Journal of Information Systems Education (JISE)

Volume 29

Volume 29 Issue 4, Pages 225-238

Fall 2018


IT Career Counseling: Are Occupational Congruence and the Job Characteristics Model Effective at Predicting IT Job Satisfaction?


Darrell Carpenter
Longwood University
Farmville, VA 23901, USA

Diana K. Young
Trinity University
San Antonio, TX 78212, USA

Alexander McLeod
Texas State University
San Marcos, TX 78666, USA

Michele Maasberg
Louisiana Tech University
Ruston, LA 71272, USA

Abstract: The IT industry struggles to attract qualified talent despite an exceptional outlook in terms of both job availability and compensation. Similarly, post-secondary academic institutions report difficultiesrecruitingstudents for IT majors. One potential reason for this is that current career counseling practices do not adequately convey relevant job characteristic data to prospective job applicants and academic majors. Accordingly, we report the results of a survey of72 IT professionals regarding their job interests and perceptions of important characteristics of their current job. We use the data to test the efficacy of Holland’s classic occupation congruence model, the basis of current career counseling practices.In addition, we assess an alternate congruence model based on professionals’job perceptions and the Job Characteristics Model of Work Motivation (JCM) to determine which is more effective at predicting desired job outcomes. Results show that a sub-set of JCM constructs including task variety, task identity, and task autonomy is superior to both congruence models in predicting positive job outcomes. This suggeststhat IT career counseling outcomes mightbe improved by emphasizingthe JCMcharacteristics.

Keywords: Job skills, IS major, Careers, STEM, Factors of major selection

Download this article: JISE - Volume 29 Issue 4, Page 225.pdf


Recommended Citation: Carpenter, D., Young, D. K., McLeod, A., & Maasberg, M. (2018). IT Career Counseling: Are Occupational Congruence and the Job Characteristics Model Effective at Predicting IT Job Satisfaction? Journal of Information Systems Education, 29(4), 225-238.