Featured Articles
Jenny Baker
/ Categories: 581

SIOP Award Winners: Sidney A. Fine Grant for Research on Job Analysis

Liberty J. Munson

As part of our ongoing series to provide visibility into what it takes to earn a SIOP award or grant, we highlight a diverse class of award winners in each edition of TIP. We hope that this insight encourages you to consider applying for a SIOP award or grant because you are probably doing something amazing that can and should be recognized by your peers in I-O psychology!

This quarter, we are highlighting the winner of the Sidney A. Fine Grant for Research on Job Analysis, Evan Mulfinger.

What award did you win? Why did you apply (if applicable)?

The award was the Sidney A. Fine Grant for Research on Job Analysis. This grant was an opportunity to fund a project I have been interested in for several years that I believed had the potential to make a quality contribution to I-O and other fields that rely on O*NET data. I believed providing better access to the O*NET could encourage it to be used more frequently by groups such as researchers. Note: This project is ongoing and is to be completed by January 2021.

Share a little a bit about who you are and what you do.

I am a 4th year PhD student in I-O psychology at Rice University. My research interests include measurement development and validation, personnel selection, individual differences (especially personality), and job performance (especially counterproductive work behavior).

What do you think was key to you winning this award?

  • Emphasizing the practical utility of creating this application by describing how it will provide unparalleled access to the rich information provided within the O*NET database
  • Emphasizing that it will be useful for multiple audiences including researchers and practitioners within and outside of I-O (e.g., career counselors)
  • Providing detailed steps as to how I will accomplish this task such as a description of the R Shiny training I plan to complete
  • Providing a detailed description of what the final application will look like
  • Emphasizing that this tool will be user-friendly, free to use, and openly accessible

What do you see as the lasting/unique contribution of this work to our discipline?

I see this app as having the potential to increase the number of people that use the O*NET database in research and practice. I also believe it has the potential to serve as a popular method used to access O*NET data for purposes outside of research.

What’s a fun fact about yourself (something that people may not know)?

I grew up in the country and was fortunate to have a pond on our property. As a kid, I frequently walked down to the pond to fish, catch frogs, climb trees, and skip rocks. During one solo trip, a dog with no collar approached me and the farm cats that accompanied me. It first seemed that the dog was being aggressive toward the cats. I attempted to scare the dog away, so it wouldn’t attack me or my cats. Despite my efforts, the dog continued to approach me and my cat company. As I left the pond, the dog continued to follow our brigade and eventually arrived at my house. It was there that I realized the dog was not a threat and was simply trying to befriend me and my cats. Soon after, I named the dog Skye, and she spent an amazing 13 or so years with us. In Skye’s later years, she became less mobile and often settled in a particular place on our property for long periods of time. This resulted in my dad building multiple dog houses to ensure she had shelter wherever she lay. Skye will forever be remembered as a first ballot Hall of Fame pooch.

What piece of advice would you give to someone new to I-O psychology? (If you knew then what you know now…)

Don’t forget about psychology’s old friend—measurement. We can do all sorts of fancy statistical analyses, but they will provide no utility if the measures being analyzed are terrible. If you are using existing measures, evaluate existing evidence for its reliability, validity, and fairness. If you are developing a new scale, give due attention to item writing, and remember the importance of piloting more items than you intend to use. Before developing a measure, pay particularly close attention to content validity by remembering that you are trying to adequately sample from the domain of all possible content for that construct. Think of the content domain as a circle and the items as smaller circles that take up space inside the larger content circle (and overlap to varying degrees). It is also important to remember that validation is an ongoing process (i.e., an argument) that is often iterative.

Another piece of advice is to carefully plan out your research studies prior to collecting data. Give due attention to your research questions, hypotheses, relevant theories, and methods. Discuss with colleagues why you believe the research is important and why the work could be considered a contribution to the field. Last, try to develop a deep understanding of the role of theory within psychology as early in your studies as possible. Understand the viewpoints of those criticizing psychological theories, and be able to discern good theory from bad.

 

About the author:

Liberty Munson is currently the principal psychometrician of the Microsoft Technical Certification and Employability programs in the Worldwide Learning organization. She is responsible for ensuring the validity and reliability of Microsoft’s certification and professional programs. Her passion is for finding innovative solutions to business challenges that balance the science of assessment design and development with the realities of budget, time, and schedule constraints. Most recently, she has been presenting on the future of testing and how technology can change the way we assess skills.\

Liberty loves to bake, hike, backpack, and camp with her husband, Scott, and miniature schnauzer, Apex. If she’s not at work, you’ll find her enjoying the great outdoors or in her kitchen tweaking some recipe just to see what happens.

Her advice to someone new to I-O psychology?  Statistics, statistics, statistics—knowing data analytic techniques will open A LOT of doors in this field and beyond!

Print
1643 Rate this article:
4.0
Comments are only visible to subscribers.

Categories

Information on this website, including articles, white papers, and other resources, is provided by SIOP staff and members. We do not include third-party content on our website or in our publications, except in rare exceptions such as paid partnerships.