Current Research Projects

  • Network Analysis

    Interested in learning more about how to apply network analysis to topics in social and organizational psychology? We’re preparing studies on peer institution networks, faculty author networks, and shared leadership networks.

  • Multidimensional Forced Choice (MFC) Measures

    MFC measures have grown in popularity as an alternative to traditional Likert-type measures (scale of 1 to 5) that often suffer from faking, social desirability, and bias. These have primarily been developed for personality measures; we are looking to develop them for constructs such as leadership and vocational interests.

  • Multigroup Membership for Multiracial Data

    Multigroup Membership multilevel models are designed to test datasets where individuals belong to two or more groups simultaneously. Though originally designed for teams and education research (e.g., employees with 2+ bosses; students in 2+ classrooms), we would like to apply this to multiracial individuals (i.e., individuals with 2+ racial identities).

  • Natural Language Processing

    NLP methods have grown tremendously in recent years, especially in psychology. We have several projects applying NLP to different contexts, such as analyzing transcripts from reality TV shows to predict performance and analyzing leadership measures.

  • GPT and LLMs

    GPT and other large language models (LLMs) are increasingly used for data generation, analysis, and experimentation. We have several projects looking to implement GPT in research areas such as leadership development, generating leadership data, and more.

  • High-Fidelity Simulation-Based Assessment

    Recent scholars have raised concerns over our field’s over-reliance on surveys and lab experiments that suffer from low generalizability to the real-world. We would like to build “high-fidelity” in-person simulation experiences to assess leadership, teamwork, and communication. This includes game design, physical setup to maximize real-world applicability, and use of technology for dense data collection (e.g., video and audio).

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Recent Publications

  • Using a database of over 20,000 research articles, we leveraged human + GPT coding to assess for publication bias in the content of the research on controversial topics in the social sciences (e.g., free speech, standardized testing). We found limited evidence of publication bias — which bodes well for maintaining the integrity of scientific research — but interesting effects among the faculty author demographics and institutional attributes. Read the full paper here.

  • Our most recent publication features a review of 80 years of research on “forced-choice” measurement. We discuss what it is, why it works, and how it can be improved. Find out more here, or read the full publication here.

  • I’m thrilled to announce my first book published with Cambridge University Press, coming in July 2025! The book is an anthology of narratives of people navigating their first jobs as they embark on their careers, paired with a review of the career counseling literature designed to help today’s job seekers in their career journeys. We hope that this book becomes an impactful resource for job seekers from all background, industries, and life stages as they begin their career journeys. You can order here using the discount code FRFJC25 for 20% off, or find it on Amazon. You can also download a preview of the book here.

  • This study focused on demonstrating how multiple facets of well-being — ranging from leadership to grit — matter in college student life. We collected data from over 5,000 college students linking self-report well-being surveys to data on their time spent on campus, course attendance, grades, and more. Find out more about the study here, or you can read the full research paper here!