Preconferences
Montag, 16. September 2019 | 9 - 12 Uhr | Seminargebäude OG2
Klick auf den Titel öffnet Beschreibung.
Sozialpsychologie zu Flucht und Integration
Dr. Helen Landmann & Dr. Jens Hellmann
Migration und Flucht nach Deutschland stellen die Gesellschaft vor eine Reihe von Herausforderungen: Wie lassen sich Ängste und Vorurteile sowohl bei den Einheimischen als auch bei den Geflüchteten reduzieren? Wie können wir möglichen Konflikten vorbeugen oder sie lösen? Wie können Ehrenamtliche unterstützt werden?
Mit einer Annäherung an Antworten auf diese und weitere Fragen möchte das Fachnetzwerk Sozialpsychologie zu Flucht und Integration durch den Austausch zwischen sozialpsychologischer Forschung und Praxis beitragen. Den Theorie-Praxis Transfer stellt das Netzwerk über die Website www.fachnetzflucht.de, Vorträge und Workshops mit Praktiker*innen sowie über Diskussionsrunden mit Politiker*innen her.
Im Rahmen dieses als Workshop geplanten Treffens werden die aktuellen Projekte des Fachnetzwerks besprochen, abgeschlossene Projekte evaluiert und weitere Projekte geplant. Als Aufgaben und Herausforderungen für das Fachnetzwerk werden wir unter anderem adressieren, wie wir die Wirksamkeit unserer Projekte überprüfen können, welche weiteren Fragen auf unserer Website beantwortet werden sollten und wie interessierte Forscher*innen, die noch nicht am Fachnetzwerk beteiligt sind, einen Beitrag für das Fachnetzwerk verfassen könnten. Interessierte sind herzlich eingeladen, an dem Workshop teilzunehmen, sich mittels Impulsvorträgen zu Beginn des Workshops über das Fachnetzwerk zu informieren und sich an unserer Arbeit zu beteiligen.
Cumulative science: From transparency to efficient theory development
Prof. Dr. Andreas Glöckner & Prof. Dr. Susan Fiedler
The replication crisis in psychology and beyond has inspired many fruitful discussions of methodological aspects of the research process. As a result, (more) openness and transparency concerning empirical work have become widely accepted methodological standards. Inspired from these discussions, also more fundamental issues concerning theory specification and theory development have come in the focus of the debate. In this workshop, we will discuss basic issues of theory of science and their implications for assuring cumulative science (a cumulative development of knowledge). Implications for the own research are discussed and in various hands-on exercises, we will practice (i) the evaluation of theories, (ii) the full formal specification of theories and (iii) (briefly) the construction of efficient theory tests.
Estimating and interpreting psychological networks
Dr. Jens Lange & Dr. Jonas Dalege
Psychological constructs are most frequently conceptualized as latent variables. That is, psychological constructs are conceptualized as unobservable entities that cause changes in measurable indicators. The indicators themselves have no direct causal effects on each other. For instance, an attitude toward someone might be a latent variable that causes changes in how a person feels or thinks about and behaves toward the other person. From this perspective, feelings, thoughts, and behaviors do not have direct causal effects on each other.
Recent research proposes an alternative to the conceptualization of psychological constructs as latent variables. The idea is that psychological constructs emerge from causal interactions between its components. Therefore, they can be represented as networks of causal relationships—the network approach. For instance, thoughts about someone may cause feelings, while thoughts and feelings collectively influence behavior. The attitude is then the network of relationships between feelings, thoughts, and behaviors without inference of any latent variable.
The network approach is gaining more and more traction in psychology. It has been proposed as an alternative to latent variable models for attitudes, beliefs, emotions, psychological disorders, personality, and intelligence. Moreover, to facilitate the estimation of networks from data, multiple analytical techniques have been developed in the last five to six years. The goal of the workshop is to introduce (a) the theoretical framework of the network approach and (b) statistical network estimation and analysis.
In the first part of the workshop (approx. 30 minutes), we will discuss the theoretical framework of the network approach. It is grounded in the interdisciplinary notion of complexity, namely the emergence of complex behavior from nonlinear interactions between simple components without central control. We will show how this notion can be applied to psychology, conceptualizing psychological constructs as emerging from networks of causal relationships between components.
In the second part of the workshop (approx. 90 minutes), we will introduce two popular models to estimate networks from data—the Ising model for binary data and the Gaussian Graphical Model for continuous data. Attendees will be asked to carry out network analysis themselves on their computers. This hands-on part will cover ways to estimate these models, visualize them, determining their structure and most central components, and testing their stability. The network analysis will be conducted in R. Therefore, some preexisting knowledge of R is required. However, we will also briefly discuss an alternative, more simple analysis program for psychological networks, namely the open source, graphical program JASP. Instructions on how to install and set up R and JASP will be send around before the workshop. Next to this, we will share all necessary data and code for the analysis.
In the third part of the workshop (approx. 60 minutes), we will leave time for attendees to analyze their own data. This provides the possibility to apply and practice network analysis with the possibility to ask for help. Before the workshop, we will give detailed instructions on how data sets should be prepared in order to allow the immediate analysis. For everyone who has no data set to analyze, we will make one available.
Eventually, the workshop will provide attendees with the necessary theoretical background regarding the network approach and prepare them to estimate networks from data as well as interpreting the results.
Reproducible data analyses in R using RStudio, RMarkdown, and the "tidyverse"
Mathias Twardawski & Felix Henninger
Following the replication crisis in psychological research, new research practices have emerged to improve psychological science. Central features of the "open science" movement are preregistrations, "open material," and "open data." These features are thought to increase the transparency of our research practices and may become the standard of good (psychological) research practice in the very near future. Additionally, researchers also started to provide their data analyses scripts (in R) to enable the replication of the analyses reported in their manuscripts; and publishers, editors, and reviewers (may) also start to ask for such scripts. Importantly, these scripts should not only include the analyses but also the manipulation and preliminary treatment of the data from the raw data file to the analyzed data set. Consequently, this data handling and preparation should be structured in a comprehensible manner.
In this short workshop, we will give interested R users some insights in how they may organize and rearrange their R scripts to increase comprehensibility and reproducibility of their data manipulation and data preparation. Therefore, we first show some very useful features of RStudio and RMarkdown before we practice reproducible data management using the R package tidyverse. Tidyverse is an R "eco system" helping to handle, analyze, and visualize small, medium, and large data sets very quickly, allowing to get from a simple data sheet to helpful graphs and test results very easily.
We assume basic familiarity with R and RStudio. Please bring your laptop with the newest versions of R and RStudio, as well as the R Package "tidyverse" being installed.
Verständlich schreiben für die Öffentlichkeit: Ein (In-Mind) Schreibworkshop
Dr. Jan Crusius & Jun.-Prof. Dr. Oliver Genschow
Psychologie hat hohe Relevanz für alltägliches Leben und Gesellschaft. Wissenschaftliche Erkenntnisse zu kommunizieren, wird daher nicht nur immer häufiger gefordert, sondern ist auch sehr lohnenswert. Dieser Workshop soll Sie dabei unterstützen. Die Dozenten des Workshops, Jan Crusius und Oliver Genschow, arbeiten als Herausgeber beim Online-Magazin In-Mind. Das Anliegen von In-Mind ist es, komplizierte wissenschaftliche Befunde in einfacher und verständlicher Sprache aufzubereiten und dabei Interesse für psychologische Forschung zu wecken. Ihre Erfahrungen dabei werden sie im Workshop weitergeben.
Ziel des Workshops ist es, sich anhand eines eigenen Manuskriptentwurfs mit wichtigen Elementen guten populärwissenschaftlichen Schreibens vertraut zu machen. Ein potentieller In-Mind-Artikel wird dafür als Beispiel dienen. Die Teilnehmenden sollen deshalb vor dem Workshop eine kurze Schreibprobe zu einem psychologischen Thema ihrer Wahl zu erstellen und mitzubringen. Der Entwurf sollte Titel, Teaser und die ersten Absätze beinhalten. Um die Inhalte des Workshops zu vertiefen, haben die Teilnehmenden während des Workshops und im Anschluss die Möglichkeit, das Manuskript zu überarbeiten und später bei In-Mind einzureichen. Um einen Eindruck von In-Mind-Artikeln zu bekommen lohnt sich der Blick auf de.in-mind.org.