N markiert
- Donnerstag 09.03. 09:00 - 10:30 Digital
- Donnerstag 16.03. 09:00 - 10:30 Digital
- Donnerstag 23.03. 09:00 - 10:30 Digital
- Donnerstag 30.03. 09:00 - 10:30 Digital
- Donnerstag 20.04. 09:00 - 10:30 Digital
- Donnerstag 27.04. 09:00 - 10:30 Digital
- Donnerstag 04.05. 09:00 - 10:30 Digital
- Donnerstag 11.05. 09:00 - 10:30 Digital
- Donnerstag 25.05. 09:00 - 10:30 Digital
- Donnerstag 01.06. 09:00 - 10:30 Digital
- Donnerstag 15.06. 09:00 - 10:30 Digital
- Donnerstag 22.06. 09:00 - 10:30 Digital
- Donnerstag 29.06. 09:00 - 10:30 Digital
Information
Ziele, Inhalte und Methode der Lehrveranstaltung
Art der Leistungskontrolle und erlaubte Hilfsmittel
Practical Arrangements: This is a self-driven, remote course. There are dates by which you have to complete all course work, however you can complete it whenever you want. You are free to work through the course materials at any time from when they are posted on Moodle until 30 May 2023. Please note that the watching of lessons, completion of quizzes, and assignments on Moodle will all contribute to your final mark.We will have weekly voluntary online Q&A sessions on Thursdays at 09h00 to 10h30. These sessions are for you to pop in at any time during the time slots and ask any questions you may have on the material. These sessions are voluntary. The links for the zoom sessions will be posted on Moodle. In addition, you can email me at any time to ask questions.Assignments/Lessons Requirements: You have to watch every lesson on Moodle and complete every quiz. In addition, you have to submit your assignment and essay by the deadline of 30 June 2023 at 00h00.
Mindestanforderungen und Beurteilungsmaßstab
Grade Composition
• Quizzes and exercises (on Moodle) – 20%
• Assignment – 20%
• Essay – 60%Grades will be converted to the Austrian 1-5 system in the following way:
≥ 90% = 1
75% – 89% = 2
60% – 74% = 3
45% – 59% = 4
≤ 44% = 5Late submissions will be handled on a case-by-case basis, but please note you may be penalized.In total there are exercises and quizzes on Moodle. Marks are given for every exercise and quiz. The point value of each question in every exercise is given next to the question.
• Quizzes and exercises (on Moodle) – 20%
• Assignment – 20%
• Essay – 60%Grades will be converted to the Austrian 1-5 system in the following way:
≥ 90% = 1
75% – 89% = 2
60% – 74% = 3
45% – 59% = 4
≤ 44% = 5Late submissions will be handled on a case-by-case basis, but please note you may be penalized.In total there are exercises and quizzes on Moodle. Marks are given for every exercise and quiz. The point value of each question in every exercise is given next to the question.
Prüfungsstoff
1. Understand, practically implement, and interpret the results of the following statistical procedures:
a. Correlations
b. Linear regression
c. Moderation and mediation
d. Path analysis
e. Exploratory factor analysis
f. Confirmatory factor analysis
g. Structural equation models (including syntax)
h. Measurement Invariance
2. Import, manage, and analyse datasets using JASP
3. Critically analyse structural equation model use and results in published peer-reviewed work
a. Correlations
b. Linear regression
c. Moderation and mediation
d. Path analysis
e. Exploratory factor analysis
f. Confirmatory factor analysis
g. Structural equation models (including syntax)
h. Measurement Invariance
2. Import, manage, and analyse datasets using JASP
3. Critically analyse structural equation model use and results in published peer-reviewed work
Literatur
Text Book: Kline, R. B. (2010). Principles and Practice of Structural Equation Modeling. This text is available in the library for you to reference or if you want additional information. It is not required for you to buy this book.Required Software: JASP, which can be downloaded here: https://jasp-stats.org/. If you have a MacBook and you experience difficulties downloading JASP, please consult this guide: https://jasp-stats.org/installation-guide/Technology Requirements: You need to have a laptop or personal computer for this course. You also need internet access to view lessons, do quizzes on Moodle and submit your assignment. Please contact me if any of this may be a problem.
Zuordnung im Vorlesungsverzeichnis
Letzte Änderung: Do 11.05.2023 11:27
• Correlation and Linear Regression
• Moderation and Mediation
• Path Analysis
• Exploratory Factor Analysis
• Confirmatory Factor Analysis
• Structural Equation Models
• InvarianceOn all these topics, background information will be given, but the course focuses on hands-on examples. Further, opportunity to use own data sets and to discuss them in class will be given. Specifically, students will get an in-depth understanding of the underlying statistical model.This course emphasizes open-source methods and data. As such we will be using only JASP and R to assess data and all of our datasets will be from open repositories of data.
No prior knowledge on latent modeling is needed, however, knowledge of basic statistic concepts (descriptive statistics, correlations, basic linear regression) is needed. We will also have a quick overview of these statistical concepts in the first few videos of the course.