Technological advancements throughout society are occurring at an ever-increasing rate. Neurological discoveries and associated investigative tools are leading to new understandings of human behavior never before explored. While the future of artificial intelligence for hiring and professional development is making headlines, this science requires time for peer review and refinement of new technologies.
This is the first in a series of monthly articles outlining the International Test Commission’s (ITC) Guidelines for Translating and Adapting Tests. The ITC guidelines are provided in a six-category format that includes the topics pre-condition, test development, confirmation, administration, scoring and interpretation, and documentation. It is the goal of this series to provide the motivation behind and an outline for the TTI Success Insights translation protocol.
This is the second in a series of monthly articles outlining the International Test Commission’s (ITC) Guidelines for Translating and Adapting Tests. The ITC guidelines are provided in a six-category format that includes the topics pre-condition, test development, confirmation, administration, scoring and interpretation, and documentation. It is the goal of this series to provide the motivation behind and an outline for the TTI Success Insights translation protocol.
This study establishes relationships between several external variables based on demographic information obtained using the O*Net job classification model and the scales of the TTI Success Insights TriMetrix EQ assessment. The work uses a logistic regression modeling approach to derive statistically significant functional relationships between the TriMetrix EQ scales and membership in the job classification group of interest. ROC curve analysis is used to show the classification algorithm outperforms the standard random selection technique.
In many cases, organization such as the American Psychological Association, provide general guidelines without providing specific guidance. As an example, we discuss the concepts of acceptable levels of reliability coefficients, as measured by the so-called “alpha” coefficients where after several decades there remains a lack of consensus.
