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Faculty

Dr. Jason Dahling

Office: SB 121
Phone: (609) 771-2582

email: dahling@tcnj.edu

Courses: Organizational Psychology, Design & Statistical Analysis, Research Seminar: Organizational Misbehavior, Laboratory Learning, Industrial Psychology, Personnel Selection & Placement, Performance Advisor, Internship Advisor, Independent Study Advisor

Research Interests: Most of my research concerns deviance in organizations, particularly in terms of (a) showing inappropriate emotions to customers in customer service settings; (b) seeking feedback to enhance one’s public image; and (c) breaking organizational rules in a pro-social fashion to improve efficiency or to provide for customers and co-workers. I am also interested in industrial topics such as flexible scheduling and work-status congruence.

Dr. Jean P. Kirnan

Office: SB 109A
Phone: (609) 771-2637

email: jkirnan@tcnj.edu

Courses: Freshman Seminar, Organizational Psychology, Research Seminar in I/O Psychology, Industrial Psychology, Consumer Psychology, Personnel Selection & Placement, Psychological Testing, Research Roundtable, Senior Seminar, Independent Study Advisor

Research Interests: Use of Biodata to Predict First Year College Success: Application of a Business Model to Education; Presence of Stereotype Threat in Employment Tests; Content Analysis of Children’s Television Commercials; Initial and Subsequent Career Success for Graduates of the I/O Specialization; Investigation of Everyday Ethical Challenges.

Dr. John Ruscio

Office: SB 110
Phone: (609) 771-2919

email: ruscio@tcnj.edu

Courses: The Price of Everything (FSP), Design & Statistical Analysis, Seminar in Applied Psychology, Science & Pseudoscience in Clinical Psychology, Seminar in Behavioral Economics, Independent Study Advisor, Honors Thesis Advisor

Research Interests: There are two streams in my recent research. First, I’ve been studying indices of scholarly impact that might be useful for decision making involving individual scientists (e.g., hiring, tenure, promotion, funding), for ranking the research productivity of graduate programs, or for comparing the influence of psychology journals. Second, I’ve been studying ways to take advantage of cheap computing power to improve modern methods of data analysis. This includes determining whether people cluster together in groups or vary along one or more continuous dimensions, measuring and communicating the size of effects, assessing the satisfaction of statistical assumptions in published studies, and developing and testing new approaches for identifying common factors underlying correlated variables.

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