Sample Education Paper on Appreciative Inquiry

To: School Education Leaders

From: Student name

Subject: Appreciative Inquiry (AI) as a Strategy for Educational Change Management

The objective of this memo is to share with you all a change management model, which I recently learnt and I believe most of you would be interested in as an organizational tool. Appreciative Inquiry (AI) has been proven efficient as a strategy to move organizations from where they are to where they desire to be. Organizations both within and outside the educational sector can therefore use AI to help identify and focus their resources on the paths towards realizing their goals. In the school setting, AI can be help in diverting attention from the present negatives, or rather ‘what is not’ to future positives or ‘what might be.’ By focusing on the core competencies in the organization, AI helps to identify strategies that can be effected to realize organizational goals. Based on my own understanding and experience with AI, I can support Fifolt and Lander (2013) in their position that it requires reflection and introspection, and is as well dependent on collaboration between involved parties.

For us in the education sector, it is important to note that AI is not organization specific, but is flexible. It is also best on theoretically sound and field tested approaches which make the principles underlying practice generalizable (Bushe, 2012). As education leaders, I would encourage each one to consider applying AI as an organizational change management tool in their respective organizations. The best approach to applying this tool would be to focus on the 4 phases of action, which are modeled by a 4 –D approach namely: Discovery, Dream, Design and Destiny phases. The phases are cyclic as shown in the diagram below. While the discovery phase leads the organization towards understanding their needs and the feelings attached to particular points in time in the organization, the destiny phase is the final, point of actualization regarding the specific change being attained.

Figure 1: 4-D Model of Appreciative Inquiry

When applying the AI approach to organizational change, the discovery phase entails uncovering or illuminating the factors that resulted in the success of the human system at a specific time within the context of the system attributes under consideration (Sommerville & Farner, 2012). The discovery phase is conducted through story telling sessions, in which project team members working in groups or pairs share past stories of success. The objective of such sharing would be to get areas of common interest or common themes that cut across different groups. Based on the shared themes, expert diagnoses would then follow to help identify the actual organizational factors that led to success at the identified and described times. It is from there that decisions can be made on what practices to undertake to get the organization into the best position for its success.

The dream phase entails thinking about what the organization would be preferred to be like. Creating a picture of the desired future is conducted by asking compelling questions of the group of change management. From the questions, an image is generated of what the human system in the organization should be like (Bushe, 2012). Through shared strengths and objectives, participants can get bolder images of positive features of the organization, making their resolve stronger towards the achievement of organizational goals. In most cases, the collaborative feature of the process makes it easier to comprehend the combined organizational needs and desires and to work towards accomplishing the organizational goals and objectives.

The design phase of the AI model involves translating the dreams of the participatory groups into actions. Designing the possible solution revolves around voting for the best approach towards the desired change, mind mapping to determine the efficacy of potential solutions, engaging in discussions on the resources required and the competencies at hand, role designation, prototyping the agreed upon solution and eventually testing the developed prototype. Any change has to consider the potential for success and the collaborative approach adopted. Fry (2014) suggests that most lessons in the design phase are learnt through collaborative creation since design is creativity and innovation oriented process. The objective of the design phase in any organization practicing AI should go beyond mere design thinking to cover actual design practices.

The last D in the model represents the destiny of the organization. As expected, the destiny is the replica of the visualized dream, which has to be planned for and designed for efficiency. According to Fry (2014), destiny stems for the implementation of the designed change process. Consequently, the destiny in any change process should not be culmination of AI practice, but rather and open ended journey towards a series of organizational success stories. From each organization’s perspective, the destiny may appear differently, or rather like stepped processes in the

As my fellow leaders, I would advise that you implement AI practices in managing change within your organizations, not only because of the perceived simplicity of the process, but also due to the many benefits that AI can result in within the organizational setting. For instance, the process has been compared to a variety of other effective change processes such as SOAR, which focuses on the strengths, opportunities, aspirations and results. Other strengths of the process center on its effectiveness as a driver of result oriented change processes. When using AI, various principles have to be at the back of your minds since the success of the process depends on how efficiently you will base your decisions on the principles underlying AI.

From Fifolt and Lander (2013), the AI approach is described based on its principles such as constructionist outlook, simultaneity, and poetic characteristic and anticipatory. AI is constructionist in that it begins from the visualization of the successful human systems in the organizations past. Furthermore, it develops changes based on expectations and particular dreams of the future. In terms of simultaneity, the approach is characterized by inquiry, relationships and collaboration, which work simultaneously to result in the desired change. When engaging in AI therefore, education leaders should always encourage thinking outside of the conventional practices and focus on innovative and collaborative approaches that can drive the human systems towards the desired outcome. The anticipatory characteristic on the other hand is founded on the positive picture developed prior to initiating any aspect of AI. Beginning from the discovery through the dream phases of AI, it is clear that organizations have to reflect on what they desire and thus develop expectations of the future. Needless to say, the process is also built on a positivity premise in that in all instances of AI application, the objective is always to move from a position of poor human systems performance to one of successful human systems performance, subject to the core competencies of the organization.

Given that the advantages and principles of AI are now clear, it would be good to also understand the resources you will need to effectively put in place AI principles in your organization. Fifolt and Lander (2013) provided an outline of the requirements needed for AI to be practiced effectively. The most important resource in AI implementation is the organizational data. In any context, data will be the prerequisite for effective AI implementation. This is because from the discovery phase, the organization would need stories, and unless they are backed up by hard facts and data, it would be possible for people to create non-existent success stories for their own selfish gains. Data organization is thus crucial, from the point of conducting interviews, through to providing reports on the efficacies of new tested systems. According to Priest, Kaufmann, Brunton and Seibel (2013) using AI as an organizational tool for change requires input in terms of time, money and other organizational resources. When the targeted change is on the human elements, it may be necessary to conduct trainings at time to pool together knowledge and competencies.

Priest et al. (2013) asserted that organizational change towards adoption of the AI strategy has to begin with those who have the authority to drive change in the organization. It is therefore my desire that all of the education leaders reading this will be able to accept and initiate change towards the application of AI as an organizational practice. Resource availability notwithstanding, organizations still needs people to stand and fight for the right approaches to change management. In the education sector, change management can be challenging at times due to resistance. When the education leaders in the society rise up to give a viable and flexible approach to change management, we will no longer have to fight for rightful placement of our organizations.

By: Student name



Bushe, G. (2012). Foundations of appreciative inquiry: History, criticism and potential. AI Practitioner, 14(1): 8- 20. Retrieved from

Fifolt, M. and Lander, L. (2013). Cultivating change using appreciative inquiry. New Directions for Student Services, 143: 19- 30.

Fry, R. (2014). Appreciative inquiry, In The Sage Encyclopedia of Action Research. Sage Publications.

Priest, K.L. Kaufmann, E.K., Brunton, S. and Seibel, M. (2013). Appreciative inquiry: A tool for organizational programmatic and project focused change. Journal of Leadership Education, 12(1): 18- 33.

Sommerville, M.M. and Farner, M. (2012). Appreciative inquiry: A transformative approach for initiating shared leadership and organizational learning. University Libraries Librarian and Staff Articles, 38: 7- 24. Retrieved from