Changing paradigms in career assessments

Psychometric tests have been in use for several decades for facilitating career decisions for individuals, undecided with their career choices. Traditionally these tests have been done using paper – pencil, however computer aided career guidance has also become popular .

Globally the most popular theory for providing career guidance to students, has been the Holland’s theory of interest, where a person’s interest types are determined as Realistic , Investigative, Artistic, Social, Enterprising or Conventional ,called RIASEC in short. This is then mapped against different careers for determining best matches.

Aptitude tests have also been used to determine an individual’s abilities to work in a career. These tests are designed to assess an individual’s spatial, verbal, arithmetic and logical reasoning skills in timed exam like conditions. Test results are compared against established norms to assess ones abilities and the results helps to determine between choces.  

Personality and Values are other internal attributes that are measured to determine fitment in different careers. Big 5 and MBTI have been popular personality tests and theory of work adjustment provides a scale for measuring work values. Despite there importance, they have been sparingly used for career guidance due to difficulties in assessment & interpretation of results.

Some of the issues highlighted in latest research in career decision making suggests that these existing mechanisms are not sufficient.  

  • Recommendations based on interests alone are too simplistic and hence may not be very helpful to career decision makers.
  • Career decision making should be a process and not an event, hence the need for a guiding framework / model to facilitate self discovery and learning across a lifetime.
  • Non-linear data driven models are needed for determining career fitment based on multiple traits. 
  • Need for internationalization in the field of career guidance. 
  • Need for indigenizing the scales developed primarily in the west before being used in other cultures.

From these, the following improvement areas can be identified

  • Consider multiple traits in matching individuals to different careers and provide relative fitments (not only best fits). Recommendations to be made at multiple levels like clusters, pathways, job family, choosing between specific careers/roles .
  • Need for data from industry for making data driven decisions. Just psychometric validation of the reliability and content validity is not sufficient, predictive validity of scales is essential.
  • Analytics driven approach to better describe, predict outcomes, makes recommendations and continously learn from assessment outcomes. 
  • Career recommendations should include education options to consider. knowledge and skill areas candidates can build on to achive their career goals.
  • Detailed content on careers and cross linkages to career standards worldwide.
  • The need for multi lingual support, recommendation across job zones and robust features to support group counselling needs emerging from demographically young economies where labour markets are maturing.