Building Blocks of the Tucareers framework
Few of the improvements to the issues highlighted in the previous post which the Tucareers framework addresses are
- It considers multiple traits in matching individuals to different careers and provide relative fitments (not only best fits).
- Recommendations are made at age appropriate and well researched career taxonomies like clusters, pathways, job families, specific occupations and roles
- The recommendations are based on data from industry. The psychometric validation ensures predictive validity besides high reliability.
- Build on the analytics driven paradigm to better describe, predict outcomes, makes recommendations and continuously learn from assessment outcomes.
- Career recommendations include knowledge and skill areas candidates can build on to achieve their career goals.
- Detailed content on careers and cross linkages to career standards worldwide.
- It provides multi lingual assessment support, recommendation across job zones and mass deployment features.
The improvements are summarized in the five key building blocks that are highlighted below
Research Driven Framework
The Tucareers framework has been developed based on cross disciplinary research in the areas of Decision sciences, IT and career decision making. The outcomes have been validated as part of a PhD thesis and published research papers. Tle framework is build on O*NET the world’s largest occupational data base in the world. The assessment framework uses standardized & non proprietary scales. Career recommendations are based on assessment of multiple age appropriate traits. Career recommendations are based on established career taxonomies and provide cross linkages to national and international career standards. For more details read here
Analytics Based Approach
Recommendations are based on data collected from industry participants across the world of work. Since we can statistically compare profiles on several aspects, both strengths and weaknesses are recognized and considered for identifying most accurate career matches. For advanced usage a prediction model is used for determining an individual’s satisfaction, tenure and estimating life time earnings in different careers, thereby facilitating choices. A culture based learning and recommendation framework is provided to help choose from between shortlisted options. For more details read here
Multi Trait Assessments
The right choice of career needs an alignment of the job requirements to multiple internal characteristics (or traits) of the individual. For instance, an alignment of interests and values ensures that the individual stays motivated and eager to learn, and feels satisfied and happy performing his duties. On the other hand, the organization also looks for a match of abilities, personality, skills, knowledge and work context preferences so that the individual’s performance and productivity is as per the requirements of the role. Lack of alignment of the traits often leads to burn outs, dissatisfaction, performance issues and shorter tenures. The tucareers career tests consider multiple traits for their recommendations. The traits included consider age appropriateness and the cognitive abilities of individuals to respond to the assessments. For more details read here
Features for mass adoption
Giving the growing need for career guidance in emerging economies, there is a need for a robust platform keeping group counseling and mass usage in mind. Several features are provided to facilitate this. The multi trait assessment capabilities provide detailed reports with navigable recommendations at multiple levels (clusters, job families, pathways, specific careers). The framework provides multi lingual support with recommendations mapped to configurable job zones, support for paper/pencil tests etc. Additionally, there are several features for counsellors, like detailed reports that help to field queries and a counselor back end panel for coupon management, bulk invitations, notes etc. For more details read here
Phased Career Decision Model
Latest research recommends that career decision should be a process and not an event. Based on existing research and best practices from existing career decision models we have developed a six phased career planning model which we call ONETCPTM . The different phases (Orient, Navigate, Explore, Track, Choose & Plan) makes it easier for the individual to explore the world of work systematically and discover his / her best fitment in it. Besides considering the internal factors or critical individual attributes, the model also considers external factors like salary, job opportunities etc, and cultural and social factors . The phased approach largely reduces risks of wrong recommendations and also makes it easy for the career decision maker reach a final choice. With the phased model it is also possible to empirically evaluate the improvement in career decision making difficulties based on the interventions (Bhatnagar, 2018). For more details read here
In the next post we look at the O*NET Content Model , a key building block of the tucareers framework.
- Bhatnagar, M. (2018). Career guidance in India based on O* NET and cultural variables. International Journal for Educational and Vocational Guidance, 18(1), 81-99.