Chapter 2 Doctoral Student Selection

The PhD program has a Fall-only admission to maintain an annual basis for enrollment evaluation, offer latitude in selection, and help us administratively monitor the process. Most importantly, this offers flexibility in balancing course offerings across the Masters and PhD programs. We value a balanced skill and experience profile across students, so evaluation doesn’t merely occur at the individual level, but rather a diversity of orientations across students and faculty.

We wanted a semi-structured process for selecting incoming I/O doctoral students above and beyond GPA, GRE, and letter/resume. As of the second year of admissions (AY 2020-2021), this is being implemented as a two-tiered process. The first phase consists of a standard I/O Psychology PhD student selection process whereas the second phase, currently being developed, will additionally implement additional predictors.1

2.1 Phase I selection

The Phase I application materials are:

  • GRE
  • Undergraduate GPA
  • 3 letters of recommendation
  • Statement of interest
  • Transcript

This foundation of predictors will be expanded upon once the MSU I/O Program PhD attains a level of establishment or otherwise has proven a robust annual applicant pool (a minimum of 35 completed applications).

The primary identified KSA’s that can be extracted from these standard predictors are:

  • General cognitive ability
    • GRE
    • Undergraduate GPA
  • Motivation
    • Letters of recommendation
    • Statement of interest
  • Knowledge
    • Transcript
    • Undergraduate GPA
  • Interest in I/O
    • Statement of interest
  • Interest outside of I/O (Multidisciplinary)
    • Statement of interest
    • Transcript
  • Civic engagement (pro-social interests)
    • MSU application form
    • Statement of interest

2.2 Phase II selection

Phase II selection materials may be be found or developed based on the KSAs presented here. The intent is for this list to expand - ideally being informed, in part, by information gleaned from current PhD students. We want a balanced cohort of students (balance of interests and skills).

KSAs to consider in making Phase II admissions decisions:

  • Statement of interest should target specific desired dimensions
    • Prosocial orientation
  • Resume
  • Echoing diversity of faculty skill sets
    • Inside and outside of I/O
  • conceptual skills
  • learning orientation
  • writing skills
  • Research experience
  • Recommended minimum GPA (3.6)
  • Internal locus of control (see also Bledow & Frese, 2009)
  • Humility with mistakes

More generally see Oswald et al. (2004).

Additionally, there was a recommendation to maybe go back to the PAD and extract constructs from there

Measure Minimum Future Notes
Purpose Statement Qualitative Develop scoring rubric? We can develop after more focused questions have been developed
Research Experience Qualitative Develop scoring rubric? Did they manage a lab? Was it specifically in I/O? What areas do they have experience in?
Letters of Recommendation Qualitative Develop scoring rubric? Can we ask MSU if they can add additional quesitons to the letter of recommendation form?
Undergraduate GPA 3.6 Likely too much inflation to place emphasis on graduate GPA for post-masters’ applicants
GRE Verbal 50th %ile 50th a placeholder
GRE Quantitative 50th %ile 50th a placeholder
Locus of Control Internally developed measure Anything beyond typical application materials will likely reduce our applicant pool
Humility with Mistakes Internally developed measure Anything beyond typical application materials will likely reduce our applicant pool
Interview Qualitative Develop scoring rubric? Anything beyond typical application materials will likely reduce our applicant pool

2.3 Selection Procedure

Core I/O faculty reviews completed applications by December 15. Everyone is expected to provide a personal candidate ranking.

2.3.1 Beyond minimum qualifications

During the second tier of the selection process, a short-list of top candidates will be administered a structured interview to assess their program understanding, research interests, and skill in research methods, study design, and general research conceptualization. This will help us make final decisions by further differentiating applicants. We will concurrently validate this tool using current graduate students to ensure it effectively forecasts graduate school performance.

Note. Mabye organize these subsections by track (data science, standard, business)

We have adapted a slightly different set of criteria for those applying to the Data Science specialization to ensure they can handle course content. In collaboration with Computer Science, we have agreed to the following set of recommended pre-requisites that can be fulfilled at the undergraduate level or through a pre-approved online course sequence:

Have an undergraduate GPA of at least 3.00 or a major GPA of at least 3.20 (to offset low grades due to difficult courses). Or, if they are a recent I/O masters graduate or current I/O masters student, have a GPA of 3.5.

Preferable to have a BA, BS, or a minor in computer science, mathematics, or commensurate STEM discipline. Provide evidence of technical skills, technological problem solving, or programming experience. Preferable if they have taken calculus, statistics, and an introductory computer science course, and received a B or higher in each course. If not calculus (or pre-calculus), it is acceptable to have taken discrete mathematical structures or a mathematical logic/set theory course. Approved online equivalents (e.g., MOOCs) are acceptable. [DO WE WANT TO DELETE THIS?]

Preference will be given to students who have completed undergraduate courses in an introductory social science course (e.g., intro psychology, intro to sociology), an Industrial-Organizational course, and Research Methods. Approved online equivalents (MOOC) are acceptable.

For students entering without suggested computer science pre-requisites, the Computer Science department offers two courses to rectify deficiencies in programming and data structures. These can be taken across their first year or in advance of admittance. The first is an introduction to Java programming along with designing algorithms and numerical computing (CSIT 501 Java Programming) and the second is an introduction to the design and analysis of computer data structures (CSIT 503 Data Structure). Student’s lacking background in hard sciences, mathematics, computer science, or programming will be required to complete each course outsidethe program’s required 79 credits (see advanced electives below).

2.4 Waiving MA Credit

The program will also adopt a matriculation process so anyone entering the MA program could advance into the PhD program if (a) they attain top-tier grades, (b) demonstrate research aptitude in coursework, (c) complete an applied research project (or thesis) as a capstone project, (d) secure sponsorship from a primary faculty member, and (e) show active involvement in the program per annual reviews. This offers (a) lagging students a leg-up to enter the PhD program if they demonstrate competence, and (b) MA students who show aptitude for a PhD but perhaps never contemplated it due to lack of mentorship at the undergraduate level. Students from the MA can apply for the PhD program to be considered for entrance into the doctoral program and have their MA courses count towards the PhD requirements as the two programs overlap in courses for the first two years. This enables us to recruit the top talent from our MA program and encourages multiple entry points into the doctorate program for individual at varying levels in their career or development. At the same time, due to low selection ratios, we will stress acceptance into the PhD is not guaranteed and will remain competitive.

In accordance with the Graduate School, students who have taken graduate work or completed a MA at a regionally accredited institution in psychology, organizational psychology, business administration, data science, or a related field may be allowed to waive up to 24 graduate credits. Eligible courses for waiver typically include the core I/O Psychology courses (currently 22 credits), methods/stats (15 credits), and, if completed and presented an original empirical project at a prior institution, the I/O Research Seminars (6 credits).

To qualify for waiver, the following criteria apply: an official transcript for desired transfer courses, equivalence to the MSU I/O courses and/or thesis project, a grade earned of “B” or higher, course taken within 10 years prior to matriculation, and the Doctoral Program Director approves the waiver. Any waiver petitions should be submitted alongside materials submitted during application to the doctoral program. Waivers will not be awarded for courses that were used within another MSU degree program.

The number of courses that may be waived is determined on a case-by-case basis by the Graduate School, I/O Program, and student’s assigned advisor. Although the department will help students with general questions about these issues, we will only conduct formal/binding reviews of course waivers until after the student has passed initial hurdles to be considered a viable applicant for acceptance into the program.It is anticipated no students will be eligible to transfer directly into doctoral candidacy; rather, most will need to complete a portion of MSU’s core I/O Psychology courses, an original thesis or IO research seminars, and pass qualifying exams before advancing.


Bledow, R., & Frese, M. (2009). A situational judgment test of personal initiative and its relationship to performance. Personnel Psychology, 62(2), 229–258.

Oswald, F. L., Schmitt, N., Kim, B. H., Ramsay, L. J., & Gillespie, M. A. (2004). Developing a biodata measure and situational judgment inventory as predictors of college student performance. Journal of Applied Psychology, 89(2), 187.

Tett, R. P., Brown, C., Walser, B., & Tonidandel, S. (2013). The 2011 SIOP Graduate Program Benchmarking Survey Part 4: Internships.

  1. This two-phase process recommendation was made in primary consideration of the MSU I/O PhD applicant pool. With additional predictors above and beyond the typical, at nascent stages of program development, the concern was that additional application hurdles would limit the size of our applicant pool.↩︎

  2. Or, if they are a recent I/O masters graduate or current I/O masters student, have a GPA of at least 3.5 or greater to reflect ability to handle graduate-level work. If they do not have a BA or BS in Psychology, course work will be individually reviewed for eligibility. Preference will be given to students with an introduction to social science course (e.g., intro to psychology, intro to sociology), I/O Psychology course, statistics (of any discipline), and a research methods course. We are looking for strong GPA commensurate with background courses.↩︎

  3. We want to make this less open-ended and specify particular dimensions of interest so we can evaluate everyone along the same characteristics. We want to expand on this within Phase II.Submit a personal statement that clearly articulates educational and professional goals. The personal statement should explain the applicant’s reasons for applying, his/her learning objectives, research interests and experience and long-term professional objectives.↩︎