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Scholarship

Workshops

The following workshops are not part of one of the certificate or badge programs. You can explore those workshops on the Certificates and Badges page.

Scholarship

Listed below are FDC workshops centered around scholarship that are not part of one of the certificate or badge programs.

Lecturer Portfolio Drop-in (click to join scheduled Zoom)

An open Zoom room to get your questions answered as you are completing your Lecturer Portfolios.

Productive Online Writing with Accountability (POWWA) (Zoom)

  • February 13, 2025 | 1:00pm-1:30pm
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A VIRTUAL writing workshop designed to value your writing and keep it going. Need accountability? Want someone in your corner? FDC Faculty Fellow Terri Patchen will help you organize your writing tasks and align your writing with your publishing aims and be accountable to your writing deadlines. Email Terri Patchen at tpatchen@fullerton.edu by February 14, 2025 to reserve a spot in this winning program.

Using Social Media for Academic Research (Hybrid; In-Person)

  • February 18, 2025 | 11:00pm-12:30pm
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Why collect data when people share so much information publicly online? This workshop will provide examples of research that draws on social media content to answer social scientific questions, including sample selection and participant recruitment. There will be time to explore how social media can be used to address your research questions.

Writing a Great CV ( Asynchronous )

A canvas-based self-paced course highlighting important concepts when writing your CV.

 

Quantitative

Listed below are FDC workshops centered around quantitative methods that are not part of one of the certificate or badge programs. Click on an offering to register.

Introduction to Excel (Asynchronous)

Learn how to enter and organize data, create basic formulas and functions, and build charts and pivot tables.

Introduction to R (Asynchronous)

The focus of this workshop will be on introducing the programming language of R and the user interface RStudio (to make R prettier) and applying R to inferential psychological statistics.  This workshop will begin with a brief installation tutorial, interacting with the RStudio user interface, and an overview of some R programming basics and key functions.

Content Analysis (Hybrid; In-Person)

Content analysis methodologies can be used to create data that is qualitative, quantitative, or mixed methods. Dr. Rakovski will share her experiences applying the methodology of content analysis in legacy media, such as newspapers and news websites, and popular culture, namely film. She will share her new research project, which analyzes social media posts. Bring your research questions and potential data sources to share with the group. There will be time to consider how you can set up your own content analysis research project, e.g., defining a population, sampling, coding systems, types of analyses, and more.

Introduction to SPSS (Asynchronous)

This hands-on workshop will serve as an introduction to using SPSS, a powerful computer program used for doing statistical analysis of data for research and other projects. Learn to enter and manage data, perform basic statistical analyses, and interpret results using SPSS.

Introduction to Multiple Regression Using SPSS (Asynchronous)

Introduction to the statistical technique of multiple regression, the appropriate applications of the technique and statistical considerations when including multiple predictors.  It will conclude with a demonstration of the common model selection algorithms (forward selection, backward elimination, and stepwise regression) using SPSS.

Introduction to Structural Equation Modeling (Asynchronous)

This workshop will focus on running and reporting basic structural equation models (SEM).  We will begin with a conceptual overview of SEM focusing on the Bentler-Weeks formulation.  Presuming the data have met the necessary assumptions (reviewed briefly), we will cover how to specify a basic SEM for analysis using the Diagrammer in EQS to write nearly all the necessary EQS syntax to run an SEM model.  We will examine the output and discuss “what to report” (e.g., adequacy of the measurement model, recommended fit indices, etc.), examine model modification indices, and present effect decomposition.  Finally, we will translate the model developed in the EQS Diagrammer, along with the EQS output, into a manuscript-ready model using LaTeX software.

Intermediate Excel (Asynchronous)

This workshop is designed for faculty who have used Excel before and want to expand their knowledge. Improving formatting, organizing data, highlighting key information, and creating formulas/links between sheets. Specifically, we will be using Excel to quickly summarize multiple sheets of data into one, turn long lists and reports into easy to read tables, use formulas to check whether cells pass or fail specified rules, create links between cells so that they update automatically, and highlight targets, trends, duplicates and errors with Conditional Formatting.

Intermediate R (Asynchronous)

The focus of this workshop will be on utilizing the programming language of R and the user interface RStudio for running inferential statistics. This workshop will begin with a brief overview of some R programming basics and key functions. After reviewing some R fundamentals, the programming language will be applied to psychological statistics including topics such as t-tests, correlation, regression, and creating customizable plots.

Introduction to Item Response Theory (Asynchronous)

An essential aspect of psychological research is the measurement of individuals on a construct of interest. Furthermore, accurate measurement of individuals is imperative when high-stakes decisions are involved. Therefore, much of psychological research comprises the development, revision, and application of measurement instruments. The focus of this workshop will be on applications of Item Response Theory (IRT) models to measuring psychological phenomenon. The workshop will begin with a brief discussion/review of related topics (e.g., classical test theory, logistic regression). After establishing IRT fundamentals, the assumptions and modeling techniques of IRT models for dichotomous data will be illustrated conceptually using modern statistical software, R. Finally, utilization of various dichotomous IRT models to inform scale revision will be demonstrated and applied to example datasets. Basic knowledge of R is recommended, but not required.