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The Science Behind PathwayU

Most college students face enormous developmental tasks during their college years, including establishing a sense of identity, building healthy relationships, […]

Most college students face enormous developmental tasks during their college years, including establishing a sense of identity, building healthy relationships, and making key decisions about the direction of their educational and career paths. This latter challenge has been a focus of decades of research within applied psychology – an academic subfield that builds on the study of individual differences, developmental theory and research, and psychometrically-sound measurement strategies.

With an emphasis on bridging science and practice, applied psychology also values evidence- based intervention strategies. Designed by internationally renowned scholars in career decision- making and online training, PathwayU’s PathwayU portal is an online career assessment and guidance system informed by the best available scientific research at every step.

Specifically, PathwayU leverages this science by (a) using reliable and valid assessments to (b) predict the level of fit between students and vocational paths based on students’ personal attributes and the unique characteristics of particular career paths, while (c) providing students with useful, empirically-supported feedback and support so they can effectively navigate the education and career decision-making process.

Psychometrically Sound Assessment of Key Student Attributes

The PathwayU portal measures key attributes which are critical for informed career decision- making: work-related values, vocational interests, personality, and workplace preferences.

  • Work-related values refer to the relative importance individuals place on various aspects of their work. When individuals (students) perform tasks that are related to their core values, they find work (study) meaningful and satisfying. PathwayU measures 20 needs that combine to form the six value dimensions drawn from the Theory of Work Adjustment: Achievement, Independence, Recognition, Relationships, Support, and Working Conditions.1
  • Vocational Interests refer to individuals’ likes and dislikes for types of work activities or occupations. When people (students) perform tasks they find interesting, they are engaged and motivated to do well and improve. PathwayU incorporates the most heavily-researched theory of vocational interests in history – John L. Holland’s theory of vocational types – which postulates that both people and work environments can be classified according to each of six interest types: Realistic, Investigative, Artistic, Social, Enterprising, and Conventional.2
  • Personality refers to stable traits that reflect how people tend to think, feel, and act over time and across situations. Personality predicts success in learning environments.3 PathwayU assesses personality using the heavily-researched HEXACO Model, consisting of the following traits: Openness to Experience, Conscientiousness, Extraversion, Agreeableness, and Emotional Stability, and Honesty/Humility.4
  • Workplace Preferences refer to the needs individuals express for particular values, beliefs, and actions that characterize an organization’s culture. PathwayU assesses seven workplace preferences drawn from a revision of the Organizational Culture Profile, arguably the most well-regarded assessment of organizational culture available.5 These dimensions are: Excellence, Guiding Principles, Collaboration, Innovation, Recognition, Performance, and Stability.

The measurement instruments used within PathwayU were carefully selected or developed according to several factors including the strength of the evidence supporting their reliability and validity. Two (the Work Interest Profiler and the Work Importance Locator) were developed by the U.S. Department of Labor, one (the HEXACO Personality measure) is a proprietary version that converges well with the HEXACO-60, and one (the Organizational Culture Profile) is based on early work by O’Reilly and colleagues, later modified by Cable and Judge, and more recently by Sarros and colleagues.

Using Person-Environment Fit to Predict Career Paths

PathwayU is built on the principle of person-environment fit: the better the fit between a student and a particular career path, the better the outcomes for that student.

More specifically, person-environment fit (P-E fit) theorists propose that fit to a particular career path predicts both satisfaction and persistence within that path – that is, students who pursue educational paths that fit them well tend to be happy, find their educational path to be meaningful and engaging, and are committed to earning a degree and obtaining relevant employment within their chosen career path.6

Putting P-E fit principles into practice, PathwayU uses proprietary algorithms that match students to career paths predicted to fit them well based on their unique psychological profiles. The “person” is quantified within the PathwayU portal whereas the “environment” is quantified with extensive data collected by the U.S. Department of Labor in its Occupational Information Network (O*NET).

O*NET provides detailed information for approximately 1,100 career paths. Validity evidence for PathwayU’s predictive methodology is drawn from several published meta-analyses, which provide quantitative summaries of decades of research on the psychological variables assessed by PathwayU. Because any single research study can be subject to chance factors that may lead to spurious results, meta-analyses are an extremely important source of evidence supporting the predictive validity of the PathwayU methodology.

Meta-analytic studies combine results drawn from many studies with the goal of identifying patterns across settings and estimating true relationships between variables. For the meta- analyses reported below, a summary statistic (averaging results of all available studies across a body of research) estimates the extent to which a characteristic, such as individual interests or fit to job, predicts meaningful outcomes.

Several recent meta-analyses yield support for the stability and predictive power of values, interests, and workplaces preferences among college students and employed adults. For example:

  • Low, Yoon, Roberts, and Rounds (2005) used a meta-analysis of 66 studies reporting 107 samples totaling 23,665 participants to establish vocational interests as arguably the most stable individual difference construct in psychology. Stability coefficients exceeded those of
    personality traits, particularly among participants who have reached young-adulthood. This evidence supports the use of interests to inform long-term career decision-making.7
  • Jin and Rounds (2012) used a meta-analysis of 22 studies to investigate the rank-order stability (n = 28,853 participants) and mean-level change (n = 14,109) of work values. They found high levels of stability over time (ρ =.69), with highest stability experienced by adults after entering the workforce, supporting the use of values to inform long-term career decision-making.8
  • Nye, Su, Rounds, and Drasgow (2012) examined vocational interests as a predictor of job performance using a meta-analysis of 60 studies (n = 15,301) spanning six decades. They found overall correlations for interest-based P-E fit of .36 with job performance, .30 with students’ grades, .30 with employee’s task performance, .37 with organizational citizenship behaviors, and .36 with persistence in jobs. As a point of comparison, these effect sizes compare favorably to the .31 relationship found between behaviorally-based interviews and subsequent job performance, and clearly establish support for the use of interest-based P- E fit to predict key performance indicators.9
  • Kristof-Brown, Zimmerman, and Johnson (2005) found that person-organization (P-O) fit based on organizational culture preferences (using same measurement approach PathwayU) correlated .29 with job satisfaction (n = 16,706), .27 with organizational commitment (n = 15,316), and -.19 with intent to quit (n = 14,835), whereas person-job (P-J) fit correlated .28 with job satisfaction, .21 with organizational commitment, and .20 with overall performance.10

Collectively, these meta-analyses establish evidence that the PathwayU assessments and methodology measures stable constructs that are predictive of important career development outcomes.

Empirically-Supported Feedback and Support

What works in career interventions?

Evidence suggests that effective career choice interventions have been developed across a range of modalities, including individual or group counseling, career development courses, and computer-assisted career guidance systems.11 Effect sizes have ranged from .30 to .50 (small to moderate) in meta-analyses comparing career interventions to a no-treatment control.12 One meta- analytic review identified five “critical ingredients” included in effective career interventions: (a) individualized interpretation and feedback, (b) up-to-date occupational information, (c) attention to support-building, (d) opportunities to learn from models of targeted behavior, and (e) written exercises.13 Given this evidence, PathwayU’s PathwayU portal and accompanying materials were designed to incorporate all five of these intervention components.

Finally, the initial concept that became PathwayU was tested in a study funded by the U.S Department of Educations’ Fund for the Improvement of Post-Secondary Education (FIPSE). This study used a randomized controlled trial design to compare three conditions:

  1. the software alone;
  2. the software plus a 90-minute workshop; and
  3. a wait-list control condition.

More than 600 students from three community college campuses and one four-year university served as participants, with follow-up data collection targeting only the community college students. Results established evidence of the effectiveness of this earlier version of the PathwayU portal, particularly when paired with a workshop, on key career development
outcomes such as:

  • confidence in one’s ability to successfully navigate the decision-making process;
  • severity of career decision difficulties; and
  • a sense of confidence that attaining one’s career goals will result in valued outcomes

Results also suggested that the effectiveness of the software and workshop was equivalent across gender, race/ethnicity, disability status, career decision readiness, and sense of relative control over one’s career decision-making. Although the effects were modest in magnitude, they were in predicted directions, and trends suggested that effects on some key outcomes (e.g., career decision self-efficacy, academic major satisfaction, and self-efficacy strivings) were maintained over a one-year period.14

Conclusion and Summary

The PathwayU platform is evolving and is updated continually based on new scientific evidence as it emerges. Nevertheless, the current PathwayU product is supported by the best available science in several ways, such as: (1) psychometrically-sound assessments, (2) a well-supported predictive model used to suggest career paths that fit, and (3) empirically-supported career development feedback and support.

  1. Dawis, R. V., & Lofquist, L. H. (1984). A psychological theory of work adjustment. Minneapolis: University of Minnesota Press.
  2. Holland, J. L. (1997). Making vocational choices: A theory of vocational personalities and work environments (3rd Ed.). Odessa, FL: Psychological Assessment Resources.
  3. Wilson, C. L., Huang, J. L., & Kraiger, K. (2013). Personality and the analysis, design, and delivery of training. In R. Tett & N. Christiansen (Eds.), Handbook of Personality and Work (pp. 543-564). NY: Routledge.
  4. Ashton, M. C., & Lee, K. (2001). A theoretical basis for the major dimensions of personality. European Journal of Personality, 15(5), 327-353.
  5. O’Reilly, C. A., Chatman, J. & Caldwell, D. F. (1991). People and organizational culture: A profile comparisons approach to assessing person-organizational fit. Academy of Management Journal, 34, 487-516; Judge, T. A., & Cable, D. M. (1997). Applicant personality, organizational culture, and organizational attraction. Personnel Psychology, 50, 359-394; Sarros, J. C., Gray, J., Densten, I. L., & Cooper, B. (2005). The Organizational Culture Profile Revisited and Revised: An Australian Perspective. Australian Journal of Management, 30, 159-182
  6. Hansen, J. C. (2013). A person-environment fit approach to cultivating meaning. In B. Dik, Z; Byrne, & M. Steger (Eds.), Purpose and meaning in the workplace (pp. 37-56). Washington, DC: American Psychological Association.
  7. vii Low, K., S. D., Yoon, M., Roberts, B. W., & Rounds, J. (2005). The stability of vocational interests from early adolescence to middle adulthood: A quantitative review of longitudinal studies. Psychological Bulletin, 131, 713-737.
  8. Jin, J., & Rounds, J. (2012). Stability and change in work values: A meta-analysis of longitudinal studies. Journal of Vocational Behavior, 80, 326-339.
  9. Nye, C. D., Su, R., Rounds, J., & Drasgow, F. (2012). Vocational interests and performance: A quantitative summary of over 60 years of research. Perspectives on Psychological Science, 7, 384-403.
  10. Kristof-Brown, A. L., Zimmerman, R. D., & Johnson, E. C. (2005). Consequences of individuals’ fit at work: A meta- analysis of person-job, person-organization, person-group, and person-supervisor fit. Personnel Psychology, 58, 281-342.
  11. Whiston, S. C., & Rihardja, D. (2008). Vocational counseling process and outcome. In S. Brown & R. Lent, Eds. Handbook of Counseling Psychology (4th ed., pp. 444-461). New York: Wiley.
  12. Oliver, L. W., & Spokane, A. R. (1988). Career-intervention outcome: What contributes to client gain? Journal of Counseling Psychology, 35, 447–462; Spokane, A. R., & Oliver, L. W. (1983). Outcomes of vocational intervention. In S. H. Osipow & W. B. Walsh (Eds.), Handbook of vocational psychology (pp. 99-136). Hillsdale, NJ: Erlbaum; Whiston, S. C; Sexton, T. L., & Lasoff, D. L. (1998). Career-intervention outcome: A replication and extension of Oliver and Spokane (1988). Journal of Counseling Psychology, 45, 150–165.
  13. Brown, S. D., & Ryan Krane, N. E. (2000). Four (or five) sessions and a cloud of dust: Old assumptions and new observations about career counseling. In S. D. Brown & R. W. Lent (Eds.), Handbook of counseling psychology (3rd ed., pp. 740–766). New York: Wiley.
  14. xiv Dik, B. J., & Kraiger, K. (2011, November). Online career assessment: Matching profiles and training programs. Paper presented at the FIPSE Comprehensive Program Project Director’s Conference, Washington, DC