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IDT837 800 Level Paper: Consulting And Appreciative Inquiry

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IDT837 800 Level Paper: Consulting And Appreciative Inquiry
IDT837 800 Level Paper:
Consulting and Appreciative Inquiry
Introduction
Appreciative Inquiry (AI), as a comparatively new area of inquiry research, presents numerous research opportunities in a variety of contexts and applications. For this literature review, the emphasis is placed on how a consultant in instructional design and technology (IDT) can implement AI to facilitate positive change within a group, organization, or community. Various research studies have been directed towards applying AI to enable positive change in employees, staff, and administrators’ performance, and facilitating improved motivation, commitment, interactions, producing positive change in the workplace (Bushe, 1999, 2001; Cooperrider and Whitney, 2001, 2010).
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discovery, dream, design, and destiny, thus the creation of a label of the “AI model”, or rather, “4-D Model” shown in Figure 1 below:
Figure 1: 4-D Appreciative Inquiry Model
(Cooperrider & Whitney, 2001; Rogers & Fraser, 2003). The four elements all begin with the letter “D”, e.g. Discovery, with the phrase “What gives life?” is first, focusing on the present and what is, the second D is Dream, with the phrase is “What might be?”, focusing on what the community or group needs, while the third D is Design, and the related phrase is “How can it be?” choosing the ideal needed, and the fourth D is Destiny, with the phrase “What will be?”, focusing on how to adapt or change (Cooperrider & Whitney, 2001). The remaining words shown in the 4-D model are action words, e.g. appreciating, envisioning results, co- constructing, and sustaining; combining reflection in learning with active participation in a positive process (Cooperrider & Whitney, 2001). Thus, the procedure of AI includes developing a list of questions based on these four essential elements and processes to use in formal and informal interviews and focus groups to gather information and data for causal analysis to use in discovering what the negative issues and problems are that cause the decline within an organization, and develop a personalized, positive solution to the issue(s) (Cooperrider & Whitney, 2001). The solution or intervention
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the implementers of AI within an organization are so focused on the positive, that they refuse to listen to any discussion about problems or issues that need to be addressed (Bushe, 2001, 2011; Bushe & Kassam, 2005; Rogers & Fraser, 2003; Whitney & Trosten-Bloom, 2010). This attitude of turning a blind eye towards needs is not part of the AI process; AI simply uses the strengths to help move the business towards support for areas of need (Bushe, 2001, 2011; Rogers & Fraser, 2003). Organizations should look at the needs, and then use the business’ strengths to facilitate positive change in the weak areas. This is a strategy that instructors use to address learning issues in the classroom, and it helps promote positive engagement, motivation, and ultimately, success for the learners. Rogers and Fraser present the view that AI is not always appropriate to use in certain situations, and as it takes training and knowledge to implement correctly, it is often misused; students would be so focused on the positive, and apply it without regard to theory or analysis for appropriate decision-making; AI should not be focused only on stating nice things about a plan or program (2003). Bushe issues a call for disciplined and systematic use of AI, and for models to define when, where, and how it is to be used appropriately, thus avoiding AI as

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