Universität Wien

590007 SE Methodology & methods (2024S)

Advanced applied statistics in Education Sciences (or Social Sciences)

5.00 ECTS (2.00 SWS), SPL 59 - Doktoratsstudium Bildungswissenschaft
Continuous assessment of course work
Moodle

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Details

max. 15 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

  • Thursday 07.03. 15:00 - 16:30 Seminarraum 2 Porzellangasse 4, EG04
  • Thursday 14.03. 15:00 - 16:30 Seminarraum 2 Porzellangasse 4, EG04
  • Thursday 21.03. 15:00 - 16:30 Seminarraum 2 Porzellangasse 4, EG04
  • Thursday 18.04. 15:00 - 16:30 Seminarraum 2 Porzellangasse 4, EG04
  • Thursday 25.04. 15:00 - 16:30 Seminarraum 2 Porzellangasse 4, EG04
  • Thursday 02.05. 15:00 - 16:30 Seminarraum 2 Porzellangasse 4, EG04
  • Thursday 16.05. 15:00 - 16:30 Seminarraum 2 Porzellangasse 4, EG04
  • Thursday 23.05. 15:00 - 16:30 Seminarraum 2 Porzellangasse 4, EG04
  • Thursday 06.06. 15:00 - 16:30 Seminarraum 2 Porzellangasse 4, EG04
  • Thursday 13.06. 15:00 - 16:30 Seminarraum 2 Porzellangasse 4, EG04
  • Thursday 20.06. 15:00 - 16:30 Seminarraum 2 Porzellangasse 4, EG04
  • Thursday 20.06. 16:45 - 18:15 Seminarraum 2 Porzellangasse 4, EG04
  • Thursday 27.06. 15:00 - 16:30 Seminarraum 2 Porzellangasse 4, EG04

Information

Aims, contents and method of the course

Lernziele
• The objective of this course is to enhance knowledge and understanding of advanced statistical methods used in Social Sciences, with a particular focus on Education Sciences.
• Additionally, it aims to encourage critical reflection on quantitative research in Education Sciences, as well as on one's own research design and analysis.
• The course also provides an opportunity to formulate a research design and develop statistical procedures that align with the participants' research questions.
• The next objective is to gain and discuss brief information on various method groups using R environment. These groups include logistic regression, multi-level modelling (mixed models), specific quasi-experimental statistical analysis (DID, PSM, RDD), basic psychometric methods, power-analysis, cluster analysis vs. latent class analysis, and basic path analysis.
• Additionally, the course aims to improve the techniques of critical reading, discussing, and replicating other people's research.

Inhalte
The course aims to provide postgraduate students with a general understanding of advanced statistical methods in Education Sciences. Its primary purpose is to aid students in selecting and implementing the necessary statistical procedures for their dissertations. The secondary purpose is to familiarize students with the methods through practical work. Basic knowledge of statistical methods is a prerequisite for the course, and an entrance test will be administered. The course will begin with a focus on working in the R environment, as this will be used for seminar work and homework.
During the first half of the course, several methods will be introduced (although not all will be covered due to time constraints) and participants will be asked about their future dissertation topics. The second half of the course will delve deeper into 2 or 3 specific methods, utilizing real data from studies (preferably the participants' own, but if not available, then the instructor's). Please note that for the homework, you will need to search for in-depth information on the methods independently. It is recommended that you prepare in advance for this task.

Methoden
Reading, oral presentations (seminar papers), group discussions, R-practice in groups (4 assignments during the semester).

Assessment and permitted materials

For the preliminary work, you will need to complete two short assignments. These assignments will require you to conduct your own analysis and provide a screenshot of the results. Final Assignment: research report on the selected topic – results and syntax, plus oral presentation with slides. All assignments must be completed in groups.

Minimum requirements and assessment criteria

Mindestanforderungen
Active participation in class and at least “Genügend/4” for each task.

Beurteilungsmaßstab
1. Each of 3 written assignments: 20 points.
2. Research report: 40 (20 for written part + 20 for oral part) /Exam

Course grade
Score for the “Sehr gut/1” mark: [100-91]
Score for the “Gut/2” mark: [90-76]
Score for the “Befriedigend/3” mark: [75-56]
Score for the “Genügend/4” mark: [55-46]
Score for the “Nicht genügend/5” mark: [45-0]

Examination topics

Two assignments, research report (1 part and 2 part).

Reading list

Cohen, L., Manion, L., & Morrison, K. (2002). Research methods in education. Routledge.
Field, A., Miles, J., & Field, Z. (2012). Discovering statistics using R. SAGE Publications.
Gerstenberg, T. (2022). Statistical methods for the behavioral and social sciences. Retrieved from https://psych252.github.io/psych252book/
Goodwin, K. A., & Goodwin, C. J. (2016). Research in psychology: Methods and design. John Wiley & Sons.
Lakens, D. (2022). Improving Your Statistical Inferences. Retrieved from https://lakens.github.io/statistical_inferences/. https://doi.org/10.5281/zenodo.6409077
Vanderstoep, S. W., & Johnson, D. D. (2008). Research methods for everyday life: Blending qualitative and quantitative approaches. John Wiley & Sons.

Association in the course directory

DSE

Last modified: Th 07.03.2024 14:47