Barriers to Adopting Technology for Teaching and Learning

The purpose of this chapter is to use a cross-cultural research-based evidence to discuss the root causes of barriers to effective technology adoption by evaluating the effect the teaching environment and the ranges of teacher behaviors have on technology adoption. The author described and explained the change processes that teachers go through as they implement new technologies or instructional practices with a view to connecting the change process, the innovation, and the individuals involved in the process. Two overarching frameworks that guided the author's discussion of this chapter and the behavior engineering model (BEM) and the concerns-based model (CBAM) frameworks.

Sales Improvement Initiative Reveals Need for Performance Improvement Interventions

This chapter posits the use of Thomas Gilbert's Behavior Engineering Model to improve human performance in the workplace. The author suggests that it is critical to apply a holistic approach when approaching any human performance improvement initiatives. Sales within an organization is a human performance issue and recurring sales performance problems should be addressed by delving to the root of the human performance issues at hand. It is critical to consider not just the repertoire of human behavior, but also examine the supporting environment, to ensure it provides the necessary impetus to improving performance.

Performance Improvement in Healthcare

Healthcare leadership and department management personnel are tasked with the responsibility of ensuring safe, high-quality patient care delivered by competent and proficient staff. This responsibility often comes in the form of identification of discrepant and erroneous practices that result in subsequent employee disciplinary action process improvement discussions and implementation. This case study presents an example of a sentinel event and how Gilbert's Behavior Engineering Model (BEM) was utilized in the context of a Just Culture to ensure both processes and personnel were adequately supported to meet expected task outcomes.

Blending Front-End Analysis

Performance problems come in all forms. The method presented in this chapter blends the models of three respected Performance improvement icons – Joe Harless, Thomas Gilbert, and Roger Chevalier. Their theoretical and practical approaches are applied to a case study. The three models – 13 Smart Questions (Front-end analysis), Behavior Engineering Model (BEM), and Updated BEM – when combined show ways practitioners can assess and improve performance. The practitioner will develop effective partnerships with clients, gain valuable perspectives on the issues, and their underlying causes. Finally the practitioner will be able to lead a department or an organization in fully analyzing problems and determining how best to solve them.

Blending Front-End Analysis

Performance problems come in all forms. The method presented in this chapter blends the models of three respected Performance improvement icons – Joe Harless, Thomas Gilbert, and Roger Chevalier. Their theoretical and practical approaches are applied to a case study. The three models – 13 Smart Questions (Front-end analysis), Behavior Engineering Model (BEM), and Updated BEM – when combined show ways practitioners can assess and improve performance. The practitioner will develop effective partnerships with clients, gain valuable perspectives on the issues, and their underlying causes. Finally the practitioner will be able to lead a department or an organization in fully analyzing problems and determining how best to solve them.