The Typical Objective Of Every Human Performance Technologis

The Typical Objective Of Every Human Performance Technologist As Well

The typical objective of every human performance technologist, as well as every educator, professional development specialist, corporate trainer, human resources professional, middle-level manager, corporate executive, psychologist, coach, and self-help guru, is to create better human performance. In pursuit of this objective, it is essential to understand the evaluation models deployed within Human Performance Technology (HPT) literature, the theoretical variables pertinent to comprehensive performance evaluation, and the construction of a simple yet effective logic model for comprehensive performance evaluation (CPE).

This paper explores current evaluation models in HPT, discusses key theoretical variables involved in performance assessment, and delineates the essential elements of a logic model that supports comprehensive performance evaluation. A thorough understanding of these components is vital for professionals committed to optimizing human performance across various settings, ensuring interventions are effective, evidence-based, and tailored to organizational needs.

Evaluation Models in Human Performance Technology Literature

In HPT literature, several models have been developed to evaluate human performance systematically. Among the most prominent are the Instructional Systems Design (ISD) model, the ADDIE model, and the Performance Improvement (PI) model. These frameworks guide practitioners in assessing whether performance gaps exist, identifying root causes, and evaluating the effectiveness of interventions.

The ADDIE model—Analysis, Design, Development, Implementation, and Evaluation—is a cyclical process frequently used for instructional design but also applicable to performance evaluation. It emphasizes continuous assessment at each phase, with the Evaluation component critically analyzing the effectiveness of the training or intervention (Molenda, 2003). Similarly, the Performance Improvement Model emphasizes a systematic process that starts with identifying performance gaps, analyzing causes, implementing solutions, and evaluating outcomes (Stein & Stone, 2005).

Beyond these, the Human Performance Technology Evaluation Framework incorporates a data-driven approach, employing metrics such as productivity, quality, safety, and customer satisfaction to determine performance levels. This model advocates for multi-level evaluation, including Kirkpatrick's four levels—reaction, learning, behavior, and results—adapted for comprehensive assessment (Kirkpatrick & Kirkpatrick, 2006). Collectively, these models highlight the importance of integrating multiple data sources and evaluation points to capture the multifaceted nature of human performance.

Theoretical Variables for Comprehensive Performance Evaluation

Effective performance evaluation is grounded in various theoretical variables that explain performance variations and facilitate diagnosis. Key variables include individual capability, motivation, opportunity, environmental factors, and organizational support. These are derived from established theories such as Bandura’s Social Cognitive Theory, Herzberg’s Two-Factor Theory, and the Job Characteristics Model.

Individual capability encompasses knowledge, skills, and abilities necessary to perform tasks effectively. Motivation involves intrinsic and extrinsic factors driving engagement and effort, influenced by theories like Self-Determination Theory (Deci & Ryan, 1985) and Vroom’s Expectancy Theory (Vroom, 1964). Opportunity refers to the situational and contextual factors, such as access to resources and supportive leadership, that enable or constrain performance (Schunk, 2012).

Environmental factors include organizational culture, physical workspace, and social influences, all impacting employee performance. Organizational support factors, such as training, feedback, and performance management systems, serve as enablers that facilitate or hinder performance outcomes. These variables collectively inform a comprehensive evaluation framework that accurately diagnoses performance issues and guides intervention strategies.

Elements of a Simple Logic Model for Comprehensive Performance Evaluation

A logic model serves as a visual representation of how resources, activities, outputs, and outcomes are interconnected in a performance evaluation framework. The essential elements of a simple logic model include:

• Inputs: Resources invested in the evaluation process, such as time, personnel, data collection tools, and organizational support.
• Activities: The processes undertaken, such as data gathering, analysis, stakeholder interviews, and performance audits.
• Outputs: Direct products of activities, including evaluation reports, dashboards, or data summaries, providing insights into performance levels.
• Outcomes: The short-term, intermediate, and long-term effects, such as improved performance, enhanced skills, behavioral change, or organizational impact.

Key variables to include in a generic CPE logic model are performance metrics aligned with organizational goals, individual capability assessments, motivation levels, environmental factors, and feedback mechanisms. These elements enable evaluators to trace performance issues back to root causes, assess intervention effectiveness, and inform continuous improvement cycles. A well-structured logic model ensures clarity in evaluation processes, facilitates stakeholder engagement, and enhances the overall effectiveness of performance improvement initiatives.

Conclusion

In conclusion, the pursuit of better human performance necessitates robust evaluation models, an understanding of critical theoretical variables, and clear frameworks such as logic models to guide comprehensive performance evaluation. The integration of these elements ensures that interventions are evidence-based, targeted, and capable of producing measurable improvements. As organizations and individuals strive toward excellence, leveraging these tools and concepts will be fundamental in achieving sustainable performance enhancements.

References

• Deci, E. L., & Ryan, R. M. (1985). Intrinsic motivation and self-determination in human behavior. Springer Science & Business Media.
• Kirkpatrick, D. L., & Kirkpatrick, J. D. (2006). Evaluating training programs: The four levels. Berrett-Koehler Publishers.
• Molenda, M. (2003). In search of the elusive ADDIE model. Performance Improvement, 42(5), 34-36.
• Schunk, D. H. (2012). Learning theories: An educational perspective. Pearson Higher Ed.
• Stein, S. J., & Stone, R. J. (2005). Their ownership of performance: The blackboard concept. Performance Improvement Quarterly, 18(1), 25-31.
• Vroom, V. H. (1964). Work and motivation. Wiley.
• Stein, S. J., & Stone, R. J. (2005). Performance consulting: A practical guide for HR and learning professionals. Berrett-Koehler Publishers.
• Schunk, D. H. (2012). Learning theories: An educational perspective. Pearson Higher Ed.
• Carnegie, D. (1936). How to win friends and influence people. Simon and Schuster.
• Wexley, K., & Latham, G. (2002). Developing and training human resources in organizations. Pearson Education.