Career prospects

The ARMS specialization focuses on modern methods of psychological data analysis - from the basics of estimating statistical models to longitudinal data analysis and practical machine learning workflows. The aim is to provide you with a theoretical understanding of central methods as well as hands-on skills in the statistical software R so that you can analyze complex data in a structured way, interpret results and document them in a reproducible manner. The accompanying seminars in particular will teach you how to apply and evaluate more complex multivariate methods. The lecture currently covers the following three topics:

• Bayesian statistics (FG Psychological Methodology),
• longitudinal data modeling (FG Differential and Personality Psychology) and
• Machine Learning (FG Psychological Diagnostics)

Bayesian statistics. The starting point is the question of where the key figures shown in statistical software come from. A basic introduction to estimation theory and the properties of estimators is provided. The two dominant approaches, maximum likelihood and Bayesian estimation, are then introduced, each with a view to complex models such as structural equation and multilevel models. A basic understanding of estimation methods is important, as estimation problems are more common in sophisticated models and jeopardize interpretability. However, the diagnosis and resolution of estimation problems requires an understanding of the underlying estimation procedures. In addition, models that can only be adequately estimated using Bayesian methods are increasingly being used in clinical and applied psychology.

Longitudinal data modeling. Using real data sets, you will systematically specify, estimate and interpret common longitudinal models: from the t-test for paired samples to linear and non-linear latent growth curve models and dynamic structural equation models. The practical implementation is mainly done in R (e.g. lme4, lavaan, brms); inferential strategies, the assessment of model fit and the handling of challenging data situations (e.g. missing values, small samples, non-normally distributed variables, nested structures) are also covered. The focus is on the fit of model and estimation methods to the respective research question as well as the appropriate interpretation of results.

Machine Learning. First, fields of application of ML in psychological research are presented and an explanation-oriented mindset is distinguished from a prediction-oriented mindset. Central terms and principles such as cross-validation, hyperparameter tuning, bias-variance trade-off and overfitting are then explained. Building on this, you will learn about regularized regression methods (Ridge, LASSO, Elastic Net) and classification methods (CART, Random Forests). The final session is dedicated to typical pitfalls such as the incorrect validation of model results and the specific challenges of applying ML models in psychology (e.g. small samples, unreliable indicators).

Career prospects: ARMS prepares you for data analysis in data-processing companies and institutes such as survey institutes, research institutions or consulting firms. You will learn to translate complex questions into precise models and select suitable analytical strategies in order to develop reliable, data-based solutions. You will learn how to systematically prepare data, critically scrutinize results and communicate them in a way that is appropriate for the target audience, as well as document the analysis steps in a transparent and reproducible manner. ARMS also prepares students for method-oriented research projects - both as part of their Master's thesis and following their studies as part of a doctorate.

The KBE specialization, represented by the subject areas of general, educational and developmental psychology, offers the opportunity to deepen basic and applied aspects in relation to educationally relevant content. You will expand your knowledge of the basic principles of teaching and learning, the development of knowledge and the influence of educational contexts on school performance.

The "Cognition" part of the lecture initially deals with newer models of working memory and how these can be used for questions of instructional psychology. Another topic of the lecture is the consolidation of learning content that has already been understood and represented in long-term memory (e.g. news on the testing effect). Finally, we deal with the question of how linguistically interacting people establish a common knowledge background (grounding). In addition, recent work on gender-equitable language or the relationship between language, sound, music and meaning will be discussed.

In the "Education" section, the lecture deals with social and motivational conditions for successful learning - such as cooperative learning, educational inequalities or current research on education. A first seminar focuses on school-related topics, e.g. teacher behavior, emotional and social dynamics in the classroom, gender and self-concept, individual learning prerequisites (e.g. self-handicapping or growth mindset) and instructional psychology approaches (e.g. productive failure, artificial intelligence and education). A second seminar is dedicated to the main topics of education, parenting and learning support - with room for individual questions.

In the "Development" part of the lecture, we will examine the extent to which cognitive abilities and tendencies to act are innate (or develop independently of formal education), what evolutionary purpose these abilities and tendencies serve, and what similarities and differences there are between humans and animals with regard to these aspects. In the project seminar, you will have the opportunity to deepen your own research interests by looking for a question yourself, for which you will develop a project.

Career prospects: The KBE specialization prepares you not only for scientific activities at university and non-university research institutes, but also for activities in the context of educational or learning counseling (e.g. school psychology or in family counseling centers), as well as for learning support or the therapy of learning disorders (e.g. dyslexia, dyscalculia), for which you do not need a license to practice. Adult education or personnel development are also possible attractive fields of activity.

Work is an important part of people's lives; they often spend a large part of their waking hours working on self-defined or externally defined tasks, earning a living or contributing to the achievement of socially valuable outcomes. People move in environments that are characterized by a certain work structure and culture. Work not only fulfills material functions, but can also be a source of meaning, identity and social connection.

At the same time, work structures are often perceived as being in need of improvement. In addition, there are new challenges, such as technological developments that change work tasks, open up new forms of collaboration or entail additional requirements.

The focus on people - work - technology provides the necessary methodological and theoretical tools to be able to analyse when work structures have a beneficial or detrimental effect on health, motivation and performance, which changes result from digitalization and automation and how work and the division of functions between man and machine can be optimally designed so that work remains humane, efficient and sustainable. Topics covered include work motivation, job satisfaction and performance, stress and health, AI use at work, leadership, group work and career development.

Career prospects: The Master's degree with a focus on MAT qualifies students for research and teaching at universities and private and public research institutions and for professional work in organizations, for example in the field of personnel and organizational development, human-machine interaction or change management.

Human civilization is facing various environmental crises which - it is unanimously expected in science - threaten the essential foundations of social coexistence and individual well-being. Human economic activity and ultimately behavior are the causes of these profound changes. Environmental psychology deals with this interaction between humans and the environment with the aim of gaining a better understanding of it and identifying paths to a more sustainable life. Topics covered include the perception of global warming, environmental conflicts, green innovations, collaborative consumption, rebound and growth, post-growth society and sufficiency.

Career prospects: Environmental psychology thus offers a modern and up-to-date field of expertise that qualifies students to work in various positions and whose relevance will increase in the coming years due to the acceleration of global warming. The Master's degree qualifies students for research and teaching at universities and private and public research institutions, but environmental psychologists are also trained for consulting and planning activities, such as in sustainability management and transformation processes, and can provide the necessary psychological input in politics, public offices, associations and companies.