Motivation Insights® 2020 Technical Manual Version 1.0

Motivation Insights® 2020 Technical Manual Version 1.0

The following manual contains information on the history and development of the concept of motivation from its beginnings to current implementation of these concepts as psychometric assessments. Included in this manual are a host of mathematical, statistical, and psychometric analyses used to establish evidence of validity and reliability of the TTI Success Insights Motivation Insights assessment.

The Industry 4.0 Talent Pipeline: A Generational Overview of the Professional Competencies, Motivational Factors & Behavioral Styles of the Workforce

The Industry 4.0 Talent Pipeline: A Generational Overview of the Professional Competencies, Motivational Factors & Behavioral Styles of the Workforce

To prosper in the Industry 4.0 ecosystem, individuals and organizations will be required to develop 21st century skill sets. This research seeks to identify emerging trends, pinpoint challenges and gain data-driven insights into the forces shaping the technical talent pipeline of Industry 4.0 in the United States. To successfully navigate the Industry 4.0 environment (and beyond), organizations will need to integrate four different generations (soon to be five) in their workforce. Next-Generation Leaders were found to be lacking in creativity and innovation and conceptual thinking, critical skills required in navigating an Industry 4.0 environment. This should serve as a wake-up call to educators tasked with overhauling an antiquated system, particularly at the graduate level. Based on responses to a series of questions using the TTI TriMetrix DNA assessment suite a data-driven, validated assessment instrument, this research presents an overview of the development of 25 professional competencies that contribute to superior performance.

Learning to Be an Interdisciplinary Researcher: Incorporating Training About Dispositional and Epistemological Differences Into Graduate Student Environmental Science Teams

Learning to Be an Interdisciplinary Researcher: Incorporating Training About Dispositional and Epistemological Differences Into Graduate Student Environmental Science Teams

Effective interdisciplinary research (IR) teams require skills of collaboration, sharing, and abilities to integrate knowledge from diverse disciplines. Pre-post data was collected using three learning modules designed to support the development of collaboration and teamwork skills in the context of IR. Results showed (1) participants learned and practiced essential collaborative skills in authentic contexts; (2) training modules were valued and helped participants recognize the important role that personal dispositional characteristics have on IR teams; (3) participants’ confidence in adapting to differences among team members increased; and (4) participants recognized that effective collaboration requires intentionality. This paper also introduces the concept of dispositional distancing.

An Application of Logistic Regression in Identifying Target Populations Using TriMetrix EQ Variables

An Application of Logistic Regression in Identifying Target Populations Using TriMetrix EQ Variables

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.

Emerging Trends & Traits Shaping the Industry 4.0 Talent Pipeline

Emerging Trends & Traits Shaping the Industry 4.0 Talent Pipeline

To successfully navigate the Industry 4.0 environment (and beyond), organizations will need to integrate four different generations in their workforce and much more. TTI SI assessment data provides the cornerstone article in this 2019 Automation Alley State of Michigan peer-reviewed conference report.