Teaching

I primarily teach courses in statistics and research methods within the field of psychology, catering to both undergraduate and graduate students. Since 2011, I have conducted 44 classes, with evaluations available for 14 of them (N = 178). Students have consistently rated my teaching highly, with an average rating of 1.53 (N = 163, SD between classes = 0.19; grades ranging from 1 = very good to 6 = unsatisfactory). Additionally, the subjects covered in these classes received an average grade of 1.72 (N = 168, SD = 0.31).

I have supervised 20 students in their thesis projects.

Research Methods (Bachelor)

Methods I

My primary focus has been on teaching Methods I, for which I have developed a comprehensive collection of teaching materials (all in German). This material, available under a CC license, is published as a print version through KDP and can be accessed at: https://amzn.eu/d/fxOVD7m. It includes 159 exercises covering various topics:

Everyday psychology vs. scientific psychology
Philosophy of science
Measuring and testing (including conjoint measurement theory)
Observation and questionnaires
Experiment and descriptive statistics
Correlation and regression
Probability theory
Short introduction to R
Logic of significance tests
T-test
Confidence intervals
ANOVA
Meta-analysis
Qualitative methods

Methods II

I also have significant experience teaching Methods II, which covers a broader range of topics. The teaching materials for this course are currently exclusively available to enrolled students. Topics include contrast analysis, dependent samples (t-test, ANOVA, contrast analysis), non-parametric tests, factor analysis, cluster analysis, non-linear relationships, explorative data analysis, and the limitations of significance testing. I plan to compile this extensive material into a book in the future.

R

For my R courses, I use my dedicated learning site: rlernen.de, along with a co-authored book (in German):

Datenanalyse mit R: Fortgeschrittene Verfahren, Burkhardt, Titz, Sedlmeier, Pearson Studium Psychologie, (ISBN-10: 3868944133, ISBN-13: 978-3868944136).

This resource covers advanced topics and includes a comprehensive chapter on multi-level modeling. It is available for purchase at various bookstores and directly from Pearson: Datenanalyse mit R.

Additionally, I recommend the Essential R Cheatsheets, which include a Basic Stats Cheatsheet covering all crucial aspects of data analysis: Essential R Cheatsheets.

Research Methods (Master)

I have taught method classes for graduate students on topics such as computer simulation (e.g., artificial neural networks, cellular automata), structural equation modeling, and mixed models. I also conducted sessions on mixed models and formal modeling in psychology as part of a lecture series on research methods for Master’s students. Additionally, I co-taught a specialized course on artificial neural networks with Prof. Dr. Peter Sedlmeier.

YouTube

Explore my YouTube channel for content on research methods and R:

Methodenmonster YouTube Channel

The content is a mix of English and German, with most videos in German.

Teaching Approach

My teaching philosophy emphasizes creating exercises based on real-world issues in psychological science. While this may seem standard, I have noticed a trend among instructors who rely on poorly constructed fake studies or fabricated data, which I believe is not the most effective way to learn.

Inspired by Klaus Grawe’s work on psychotherapy mechanisms, particularly problem actuation, I stress the importance of experiencing problems firsthand in a genuine setting to overcome them. This principle also applies to learning, where the goal is simply behavior change. To foster problem actuation, I integrate real research papers into my courses. This approach reflects the challenges scientists face—reading and understanding literature, including methods and statistics—and provides a deeper understanding of the scientific process and research methods.